Add observability support to existing vector stores

Add observability support to:
 - Cassandra
 - Chroma
 - Elasticsearch
 - Milvus
 - Neo4j
 - OpenSearch
 - Qdrant
 - Redis
 - Typesense
 - Weaviate
 - Pinecone
 - Oracle
 - Gemifire
 - MongoDB
 - HanaDB

 Add autoconfiguration obsrvability for the above vector stores.
 Add integration tests for all vector stores.

spring-ai-core/src/main/java/org/springframework/ai/observation/conventions/VectorStoreProvider.java

@@ -23,7 +23,23 @@ public enum VectorStoreProvider {
 
 	// @formatter:off
         PG_VECTOR("pg_vector"),
-        SIMPLE_VECTOR_STORE("simple_vector_store");
+        AZURE("azure"),
+        CASSANDRA("cassandra"),
+        CHROMA("chroma"),
+        ELASTICSEARCH("elasticsearch"),
+        MILVUS("milvus"),
+        NEO4J("neo4j"),
+        OPENSEARCH("opensearch"),
+        QDRANT("qdrant"),
+        REDIS("redis"),
+        TYPESENSE("typesense"),
+        WEAVIATE("weaviate"),
+        PINECONE("pinecone"),
+        ORACLE("oracle"),
+        MONGODB("mongodb"),
+        GEMFIRE("gemfire"),
+        HANA("hana"),
+        SIMPLE("simple");
 
         // @formatter:on
 	private final String value;

spring-ai-core/src/main/java/org/springframework/ai/vectorstore/SimpleVectorStore.java

@@ -40,6 +40,7 @@ import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
 import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.core.io.Resource;
 
 import com.fasterxml.jackson.core.JsonProcessingException;
@@ -47,6 +48,8 @@ import com.fasterxml.jackson.core.type.TypeReference;
 import com.fasterxml.jackson.databind.ObjectMapper;
 import com.fasterxml.jackson.databind.ObjectWriter;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * SimpleVectorStore is a simple implementation of the VectorStore interface.
  *
@@ -71,6 +74,14 @@ public class SimpleVectorStore extends AbstractObservationVectorStore {
 	protected EmbeddingModel embeddingModel;
 
 	public SimpleVectorStore(EmbeddingModel embeddingModel) {
+		this(embeddingModel, ObservationRegistry.NOOP, null);
+	}
+
+	public SimpleVectorStore(EmbeddingModel embeddingModel, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		Objects.requireNonNull(embeddingModel, "EmbeddingModel must not be null");
 		this.embeddingModel = embeddingModel;
 	}
@@ -265,7 +276,7 @@ public class SimpleVectorStore extends AbstractObservationVectorStore {
 	@Override
 	public VectorStoreObservationContext.Builder createObservationContextBuilder(String operationName) {
 
-		return VectorStoreObservationContext.builder(VectorStoreProvider.SIMPLE_VECTOR_STORE.value(), operationName)
+		return VectorStoreObservationContext.builder(VectorStoreProvider.SIMPLE.value(), operationName)
 			.withDimensions(this.embeddingModel.dimensions())
 			.withCollectionName("in-memory-map")
 			.withSimilarityMetric(VectorStoreSimilarityMetric.COSINE.value());

spring-ai-core/src/main/java/org/springframework/ai/vectorstore/observation/AbstractObservationVectorStore.java

@@ -38,18 +38,10 @@ public abstract class AbstractObservationVectorStore implements VectorStore {
 	@Nullable
 	private final VectorStoreObservationConvention customObservationConvention;
 
-	public AbstractObservationVectorStore() {
-		this(ObservationRegistry.NOOP, null);
-	}
-
-	public AbstractObservationVectorStore(ObservationRegistry observationRegistry) {
-		this(observationRegistry, null);
-	}
-
 	public AbstractObservationVectorStore(ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customSearchObservationConvention) {
+			VectorStoreObservationConvention customObservationConvention) {
 		this.observationRegistry = observationRegistry;
-		this.customObservationConvention = customSearchObservationConvention;
+		this.customObservationConvention = customObservationConvention;
 	}
 
 	@Override

spring-ai-core/src/main/java/org/springframework/ai/vectorstore/observation/DefaultVectorStoreObservationConvention.java

@@ -44,6 +44,9 @@ public class DefaultVectorStoreObservationConvention implements VectorStoreObser
 
 	private static final KeyValue TOP_K_NONE = KeyValue.of(HighCardinalityKeyNames.TOP_K, KeyValue.NONE_VALUE);
 
+	private static final KeyValue SIMILARITY_THRESHOLD_NONE = KeyValue.of(HighCardinalityKeyNames.SIMILARITY_THRESHOLD,
+			KeyValue.NONE_VALUE);
+
 	private static final KeyValue SIMILARITY_METRIC_NONE = KeyValue.of(HighCardinalityKeyNames.SIMILARITY_METRIC,
 			KeyValue.NONE_VALUE);
 
@@ -89,7 +92,7 @@ public class DefaultVectorStoreObservationConvention implements VectorStoreObser
 	public KeyValues getHighCardinalityKeyValues(VectorStoreObservationContext context) {
 		return KeyValues.of(query(context), metadataFilter(context), topK(context), dimensions(context),
 				similarityMetric(context), collectionName(context), namespace(context), fieldName(context),
-				indexName(context));
+				indexName(context), similarityThreshold(context));
 	}
 
 	protected KeyValue springAiKind() {
@@ -133,6 +136,14 @@ public class DefaultVectorStoreObservationConvention implements VectorStoreObser
 		return TOP_K_NONE;
 	}
 
+	protected KeyValue similarityThreshold(VectorStoreObservationContext context) {
+		if (context.getQueryRequest() != null && context.getQueryRequest().getSimilarityThreshold() >= 0) {
+			return KeyValue.of(HighCardinalityKeyNames.SIMILARITY_THRESHOLD,
+					"" + context.getQueryRequest().getSimilarityThreshold());
+		}
+		return SIMILARITY_THRESHOLD_NONE;
+	}
+
 	protected KeyValue similarityMetric(VectorStoreObservationContext context) {
 		if (StringUtils.hasText(context.getSimilarityMetric())) {
 			return KeyValue.of(HighCardinalityKeyNames.SIMILARITY_METRIC, context.getSimilarityMetric());

spring-ai-core/src/main/java/org/springframework/ai/vectorstore/observation/VectorStoreObservationContext.java

@@ -27,7 +27,6 @@ import io.micrometer.observation.Observation;
  * @author Christian Tzolov
  * @since 1.0.0
  */
-
 public class VectorStoreObservationContext extends Observation.Context {
 
 	public enum Operation {

spring-ai-core/src/main/java/org/springframework/ai/vectorstore/observation/VectorStoreObservationDocumentation.java

@@ -128,6 +128,17 @@ public enum VectorStoreObservationDocumentation implements ObservationDocumentat
 				return "db.vector.query.top_k";
 			}
 		},
+		/**
+		 * Similarity threshold that accepts all search scores. A threshold value of 0.0
+		 * means any similarity is accepted or disable the similarity threshold filtering.
+		 * A threshold value of 1.0 means an exact match is required.
+		 */
+		SIMILARITY_THRESHOLD {
+			@Override
+			public String asString() {
+				return "db.vector.query.similarity_threshold";
+			}
+		},
 		/**
 		 * The dimension of the vector.
 		 */

spring-ai-spring-boot-autoconfigure/pom.xml

@@ -519,6 +519,12 @@
 			<scope>test</scope>
 		</dependency>
 
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
+
 	</dependencies>
 
 </project>

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/azure/AzureVectorStoreAutoConfiguration.java

@@ -19,8 +19,14 @@ import com.azure.core.credential.AzureKeyCredential;
 import com.azure.search.documents.indexes.SearchIndexClient;
 import com.azure.search.documents.indexes.SearchIndexClientBuilder;
 
+import io.micrometer.observation.ObservationRegistry;
+
+import java.util.List;
+
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.azure.AzureVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -48,9 +54,12 @@ public class AzureVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public AzureVectorStore vectorStore(SearchIndexClient searchIndexClient, EmbeddingModel embeddingModel,
-			AzureVectorStoreProperties properties) {
+			AzureVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 
-		var vectorStore = new AzureVectorStore(searchIndexClient, embeddingModel, properties.isInitializeSchema());
+		var vectorStore = new AzureVectorStore(searchIndexClient, embeddingModel, properties.isInitializeSchema(),
+				List.of(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 
 		vectorStore.setIndexName(properties.getIndexName());
 

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/cassandra/CassandraVectorStoreAutoConfiguration.java

@@ -20,9 +20,13 @@ import java.time.Duration;
 import com.datastax.oss.driver.api.core.CqlSession;
 import com.datastax.oss.driver.api.core.config.DefaultDriverOption;
 
+import io.micrometer.observation.ObservationRegistry;
+
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.CassandraVectorStore;
 import org.springframework.ai.vectorstore.CassandraVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.cassandra.CassandraAutoConfiguration;
 import org.springframework.boot.autoconfigure.cassandra.DriverConfigLoaderBuilderCustomizer;
@@ -33,6 +37,7 @@ import org.springframework.context.annotation.Bean;
 
 /**
  * @author Mick Semb Wever
+ * @author Christian Tzolov
  * @since 1.0.0
  */
 @AutoConfiguration(after = CassandraAutoConfiguration.class)
@@ -43,7 +48,8 @@ public class CassandraVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public CassandraVectorStore vectorStore(EmbeddingModel embeddingModel, CassandraVectorStoreProperties properties,
-			CqlSession cqlSession) {
+			CqlSession cqlSession, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 
 		var builder = CassandraVectorStoreConfig.builder().withCqlSession(cqlSession);
 
@@ -61,7 +67,9 @@ public class CassandraVectorStoreAutoConfiguration {
 			builder = builder.returnEmbeddings();
 		}
 
-		return CassandraVectorStore.create(builder.build(), embeddingModel);
+		return new CassandraVectorStore(builder.build(), embeddingModel,
+				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 	@Bean

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/chroma/ChromaVectorStoreAutoConfiguration.java

@@ -18,6 +18,8 @@ package org.springframework.ai.autoconfigure.vectorstore.chroma;
 import org.springframework.ai.chroma.ChromaApi;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.ChromaVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -29,6 +31,8 @@ import org.springframework.web.client.RestClient;
 
 import com.fasterxml.jackson.databind.ObjectMapper;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * @author Christian Tzolov
  * @author Eddú Meléndez
@@ -72,9 +76,11 @@ public class ChromaVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public ChromaVectorStore vectorStore(EmbeddingModel embeddingModel, ChromaApi chromaApi,
-			ChromaVectorStoreProperties storeProperties) {
+			ChromaVectorStoreProperties storeProperties, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 		return new ChromaVectorStore(embeddingModel, chromaApi, storeProperties.getCollectionName(),
-				storeProperties.isInitializeSchema());
+				storeProperties.isInitializeSchema(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 	static class PropertiesChromaConnectionDetails implements ChromaConnectionDetails {

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/elasticsearch/ElasticsearchVectorStoreAutoConfiguration.java

@@ -20,6 +20,8 @@ import org.elasticsearch.client.RestClient;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.ElasticsearchVectorStore;
 import org.springframework.ai.vectorstore.ElasticsearchVectorStoreOptions;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -28,10 +30,13 @@ import org.springframework.boot.context.properties.EnableConfigurationProperties
 import org.springframework.context.annotation.Bean;
 import org.springframework.util.StringUtils;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * @author Eddú Meléndez
  * @author Wei Jiang
  * @author Josh Long
+ * @author Christian Tzolov
  * @since 1.0.0
  */
 
@@ -43,7 +48,8 @@ class ElasticsearchVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	ElasticsearchVectorStore vectorStore(ElasticsearchVectorStoreProperties properties, RestClient restClient,
-			EmbeddingModel embeddingModel) {
+			EmbeddingModel embeddingModel, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 		ElasticsearchVectorStoreOptions elasticsearchVectorStoreOptions = new ElasticsearchVectorStoreOptions();
 
 		if (StringUtils.hasText(properties.getIndexName())) {
@@ -57,7 +63,8 @@ class ElasticsearchVectorStoreAutoConfiguration {
 		}
 
 		return new ElasticsearchVectorStore(elasticsearchVectorStoreOptions, restClient, embeddingModel,
-				properties.isInitializeSchema());
+				properties.isInitializeSchema(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 }

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/gemfire/GemFireVectorStoreAutoConfiguration.java

@@ -19,6 +19,8 @@ package org.springframework.ai.autoconfigure.vectorstore.gemfire;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.GemFireVectorStore;
 import org.springframework.ai.vectorstore.GemFireVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -26,8 +28,11 @@ import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
 import org.springframework.boot.context.properties.EnableConfigurationProperties;
 import org.springframework.context.annotation.Bean;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * @author Geet Rawat
+ * @author Christian Tzolov
  */
 @AutoConfiguration
 @ConditionalOnClass({ GemFireVectorStore.class, EmbeddingModel.class })
@@ -45,7 +50,8 @@ public class GemFireVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public GemFireVectorStore gemfireVectorStore(EmbeddingModel embeddingModel, GemFireVectorStoreProperties properties,
-			GemFireConnectionDetails gemFireConnectionDetails) {
+			GemFireConnectionDetails gemFireConnectionDetails, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 		var config = new GemFireVectorStoreConfig();
 
 		config.setHost(gemFireConnectionDetails.getHost())
@@ -57,7 +63,9 @@ public class GemFireVectorStoreAutoConfiguration {
 			.setVectorSimilarityFunction(properties.getVectorSimilarityFunction())
 			.setFields(properties.getFields())
 			.setSslEnabled(properties.isSslEnabled());
-		return new GemFireVectorStore(config, embeddingModel, properties.isInitializeSchema());
+		return new GemFireVectorStore(config, embeddingModel, properties.isInitializeSchema(),
+				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 	private static class PropertiesGemFireConnectionDetails implements GemFireConnectionDetails {

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/hanadb/HanaCloudVectorStoreAutoConfiguration.java

@@ -22,6 +22,8 @@ import org.springframework.ai.vectorstore.HanaCloudVectorStore;
 import org.springframework.ai.vectorstore.HanaCloudVectorStoreConfig;
 import org.springframework.ai.vectorstore.HanaVectorEntity;
 import org.springframework.ai.vectorstore.HanaVectorRepository;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -29,8 +31,11 @@ import org.springframework.boot.autoconfigure.data.jpa.JpaRepositoriesAutoConfig
 import org.springframework.boot.context.properties.EnableConfigurationProperties;
 import org.springframework.context.annotation.Bean;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * @author Rahul Mittal
+ * @author Christian Tzolov
  * @since 1.0.0
  */
 @AutoConfiguration(after = { JpaRepositoriesAutoConfiguration.class })
@@ -41,13 +46,17 @@ public class HanaCloudVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public HanaCloudVectorStore vectorStore(HanaVectorRepository<? extends HanaVectorEntity> repository,
-			EmbeddingModel embeddingModel, HanaCloudVectorStoreProperties properties) {
+			EmbeddingModel embeddingModel, HanaCloudVectorStoreProperties properties,
+			ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 
 		return new HanaCloudVectorStore(repository, embeddingModel,
 				HanaCloudVectorStoreConfig.builder()
 					.tableName(properties.getTableName())
 					.topK(properties.getTopK())
-					.build());
+					.build(),
+				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 }

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/milvus/MilvusVectorStoreAutoConfiguration.java

@@ -17,6 +17,7 @@ package org.springframework.ai.autoconfigure.vectorstore.milvus;
 
 import java.util.concurrent.TimeUnit;
 
+import io.micrometer.observation.ObservationRegistry;
 import io.milvus.client.MilvusServiceClient;
 import io.milvus.param.ConnectParam;
 import io.milvus.param.IndexType;
@@ -25,6 +26,8 @@ import io.milvus.param.MetricType;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.MilvusVectorStore;
 import org.springframework.ai.vectorstore.MilvusVectorStore.MilvusVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -51,7 +54,8 @@ public class MilvusVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public MilvusVectorStore vectorStore(MilvusServiceClient milvusClient, EmbeddingModel embeddingModel,
-			MilvusVectorStoreProperties properties) {
+			MilvusVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 
 		MilvusVectorStoreConfig config = MilvusVectorStoreConfig.builder()
 			.withCollectionName(properties.getCollectionName())
@@ -62,7 +66,9 @@ public class MilvusVectorStoreAutoConfiguration {
 			.withEmbeddingDimension(properties.getEmbeddingDimension())
 			.build();
 
-		return new MilvusVectorStore(milvusClient, embeddingModel, config, properties.isInitializeSchema());
+		return new MilvusVectorStore(milvusClient, embeddingModel, config, properties.isInitializeSchema(),
+				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 	@Bean

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/mongo/MongoDBAtlasVectorStoreAutoConfiguration.java

@@ -17,7 +17,9 @@ package org.springframework.ai.autoconfigure.vectorstore.mongo;
 
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.MongoDBAtlasVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.BeansException;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.beans.factory.config.BeanPostProcessor;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
@@ -31,6 +33,8 @@ import org.springframework.data.mongodb.core.convert.MongoCustomConversions;
 import org.springframework.util.MimeType;
 import org.springframework.util.StringUtils;
 
+import io.micrometer.observation.ObservationRegistry;
+
 import java.util.Arrays;
 
 /**
@@ -46,7 +50,8 @@ public class MongoDBAtlasVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	MongoDBAtlasVectorStore vectorStore(MongoTemplate mongoTemplate, EmbeddingModel embeddingModel,
-			MongoDBAtlasVectorStoreProperties properties) {
+			MongoDBAtlasVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 
 		var builder = MongoDBAtlasVectorStore.MongoDBVectorStoreConfig.builder();
 
@@ -61,7 +66,9 @@ public class MongoDBAtlasVectorStoreAutoConfiguration {
 		}
 		MongoDBAtlasVectorStore.MongoDBVectorStoreConfig config = builder.build();
 
-		return new MongoDBAtlasVectorStore(mongoTemplate, embeddingModel, config, properties.isInitializeSchema());
+		return new MongoDBAtlasVectorStore(mongoTemplate, embeddingModel, config, properties.isInitializeSchema(),
+				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 	@Bean

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/neo4j/Neo4jVectorStoreAutoConfiguration.java

@@ -19,6 +19,8 @@ import org.neo4j.driver.Driver;
 
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.Neo4jVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -26,9 +28,12 @@ import org.springframework.boot.autoconfigure.neo4j.Neo4jAutoConfiguration;
 import org.springframework.boot.context.properties.EnableConfigurationProperties;
 import org.springframework.context.annotation.Bean;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * @author Jingzhou Ou
  * @author Josh Long
+ * @author Christian Tzolov
  */
 @AutoConfiguration(after = Neo4jAutoConfiguration.class)
 @ConditionalOnClass({ Neo4jVectorStore.class, EmbeddingModel.class, Driver.class })
@@ -38,7 +43,8 @@ public class Neo4jVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public Neo4jVectorStore vectorStore(Driver driver, EmbeddingModel embeddingModel,
-			Neo4jVectorStoreProperties properties) {
+			Neo4jVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 		Neo4jVectorStore.Neo4jVectorStoreConfig config = Neo4jVectorStore.Neo4jVectorStoreConfig.builder()
 			.withDatabaseName(properties.getDatabaseName())
 			.withEmbeddingDimension(properties.getEmbeddingDimension())
@@ -50,7 +56,9 @@ public class Neo4jVectorStoreAutoConfiguration {
 			.withConstraintName(properties.getConstraintName())
 			.build();
 
-		return new Neo4jVectorStore(driver, embeddingModel, config, properties.isInitializeSchema());
+		return new Neo4jVectorStore(driver, embeddingModel, config, properties.isInitializeSchema(),
+				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 }

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/opensearch/OpenSearchVectorStoreAutoConfiguration.java

@@ -26,6 +26,8 @@ import org.opensearch.client.transport.aws.AwsSdk2TransportOptions;
 import org.opensearch.client.transport.httpclient5.ApacheHttpClient5TransportBuilder;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.OpenSearchVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -33,6 +35,8 @@ import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingClas
 import org.springframework.boot.context.properties.EnableConfigurationProperties;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
+
+import io.micrometer.observation.ObservationRegistry;
 import software.amazon.awssdk.auth.credentials.AwsBasicCredentials;
 import software.amazon.awssdk.auth.credentials.StaticCredentialsProvider;
 import software.amazon.awssdk.http.SdkHttpClient;
@@ -57,12 +61,14 @@ public class OpenSearchVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	OpenSearchVectorStore vectorStore(OpenSearchVectorStoreProperties properties, OpenSearchClient openSearchClient,
-			EmbeddingModel embeddingModel) {
+			EmbeddingModel embeddingModel, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 		var indexName = Optional.ofNullable(properties.getIndexName()).orElse(OpenSearchVectorStore.DEFAULT_INDEX_NAME);
 		var mappingJson = Optional.ofNullable(properties.getMappingJson())
 			.orElse(OpenSearchVectorStore.DEFAULT_MAPPING_EMBEDDING_TYPE_KNN_VECTOR_DIMENSION_1536);
 		return new OpenSearchVectorStore(indexName, openSearchClient, embeddingModel, mappingJson,
-				properties.isInitializeSchema());
+				properties.isInitializeSchema(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 	@Configuration(proxyBeanMethods = false)

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/oracle/OracleVectorStoreAutoConfiguration.java

@@ -19,6 +19,8 @@ import javax.sql.DataSource;
 
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.OracleVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -27,9 +29,12 @@ import org.springframework.boot.context.properties.EnableConfigurationProperties
 import org.springframework.context.annotation.Bean;
 import org.springframework.jdbc.core.JdbcTemplate;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * @author Loïc Lefèvre
  * @author Eddú Meléndez
+ * @author Christian Tzolov
  */
 @AutoConfiguration(after = JdbcTemplateAutoConfiguration.class)
 @ConditionalOnClass({ OracleVectorStore.class, DataSource.class, JdbcTemplate.class })
@@ -39,11 +44,13 @@ public class OracleVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public OracleVectorStore vectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel,
-			OracleVectorStoreProperties properties) {
+			OracleVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 		return new OracleVectorStore(jdbcTemplate, embeddingModel, properties.getTableName(), properties.getIndexType(),
 				properties.getDistanceType(), properties.getDimensions(), properties.getSearchAccuracy(),
 				properties.isInitializeSchema(), properties.isRemoveExistingVectorStoreTable(),
-				properties.isForcedNormalization());
+				properties.isForcedNormalization(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 }

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/pgvector/PgVectorStoreAutoConfiguration.java

@@ -44,7 +44,7 @@ public class PgVectorStoreAutoConfiguration {
 	@ConditionalOnMissingBean
 	public PgVectorStore vectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel,
 			PgVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
-			ObjectProvider<VectorStoreObservationConvention> customSearchObservationConvention) {
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 
 		var initializeSchema = properties.isInitializeSchema();
 
@@ -57,7 +57,7 @@ public class PgVectorStoreAutoConfiguration {
 			.withIndexType(properties.getIndexType())
 			.withInitializeSchema(initializeSchema)
 			.withObservationRegistry(observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP))
-			.withSearchObservationConvention(customSearchObservationConvention.getIfAvailable(() -> null))
+			.withSearchObservationConvention(customObservationConvention.getIfAvailable(() -> null))
 			.build();
 	}
 

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/pinecone/PineconeVectorStoreAutoConfiguration.java

@@ -18,12 +18,16 @@ package org.springframework.ai.autoconfigure.vectorstore.pinecone;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.PineconeVectorStore;
 import org.springframework.ai.vectorstore.PineconeVectorStore.PineconeVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
 import org.springframework.boot.context.properties.EnableConfigurationProperties;
 import org.springframework.context.annotation.Bean;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * @author Christian Tzolov
  */
@@ -34,7 +38,9 @@ public class PineconeVectorStoreAutoConfiguration {
 
 	@Bean
 	@ConditionalOnMissingBean
-	public PineconeVectorStore vectorStore(EmbeddingModel embeddingModel, PineconeVectorStoreProperties properties) {
+	public PineconeVectorStore vectorStore(EmbeddingModel embeddingModel, PineconeVectorStoreProperties properties,
+			ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 
 		var config = PineconeVectorStoreConfig.builder()
 			.withApiKey(properties.getApiKey())
@@ -47,7 +53,9 @@ public class PineconeVectorStoreAutoConfiguration {
 			.withServerSideTimeout(properties.getServerSideTimeout())
 			.build();
 
-		return new PineconeVectorStore(config, embeddingModel);
+		return new PineconeVectorStore(config, embeddingModel,
+				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 }

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/qdrant/QdrantVectorStoreAutoConfiguration.java

@@ -15,10 +15,13 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.qdrant;
 
+import io.micrometer.observation.ObservationRegistry;
 import io.qdrant.client.QdrantClient;
 import io.qdrant.client.QdrantGrpcClient;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.ai.vectorstore.qdrant.QdrantVectorStore;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -28,6 +31,7 @@ import org.springframework.context.annotation.Bean;
 /**
  * @author Anush Shetty
  * @author Eddú Meléndez
+ * @author Christian Tzolov
  * @since 0.8.1
  */
 @AutoConfiguration
@@ -57,9 +61,11 @@ public class QdrantVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public QdrantVectorStore vectorStore(EmbeddingModel embeddingModel, QdrantVectorStoreProperties properties,
-			QdrantClient qdrantClient) {
+			QdrantClient qdrantClient, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 		return new QdrantVectorStore(qdrantClient, properties.getCollectionName(), embeddingModel,
-				properties.isInitializeSchema());
+				properties.isInitializeSchema(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 	static class PropertiesQdrantConnectionDetails implements QdrantConnectionDetails {

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/redis/RedisVectorStoreAutoConfiguration.java

@@ -18,6 +18,8 @@ package org.springframework.ai.autoconfigure.vectorstore.redis;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.RedisVectorStore;
 import org.springframework.ai.vectorstore.RedisVectorStore.RedisVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnBean;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
@@ -26,6 +28,8 @@ import org.springframework.boot.autoconfigure.data.redis.RedisAutoConfiguration;
 import org.springframework.boot.context.properties.EnableConfigurationProperties;
 import org.springframework.context.annotation.Bean;
 import org.springframework.data.redis.connection.jedis.JedisConnectionFactory;
+
+import io.micrometer.observation.ObservationRegistry;
 import redis.clients.jedis.JedisPooled;
 
 /**
@@ -41,7 +45,8 @@ public class RedisVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public RedisVectorStore vectorStore(EmbeddingModel embeddingModel, RedisVectorStoreProperties properties,
-			JedisConnectionFactory jedisConnectionFactory) {
+			JedisConnectionFactory jedisConnectionFactory, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 
 		var config = RedisVectorStoreConfig.builder()
 			.withIndexName(properties.getIndex())
@@ -50,7 +55,8 @@ public class RedisVectorStoreAutoConfiguration {
 
 		return new RedisVectorStore(config, embeddingModel,
 				new JedisPooled(jedisConnectionFactory.getHostName(), jedisConnectionFactory.getPort()),
-				properties.isInitializeSchema());
+				properties.isInitializeSchema(), observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 }

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/typesense/TypesenseVectorStoreAutoConfiguration.java

@@ -18,6 +18,8 @@ package org.springframework.ai.autoconfigure.vectorstore.typesense;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.TypesenseVectorStore;
 import org.springframework.ai.vectorstore.TypesenseVectorStore.TypesenseVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -27,6 +29,8 @@ import org.typesense.api.Client;
 import org.typesense.api.Configuration;
 import org.typesense.resources.Node;
 
+import io.micrometer.observation.ObservationRegistry;
+
 import java.time.Duration;
 import java.util.ArrayList;
 import java.util.List;
@@ -50,14 +54,17 @@ public class TypesenseVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public TypesenseVectorStore vectorStore(Client typesenseClient, EmbeddingModel embeddingModel,
-			TypesenseVectorStoreProperties properties) {
+			TypesenseVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 
 		TypesenseVectorStoreConfig config = TypesenseVectorStoreConfig.builder()
 			.withCollectionName(properties.getCollectionName())
 			.withEmbeddingDimension(properties.getEmbeddingDimension())
 			.build();
 
-		return new TypesenseVectorStore(typesenseClient, embeddingModel, config, properties.isInitializeSchema());
+		return new TypesenseVectorStore(typesenseClient, embeddingModel, config, properties.isInitializeSchema(),
+				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 	@Bean

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/weaviate/WeaviateVectorStoreAutoConfiguration.java

@@ -15,6 +15,7 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.weaviate;
 
+import io.micrometer.observation.ObservationRegistry;
 import io.weaviate.client.Config;
 import io.weaviate.client.WeaviateAuthClient;
 import io.weaviate.client.WeaviateClient;
@@ -23,6 +24,8 @@ import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.vectorstore.WeaviateVectorStore;
 import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig;
 import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig.MetadataField;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.ObjectProvider;
 import org.springframework.boot.autoconfigure.AutoConfiguration;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnClass;
 import org.springframework.boot.autoconfigure.condition.ConditionalOnMissingBean;
@@ -62,7 +65,8 @@ public class WeaviateVectorStoreAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public WeaviateVectorStore vectorStore(EmbeddingModel embeddingModel, WeaviateClient weaviateClient,
-			WeaviateVectorStoreProperties properties) {
+			WeaviateVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
+			ObjectProvider<VectorStoreObservationConvention> customObservationConvention) {
 
 		WeaviateVectorStoreConfig.Builder configBuilder = WeaviateVectorStore.WeaviateVectorStoreConfig.builder()
 			.withObjectClass(properties.getObjectClass())
@@ -73,7 +77,9 @@ public class WeaviateVectorStoreAutoConfiguration {
 				.toList())
 			.withConsistencyLevel(properties.getConsistencyLevel());
 
-		return new WeaviateVectorStore(configBuilder.build(), embeddingModel, weaviateClient);
+		return new WeaviateVectorStore(configBuilder.build(), embeddingModel, weaviateClient,
+				observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP),
+				customObservationConvention.getIfAvailable(() -> null));
 	}
 
 	static class PropertiesWeaviateConnectionDetails implements WeaviateConnectionDetails {

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/azure/AzureVectorStoreAutoConfigurationIT.java

@@ -15,6 +15,10 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.azure;
 
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.hamcrest.Matchers.hasSize;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
+
 import java.io.IOException;
 import java.nio.charset.StandardCharsets;
 import java.time.Duration;
@@ -26,21 +30,21 @@ import org.awaitility.Awaitility;
 import org.junit.jupiter.api.BeforeAll;
 import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
-
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
-import org.springframework.ai.vectorstore.azure.AzureVectorStore;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.azure.AzureVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
 import org.springframework.core.io.DefaultResourceLoader;
 
-import static org.assertj.core.api.Assertions.assertThat;
-import static org.hamcrest.Matchers.hasSize;
+import io.micrometer.observation.tck.TestObservationRegistry;
 
 /**
  * @author Christian Tzolov
@@ -97,6 +101,7 @@ public class AzureVectorStoreAutoConfigurationIT {
 				assertThat(properties.getIndexName()).isEqualTo("my_test_index");
 
 				VectorStore vectorStore = context.getBean(VectorStore.class);
+				TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
 
 				assertThat(vectorStore).isInstanceOf(AzureVectorStore.class);
 
@@ -106,6 +111,10 @@ public class AzureVectorStoreAutoConfigurationIT {
 					return vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 				}, hasSize(1));
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.AZURE,
+						VectorStoreObservationContext.Operation.ADD);
+				observationRegistry.clear();
+
 				List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 
 				assertThat(results).hasSize(1);
@@ -116,18 +125,32 @@ public class AzureVectorStoreAutoConfigurationIT {
 				assertThat(resultDoc.getMetadata()).hasSize(2);
 				assertThat(resultDoc.getMetadata()).containsKeys("spring", "distance");
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.AZURE,
+						VectorStoreObservationContext.Operation.QUERY);
+				observationRegistry.clear();
+
 				// Remove all documents from the store
 				vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
 
 				Awaitility.await().until(() -> {
 					return vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 				}, hasSize(0));
+
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.AZURE,
+						VectorStoreObservationContext.Operation.DELETE);
+				observationRegistry.clear();
+
 			});
 	}
 
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/cassandra/CassandraVectorStoreAutoConfigurationIT.java

@@ -15,31 +15,36 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.cassandra;
 
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
+
 import java.util.List;
 import java.util.Map;
 
 import org.junit.jupiter.api.Test;
-import org.testcontainers.junit.jupiter.Container;
-import org.testcontainers.junit.jupiter.Testcontainers;
-import org.testcontainers.containers.CassandraContainer;
-import org.testcontainers.utility.DockerImageName;
-
 import org.springframework.ai.ResourceUtils;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.autoconfigure.cassandra.CassandraAutoConfiguration;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
+import org.testcontainers.containers.CassandraContainer;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+import org.testcontainers.utility.DockerImageName;
 
-import static org.assertj.core.api.Assertions.assertThat;
+import io.micrometer.observation.tck.TestObservationRegistry;
 
 /**
  * @author Mick Semb Wever
+ * @author Christian Tzolov
  * @since 1.0.0
  */
 @Testcontainers
@@ -72,8 +77,13 @@ class CassandraVectorStoreAutoConfigurationIT {
 
 			.run(context -> {
 				VectorStore vectorStore = context.getBean(VectorStore.class);
+				TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
 				vectorStore.add(documents);
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.CASSANDRA,
+						VectorStoreObservationContext.Operation.ADD);
+				observationRegistry.clear();
+
 				List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 
 				assertThat(results).hasSize(1);
@@ -82,17 +92,30 @@ class CassandraVectorStoreAutoConfigurationIT {
 				assertThat(resultDoc.getContent()).contains(
 						"Spring AI provides abstractions that serve as the foundation for developing AI applications.");
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.CASSANDRA,
+						VectorStoreObservationContext.Operation.QUERY);
+				observationRegistry.clear();
+
 				// Remove all documents from the store
 				vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
 
 				results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 				assertThat(results).isEmpty();
+
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.CASSANDRA,
+						VectorStoreObservationContext.Operation.DELETE);
+				observationRegistry.clear();
 			});
 	}
 
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/chroma/ChromaVectorStoreAutoConfigurationIT.java

@@ -23,17 +23,25 @@ import org.testcontainers.chromadb.ChromaDBContainer;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
 
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
 
 import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
 
 /**
  * @author Christian Tzolov
@@ -60,6 +68,7 @@ public class ChromaVectorStoreAutoConfigurationIT {
 		contextRunner.run(context -> {
 
 			VectorStore vectorStore = context.getBean(VectorStore.class);
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
 
 			var bgDocument = new Document("The World is Big and Salvation Lurks Around the Corner",
 					Map.of("country", "Bulgaria"));
@@ -68,29 +77,62 @@ public class ChromaVectorStoreAutoConfigurationIT {
 
 			vectorStore.add(List.of(bgDocument, nlDocument));
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.CHROMA,
+					VectorStoreObservationContext.Operation.ADD);
+			observationRegistry.clear();
+
 			var request = SearchRequest.query("The World").withTopK(5);
 
 			List<Document> results = vectorStore.similaritySearch(request);
 			assertThat(results).hasSize(2);
+			observationRegistry.clear();
 
 			results = vectorStore
 				.similaritySearch(request.withSimilarityThresholdAll().withFilterExpression("country == 'Bulgaria'"));
 			assertThat(results).hasSize(1);
 			assertThat(results.get(0).getId()).isEqualTo(bgDocument.getId());
+			observationRegistry.clear();
 
 			results = vectorStore.similaritySearch(
 					request.withSimilarityThresholdAll().withFilterExpression("country == 'Netherlands'"));
 			assertThat(results).hasSize(1);
 			assertThat(results.get(0).getId()).isEqualTo(nlDocument.getId());
 
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store chroma query")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY_METADATA_FILTER.asString(),
+						"Expression[type=EQ, left=Key[key=country], right=Value[value=Netherlands]]")
+				.hasBeenStarted()
+				.hasBeenStopped();
+			observationRegistry.clear();
+
 			// Remove all documents from the store
 			vectorStore.delete(List.of(bgDocument, nlDocument).stream().map(doc -> doc.getId()).toList());
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store chroma delete")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY_METADATA_FILTER.asString(), "none")
+				.hasBeenStarted()
+				.hasBeenStopped();
+			observationRegistry.clear();
+
 		});
 	}
 
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/elasticsearch/ElasticsearchVectorStoreAutoConfigurationIT.java

@@ -15,31 +15,38 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.elasticsearch;
 
-import org.awaitility.Awaitility;
-import org.junit.jupiter.api.Test;
-import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
-import org.springframework.ai.autoconfigure.openai.OpenAiAutoConfiguration;
-import org.springframework.ai.autoconfigure.retry.SpringAiRetryAutoConfiguration;
-import org.springframework.ai.document.Document;
-import org.springframework.ai.vectorstore.ElasticsearchVectorStore;
-import org.springframework.ai.vectorstore.SearchRequest;
-import org.springframework.ai.vectorstore.SimilarityFunction;
-import org.springframework.boot.autoconfigure.AutoConfigurations;
-import org.springframework.boot.autoconfigure.elasticsearch.ElasticsearchRestClientAutoConfiguration;
-import org.springframework.boot.autoconfigure.web.client.RestClientAutoConfiguration;
-import org.springframework.boot.test.context.runner.ApplicationContextRunner;
-import org.springframework.core.io.DefaultResourceLoader;
-import org.testcontainers.elasticsearch.ElasticsearchContainer;
-import org.testcontainers.junit.jupiter.Container;
-import org.testcontainers.junit.jupiter.Testcontainers;
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.hamcrest.Matchers.hasSize;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
 
 import java.io.IOException;
 import java.nio.charset.StandardCharsets;
 import java.util.List;
 import java.util.Map;
 
-import static org.assertj.core.api.Assertions.assertThat;
-import static org.hamcrest.Matchers.hasSize;
+import org.awaitility.Awaitility;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.springframework.ai.autoconfigure.openai.OpenAiAutoConfiguration;
+import org.springframework.ai.autoconfigure.retry.SpringAiRetryAutoConfiguration;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.vectorstore.ElasticsearchVectorStore;
+import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.SimilarityFunction;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.boot.autoconfigure.AutoConfigurations;
+import org.springframework.boot.autoconfigure.elasticsearch.ElasticsearchRestClientAutoConfiguration;
+import org.springframework.boot.autoconfigure.web.client.RestClientAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.testcontainers.elasticsearch.ElasticsearchContainer;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+
+import io.micrometer.observation.tck.TestObservationRegistry;
 
 @Testcontainers
 @EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
@@ -59,6 +66,7 @@ class ElasticsearchVectorStoreAutoConfigurationIT {
 		.withConfiguration(AutoConfigurations.of(ElasticsearchRestClientAutoConfiguration.class,
 				ElasticsearchVectorStoreAutoConfiguration.class, RestClientAutoConfiguration.class,
 				SpringAiRetryAutoConfiguration.class, OpenAiAutoConfiguration.class))
+		.withUserConfiguration(Config.class)
 		.withPropertyValues("spring.elasticsearch.uris=" + elasticsearchContainer.getHttpHostAddress(),
 				"spring.ai.vectorstore.elasticsearch.initializeSchema=true",
 				"spring.ai.openai.api-key=" + System.getenv("OPENAI_API_KEY"));
@@ -70,14 +78,21 @@ class ElasticsearchVectorStoreAutoConfigurationIT {
 
 		this.contextRunner.run(context -> {
 			ElasticsearchVectorStore vectorStore = context.getBean(ElasticsearchVectorStore.class);
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
 
 			vectorStore.add(documents);
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.ELASTICSEARCH,
+					VectorStoreObservationContext.Operation.ADD);
+			observationRegistry.clear();
+
 			Awaitility.await()
 				.until(() -> vectorStore
 					.similaritySearch(SearchRequest.query("Great Depression").withTopK(1).withSimilarityThreshold(0)),
 						hasSize(1));
 
+			observationRegistry.clear();
+
 			List<Document> results = vectorStore
 				.similaritySearch(SearchRequest.query("Great Depression").withTopK(1).withSimilarityThreshold(0));
 
@@ -89,9 +104,17 @@ class ElasticsearchVectorStoreAutoConfigurationIT {
 			assertThat(resultDoc.getMetadata()).containsKey("meta2");
 			assertThat(resultDoc.getMetadata()).containsKey("distance");
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.ELASTICSEARCH,
+					VectorStoreObservationContext.Operation.QUERY);
+			observationRegistry.clear();
+
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(Document::getId).toList());
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.ELASTICSEARCH,
+					VectorStoreObservationContext.Operation.DELETE);
+			observationRegistry.clear();
+
 			Awaitility.await()
 				.until(() -> vectorStore
 					.similaritySearch(SearchRequest.query("Great Depression").withTopK(1).withSimilarityThreshold(0)),
@@ -135,4 +158,14 @@ class ElasticsearchVectorStoreAutoConfigurationIT {
 		}
 	}
 
+	@Configuration(proxyBeanMethods = false)
+	static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+	}
+
 }

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/gemfire/GemFireVectorStoreAutoConfigurationIT.java

@@ -18,17 +18,12 @@ package org.springframework.ai.autoconfigure.vectorstore.gemfire;
 
 import static org.assertj.core.api.Assertions.assertThat;
 import static org.hamcrest.Matchers.hasSize;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
 
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
 
-import com.fasterxml.jackson.databind.JsonNode;
-import com.fasterxml.jackson.databind.ObjectMapper;
-import com.github.dockerjava.api.model.ExposedPort;
-import com.github.dockerjava.api.model.PortBinding;
-import com.github.dockerjava.api.model.Ports;
-import com.vmware.gemfire.testcontainers.GemFireCluster;
 import org.awaitility.Awaitility;
 import org.junit.jupiter.api.AfterAll;
 import org.junit.jupiter.api.Assertions;
@@ -37,19 +32,30 @@ import org.junit.jupiter.api.Test;
 import org.springframework.ai.ResourceUtils;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.GemFireVectorStore;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
 
+import com.fasterxml.jackson.databind.JsonNode;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import com.github.dockerjava.api.model.ExposedPort;
+import com.github.dockerjava.api.model.PortBinding;
+import com.github.dockerjava.api.model.Ports;
+import com.vmware.gemfire.testcontainers.GemFireCluster;
+
+import io.micrometer.observation.tck.TestObservationRegistry;
+
 /**
  * @author Geet Rawat
+ * @author Christian Tzolov
  */
-
 class GemFireVectorStoreAutoConfigurationIT {
 
 	private static GemFireCluster gemFireCluster;
@@ -116,6 +122,7 @@ class GemFireVectorStoreAutoConfigurationIT {
 	void ensureGemFireVectorStoreCustomConfiguration() {
 		this.contextRunner.run(context -> {
 			GemFireVectorStore store = context.getBean(GemFireVectorStore.class);
+
 			Assertions.assertNotNull(store);
 			assertThat(store.getIndexName()).isEqualTo(INDEX_NAME);
 			assertThat(store.getBeamWidth()).isEqualTo(BEAM_WIDTH);
@@ -138,14 +145,24 @@ class GemFireVectorStoreAutoConfigurationIT {
 	public void addAndSearchTest() {
 		contextRunner.run(context -> {
 			VectorStore vectorStore = context.getBean(VectorStore.class);
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
 			vectorStore.add(documents);
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.GEMFIRE,
+					VectorStoreObservationContext.Operation.ADD);
+
 			Awaitility.await().until(() -> {
 				return vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 			}, hasSize(1));
+			observationRegistry.clear();
 
 			List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.GEMFIRE,
+					VectorStoreObservationContext.Operation.QUERY);
+			observationRegistry.clear();
+
 			assertThat(results).hasSize(1);
 			Document resultDoc = results.get(0);
 			assertThat(resultDoc.getId()).isEqualTo(documents.get(0).getId());
@@ -157,9 +174,13 @@ class GemFireVectorStoreAutoConfigurationIT {
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.GEMFIRE,
+					VectorStoreObservationContext.Operation.DELETE);
+
 			Awaitility.await().until(() -> {
 				return vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 			}, hasSize(0));
+			observationRegistry.clear();
 		});
 	}
 
@@ -191,6 +212,11 @@ class GemFireVectorStoreAutoConfigurationIT {
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/milvus/MilvusVectorStoreAutoConfigurationIT.java

@@ -15,26 +15,30 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.milvus;
 
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
+
 import java.util.List;
 import java.util.Map;
 
 import org.junit.jupiter.api.Test;
-import org.testcontainers.junit.jupiter.Container;
-import org.testcontainers.junit.jupiter.Testcontainers;
-
 import org.springframework.ai.ResourceUtils;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
 import org.testcontainers.milvus.MilvusContainer;
 
-import static org.assertj.core.api.Assertions.assertThat;
+import io.micrometer.observation.tck.TestObservationRegistry;
 
 /**
  * @author Christian Tzolov
@@ -68,8 +72,14 @@ public class MilvusVectorStoreAutoConfigurationIT {
 					"spring.ai.vectorstore.milvus.client.port=" + milvus.getMappedPort(19530))
 			.run(context -> {
 				VectorStore vectorStore = context.getBean(VectorStore.class);
+				TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
 				vectorStore.add(documents);
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.MILVUS,
+						VectorStoreObservationContext.Operation.ADD);
+				observationRegistry.clear();
+
 				List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 
 				assertThat(results).hasSize(1);
@@ -80,17 +90,31 @@ public class MilvusVectorStoreAutoConfigurationIT {
 				assertThat(resultDoc.getMetadata()).hasSize(2);
 				assertThat(resultDoc.getMetadata()).containsKeys("spring", "distance");
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.MILVUS,
+						VectorStoreObservationContext.Operation.QUERY);
+				observationRegistry.clear();
+
 				// Remove all documents from the store
 				vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
 
 				results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 				assertThat(results).hasSize(0);
+
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.MILVUS,
+						VectorStoreObservationContext.Operation.DELETE);
+				observationRegistry.clear();
+
 			});
 	}
 
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/mongo/MongoDBAtlasVectorStoreAutoConfigurationIT.java

@@ -15,33 +15,43 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.mongo;
 
-import org.junit.jupiter.api.Test;
-import org.springframework.ai.autoconfigure.openai.OpenAiAutoConfiguration;
-import org.springframework.ai.autoconfigure.retry.SpringAiRetryAutoConfiguration;
-import org.springframework.ai.document.Document;
-import org.springframework.ai.vectorstore.SearchRequest;
-import org.springframework.ai.vectorstore.VectorStore;
-import org.springframework.boot.autoconfigure.AutoConfigurations;
-import org.springframework.boot.autoconfigure.data.mongo.MongoDataAutoConfiguration;
-import org.springframework.boot.autoconfigure.mongo.MongoAutoConfiguration;
-import org.springframework.boot.autoconfigure.web.client.RestClientAutoConfiguration;
-import org.springframework.boot.test.context.runner.ApplicationContextRunner;
-import org.testcontainers.containers.GenericContainer;
-import org.testcontainers.containers.wait.strategy.Wait;
-import org.testcontainers.junit.jupiter.Container;
-import org.testcontainers.junit.jupiter.Testcontainers;
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
 
 import java.time.Duration;
 import java.util.Collections;
 import java.util.List;
 import java.util.stream.Collectors;
 
-import static org.assertj.core.api.Assertions.assertThat;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.springframework.ai.autoconfigure.openai.OpenAiAutoConfiguration;
+import org.springframework.ai.autoconfigure.retry.SpringAiRetryAutoConfiguration;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.boot.autoconfigure.AutoConfigurations;
+import org.springframework.boot.autoconfigure.data.mongo.MongoDataAutoConfiguration;
+import org.springframework.boot.autoconfigure.mongo.MongoAutoConfiguration;
+import org.springframework.boot.autoconfigure.web.client.RestClientAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.testcontainers.containers.GenericContainer;
+import org.testcontainers.containers.wait.strategy.Wait;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+
+import io.micrometer.observation.tck.TestObservationRegistry;
 
 /**
  * @author Eddú Meléndez
+ * @author Christian Tzolov
  */
 @Testcontainers
+@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
 class MongoDBAtlasVectorStoreAutoConfigurationIT {
 
 	@Container
@@ -61,6 +71,7 @@ class MongoDBAtlasVectorStoreAutoConfigurationIT {
 					Collections.singletonMap("meta2", "meta2")));
 
 	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class)
 		.withConfiguration(AutoConfigurations.of(MongoAutoConfiguration.class, MongoDataAutoConfiguration.class,
 				MongoDBAtlasVectorStoreAutoConfiguration.class, RestClientAutoConfiguration.class,
 				SpringAiRetryAutoConfiguration.class, OpenAiAutoConfiguration.class))
@@ -79,8 +90,13 @@ class MongoDBAtlasVectorStoreAutoConfigurationIT {
 		contextRunner.run(context -> {
 
 			VectorStore vectorStore = context.getBean(VectorStore.class);
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
 
 			vectorStore.add(documents);
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.MONGODB,
+					VectorStoreObservationContext.Operation.ADD);
+			observationRegistry.clear();
+
 			Thread.sleep(5000); // Await a second for the document to be indexed
 
 			List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Great").withTopK(1));
@@ -92,12 +108,30 @@ class MongoDBAtlasVectorStoreAutoConfigurationIT {
 					"Great Depression Great Depression Great Depression Great Depression Great Depression Great Depression");
 			assertThat(resultDoc.getMetadata()).containsEntry("meta2", "meta2");
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.MONGODB,
+					VectorStoreObservationContext.Operation.QUERY);
+			observationRegistry.clear();
+
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(Document::getId).collect(Collectors.toList()));
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.MONGODB,
+					VectorStoreObservationContext.Operation.DELETE);
+			observationRegistry.clear();
+
 			List<Document> results2 = vectorStore.similaritySearch(SearchRequest.query("Great").withTopK(1));
 			assertThat(results2).isEmpty();
 		});
 	}
 
+	@Configuration(proxyBeanMethods = false)
+	static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+	}
+
 }

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/neo4j/Neo4jVectorStoreAutoConfigurationIT.java

@@ -15,32 +15,37 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.neo4j;
 
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
+
 import java.util.List;
 import java.util.Map;
 
 import org.junit.jupiter.api.Test;
+import org.springframework.ai.ResourceUtils;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.transformers.TransformersEmbeddingModel;
+import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.autoconfigure.neo4j.Neo4jAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
 import org.testcontainers.containers.Neo4jContainer;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
 import org.testcontainers.utility.DockerImageName;
 
-import org.springframework.ai.ResourceUtils;
-import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.EmbeddingModel;
-import org.springframework.ai.transformers.TransformersEmbeddingModel;
-import org.springframework.ai.vectorstore.SearchRequest;
-import org.springframework.ai.vectorstore.VectorStore;
-import org.springframework.boot.autoconfigure.AutoConfigurations;
-import org.springframework.boot.test.context.runner.ApplicationContextRunner;
-import org.springframework.context.annotation.Bean;
-import org.springframework.context.annotation.Configuration;
-
-import static org.assertj.core.api.Assertions.assertThat;
+import io.micrometer.observation.tck.TestObservationRegistry;
 
 /**
  * @author Jingzhou Ou
  * @author Soby Chacko
+ * @author Christian Tzolov
  */
 @Testcontainers
 public class Neo4jVectorStoreAutoConfigurationIT {
@@ -48,7 +53,7 @@ public class Neo4jVectorStoreAutoConfigurationIT {
 	// Needs to be Neo4j 5.15+, because Neo4j 5.15 deprecated the used embedding storing
 	// function.
 	@Container
-	static Neo4jContainer<?> neo4jContainer = new Neo4jContainer<>(DockerImageName.parse("neo4j:5.15"))
+	static Neo4jContainer<?> neo4jContainer = new Neo4jContainer<>(DockerImageName.parse("neo4j:5.18"))
 		.withRandomPassword();
 
 	List<Document> documents = List.of(
@@ -76,8 +81,14 @@ public class Neo4jVectorStoreAutoConfigurationIT {
 				assertThat(properties.getIndexName()).isEqualTo("customIndexName");
 
 				VectorStore vectorStore = context.getBean(VectorStore.class);
+				TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
 				vectorStore.add(documents);
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.NEO4J,
+						VectorStoreObservationContext.Operation.ADD);
+				observationRegistry.clear();
+
 				List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 
 				assertThat(results).hasSize(1);
@@ -86,9 +97,17 @@ public class Neo4jVectorStoreAutoConfigurationIT {
 				assertThat(resultDoc.getContent()).contains(
 						"Spring AI provides abstractions that serve as the foundation for developing AI applications.");
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.NEO4J,
+						VectorStoreObservationContext.Operation.QUERY);
+				observationRegistry.clear();
+
 				// Remove all documents from the store
 				vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.NEO4J,
+						VectorStoreObservationContext.Operation.DELETE);
+				observationRegistry.clear();
+
 				results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 				assertThat(results).isEmpty();
 			});
@@ -97,6 +116,11 @@ public class Neo4jVectorStoreAutoConfigurationIT {
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/observation/ObservationTestUtil.java

@@ -0,0 +1,43 @@
+/*
+* Copyright 2024 - 2024 the original author or authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* https://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+package org.springframework.ai.autoconfigure.vectorstore.observation;
+
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+/**
+ * @author Christian Tzolov
+ * @since 1.0.0
+ */
+
+public class ObservationTestUtil {
+
+	public static void assertObservationRegistry(TestObservationRegistry observationRegistry, String kind,
+			VectorStoreProvider vectorStoreProvider, VectorStoreObservationContext.Operation operation) {
+		TestObservationRegistryAssert.assertThat(observationRegistry)
+			.doesNotHaveAnyRemainingCurrentObservation()
+			.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+			.that()
+			.hasContextualNameEqualTo(kind + " " + vectorStoreProvider.value() + " " + operation.value())
+			.hasBeenStarted()
+			.hasBeenStopped();
+	}
+
+}

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/opensearch/AwsOpenSearchVectorStoreAutoConfigurationIT.java

@@ -47,7 +47,7 @@ import static org.awaitility.Awaitility.await;
 import static org.hamcrest.Matchers.hasSize;
 
 @Testcontainers
-class a {
+class AwsOpenSearchVectorStoreAutoConfigurationIT {
 
 	@Container
 	private static final LocalStackContainer localstack = new LocalStackContainer(

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/opensearch/OpenSearchVectorStoreAutoConfigurationIT.java

@@ -15,15 +15,26 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.opensearch;
 
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.hamcrest.Matchers.hasSize;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+
 import org.awaitility.Awaitility;
 import org.junit.jupiter.api.Test;
 import org.opensearch.testcontainers.OpensearchContainer;
 import org.springframework.ai.autoconfigure.retry.SpringAiRetryAutoConfiguration;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.OpenSearchVectorStore;
 import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.test.context.FilteredClassLoader;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
@@ -33,17 +44,11 @@ import org.springframework.core.io.DefaultResourceLoader;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
 import org.testcontainers.utility.DockerImageName;
+
+import io.micrometer.observation.tck.TestObservationRegistry;
 import software.amazon.awssdk.http.apache.ApacheHttpClient;
 import software.amazon.awssdk.regions.Region;
 
-import java.io.IOException;
-import java.nio.charset.StandardCharsets;
-import java.util.List;
-import java.util.Map;
-
-import static org.assertj.core.api.Assertions.assertThat;
-import static org.hamcrest.Matchers.hasSize;
-
 @Testcontainers
 class OpenSearchVectorStoreAutoConfigurationIT {
 
@@ -82,17 +87,28 @@ class OpenSearchVectorStoreAutoConfigurationIT {
 
 		this.contextRunner.run(context -> {
 			OpenSearchVectorStore vectorStore = context.getBean(OpenSearchVectorStore.class);
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
 
 			vectorStore.add(documents);
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.OPENSEARCH,
+					VectorStoreObservationContext.Operation.ADD);
+
 			Awaitility.await()
 				.until(() -> vectorStore
 					.similaritySearch(SearchRequest.query("Great Depression").withTopK(1).withSimilarityThreshold(0)),
 						hasSize(1));
 
+			observationRegistry.clear();
+
 			List<Document> results = vectorStore
 				.similaritySearch(SearchRequest.query("Great Depression").withTopK(1).withSimilarityThreshold(0));
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.OPENSEARCH,
+					VectorStoreObservationContext.Operation.QUERY);
+
+			observationRegistry.clear();
+
 			assertThat(results).hasSize(1);
 			Document resultDoc = results.get(0);
 			assertThat(resultDoc.getId()).isEqualTo(documents.get(2).getId());
@@ -104,6 +120,10 @@ class OpenSearchVectorStoreAutoConfigurationIT {
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(Document::getId).toList());
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.OPENSEARCH,
+					VectorStoreObservationContext.Operation.DELETE);
+			observationRegistry.clear();
+
 			Awaitility.await()
 				.until(() -> vectorStore
 					.similaritySearch(SearchRequest.query("Great Depression").withTopK(1).withSimilarityThreshold(0)),
@@ -124,6 +144,11 @@ class OpenSearchVectorStoreAutoConfigurationIT {
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/oracle/OracleVectorStoreAutoConfigurationIT.java

@@ -15,31 +15,35 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.oracle;
 
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
+
 import java.io.IOException;
 import java.nio.charset.StandardCharsets;
 import java.util.List;
 import java.util.Map;
 
 import org.junit.jupiter.api.Test;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.transformers.TransformersEmbeddingModel;
+import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.boot.autoconfigure.AutoConfigurations;
+import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
 import org.springframework.boot.autoconfigure.jdbc.JdbcTemplateAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.core.io.DefaultResourceLoader;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
 import org.testcontainers.oracle.OracleContainer;
 import org.testcontainers.utility.MountableFile;
 
-import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.EmbeddingModel;
-import org.springframework.ai.transformers.TransformersEmbeddingModel;
-import org.springframework.ai.vectorstore.SearchRequest;
-import org.springframework.ai.vectorstore.VectorStore;
-import org.springframework.boot.autoconfigure.AutoConfigurations;
-import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
-import org.springframework.boot.test.context.runner.ApplicationContextRunner;
-import org.springframework.context.annotation.Bean;
-import org.springframework.context.annotation.Configuration;
-import org.springframework.core.io.DefaultResourceLoader;
-
-import static org.assertj.core.api.Assertions.assertThat;
+import io.micrometer.observation.tck.TestObservationRegistry;
 
 /**
  * @author Christian Tzolov
@@ -76,9 +80,14 @@ public class OracleVectorStoreAutoConfigurationIT {
 		contextRunner.run(context -> {
 
 			VectorStore vectorStore = context.getBean(VectorStore.class);
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
 
 			vectorStore.add(documents);
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.ORACLE,
+					VectorStoreObservationContext.Operation.ADD);
+			observationRegistry.clear();
+
 			List<Document> results = vectorStore
 				.similaritySearch(SearchRequest.query("What is Great Depression?").withTopK(1));
 
@@ -87,8 +96,17 @@ public class OracleVectorStoreAutoConfigurationIT {
 			assertThat(resultDoc.getId()).isEqualTo(documents.get(2).getId());
 			assertThat(resultDoc.getMetadata()).containsKeys("depression", "distance");
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.ORACLE,
+					VectorStoreObservationContext.Operation.QUERY);
+			observationRegistry.clear();
+
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
+
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.ORACLE,
+					VectorStoreObservationContext.Operation.DELETE);
+			observationRegistry.clear();
+
 			results = vectorStore.similaritySearch(SearchRequest.query("Great Depression").withTopK(1));
 			assertThat(results).hasSize(0);
 		});
@@ -107,6 +125,11 @@ public class OracleVectorStoreAutoConfigurationIT {
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/pgvector/PgVectorStoreAutoConfigurationIT.java

@@ -16,6 +16,7 @@
 package org.springframework.ai.autoconfigure.vectorstore.pgvector;
 
 import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
 
 import java.io.IOException;
 import java.nio.charset.StandardCharsets;
@@ -27,9 +28,11 @@ import org.junit.jupiter.params.ParameterizedTest;
 import org.junit.jupiter.params.provider.ValueSource;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.PgVectorStore;
 import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
 import org.springframework.boot.autoconfigure.jdbc.JdbcTemplateAutoConfiguration;
@@ -43,6 +46,8 @@ import org.testcontainers.containers.PostgreSQLContainer;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
 
+import io.micrometer.observation.tck.TestObservationRegistry;
+
 /**
  * @author Christian Tzolov
  * @author Muthukumaran Navaneethakrishnan
@@ -88,6 +93,7 @@ public class PgVectorStoreAutoConfigurationIT {
 		contextRunner.run(context -> {
 
 			PgVectorStore vectorStore = context.getBean(PgVectorStore.class);
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
 
 			assertThat(isFullyQualifiedTableExists(context, PgVectorStore.DEFAULT_SCHEMA_NAME,
 					PgVectorStore.DEFAULT_TABLE_NAME))
@@ -95,6 +101,10 @@ public class PgVectorStoreAutoConfigurationIT {
 
 			vectorStore.add(documents);
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.PG_VECTOR,
+					VectorStoreObservationContext.Operation.ADD);
+			observationRegistry.clear();
+
 			List<Document> results = vectorStore
 				.similaritySearch(SearchRequest.query("What is Great Depression?").withTopK(1));
 
@@ -103,10 +113,19 @@ public class PgVectorStoreAutoConfigurationIT {
 			assertThat(resultDoc.getId()).isEqualTo(documents.get(2).getId());
 			assertThat(resultDoc.getMetadata()).containsKeys("depression", "distance");
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.PG_VECTOR,
+					VectorStoreObservationContext.Operation.QUERY);
+			observationRegistry.clear();
+
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
+
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.PG_VECTOR,
+					VectorStoreObservationContext.Operation.DELETE);
+
 			results = vectorStore.similaritySearch(SearchRequest.query("Great Depression").withTopK(1));
 			assertThat(results).hasSize(0);
+			observationRegistry.clear();
 		});
 	}
 
@@ -142,6 +161,11 @@ public class PgVectorStoreAutoConfigurationIT {
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/pinecone/PineconeVectorStoreAutoConfigurationIT.java

@@ -17,6 +17,7 @@ package org.springframework.ai.autoconfigure.vectorstore.pinecone;
 
 import static org.assertj.core.api.Assertions.assertThat;
 import static org.hamcrest.Matchers.hasSize;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
 
 import java.io.IOException;
 import java.nio.charset.StandardCharsets;
@@ -31,15 +32,19 @@ import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.PineconeVectorStore;
 import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
 import org.springframework.core.io.DefaultResourceLoader;
 
+import io.micrometer.observation.tck.TestObservationRegistry;
+
 /**
  * @author Christian Tzolov
  * @author Soby Chacko
@@ -85,12 +90,17 @@ public class PineconeVectorStoreAutoConfigurationIT {
 		contextRunner.run(context -> {
 
 			PineconeVectorStore vectorStore = context.getBean(PineconeVectorStore.class);
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
 
 			vectorStore.add(documents);
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.PINECONE,
+					VectorStoreObservationContext.Operation.ADD);
+
 			Awaitility.await().until(() -> {
 				return vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 			}, hasSize(1));
+			observationRegistry.clear();
 
 			List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 
@@ -102,9 +112,17 @@ public class PineconeVectorStoreAutoConfigurationIT {
 			assertThat(resultDoc.getMetadata()).hasSize(2);
 			assertThat(resultDoc.getMetadata()).containsKeys("spring", "customDistanceField");
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.PINECONE,
+					VectorStoreObservationContext.Operation.QUERY);
+			observationRegistry.clear();
+
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.PINECONE,
+					VectorStoreObservationContext.Operation.DELETE);
+			observationRegistry.clear();
+
 			Awaitility.await().until(() -> {
 				return vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 			}, hasSize(0));
@@ -114,6 +132,11 @@ public class PineconeVectorStoreAutoConfigurationIT {
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/qdrant/QdrantVectorStoreAutoConfigurationIT.java

@@ -15,28 +15,32 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.qdrant;
 
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
+
 import java.io.IOException;
 import java.nio.charset.StandardCharsets;
 import java.util.List;
 import java.util.Map;
 
 import org.junit.jupiter.api.Test;
-import org.testcontainers.junit.jupiter.Container;
-import org.testcontainers.junit.jupiter.Testcontainers;
-import org.testcontainers.qdrant.QdrantContainer;
-
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
 import org.springframework.core.io.DefaultResourceLoader;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+import org.testcontainers.qdrant.QdrantContainer;
 
-import static org.assertj.core.api.Assertions.assertThat;
+import io.micrometer.observation.tck.TestObservationRegistry;
 
 /**
  * @author Christian Tzolov
@@ -67,9 +71,14 @@ public class QdrantVectorStoreAutoConfigurationIT {
 		contextRunner.run(context -> {
 
 			VectorStore vectorStore = context.getBean(VectorStore.class);
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
 
 			vectorStore.add(documents);
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.QDRANT,
+					VectorStoreObservationContext.Operation.ADD);
+			observationRegistry.clear();
+
 			List<Document> results = vectorStore
 				.similaritySearch(SearchRequest.query("What is Great Depression?").withTopK(1));
 
@@ -78,10 +87,18 @@ public class QdrantVectorStoreAutoConfigurationIT {
 			assertThat(resultDoc.getId()).isEqualTo(documents.get(2).getId());
 			assertThat(resultDoc.getMetadata()).containsKeys("depression", "distance");
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.QDRANT,
+					VectorStoreObservationContext.Operation.QUERY);
+			observationRegistry.clear();
+
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
 			results = vectorStore.similaritySearch(SearchRequest.query("Great Depression").withTopK(1));
 			assertThat(results).hasSize(0);
+
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.QDRANT,
+					VectorStoreObservationContext.Operation.DELETE);
+			observationRegistry.clear();
 		});
 	}
 
@@ -98,6 +115,11 @@ public class QdrantVectorStoreAutoConfigurationIT {
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/redis/RedisVectorStoreAutoConfigurationIT.java

@@ -16,6 +16,7 @@
 package org.springframework.ai.autoconfigure.vectorstore.redis;
 
 import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
 
 import java.util.List;
 import java.util.Map;
@@ -24,9 +25,11 @@ import org.junit.jupiter.api.Test;
 import org.springframework.ai.ResourceUtils;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.autoconfigure.data.redis.RedisAutoConfiguration;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
@@ -37,10 +40,13 @@ import org.testcontainers.junit.jupiter.Testcontainers;
 
 import com.redis.testcontainers.RedisStackContainer;
 
+import io.micrometer.observation.tck.TestObservationRegistry;
+
 /**
  * @author Julien Ruaux
  * @author Eddú Meléndez
  * @author Soby Chacko
+ * @author Christian Tzolov
  */
 @Testcontainers
 class RedisVectorStoreAutoConfigurationIT {
@@ -66,8 +72,14 @@ class RedisVectorStoreAutoConfigurationIT {
 	void addAndSearch() {
 		contextRunner.run(context -> {
 			VectorStore vectorStore = context.getBean(VectorStore.class);
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
 			vectorStore.add(documents);
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.REDIS,
+					VectorStoreObservationContext.Operation.ADD);
+			observationRegistry.clear();
+
 			List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 
 			assertThat(results).hasSize(1);
@@ -76,9 +88,17 @@ class RedisVectorStoreAutoConfigurationIT {
 			assertThat(resultDoc.getContent()).contains(
 					"Spring AI provides abstractions that serve as the foundation for developing AI applications.");
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.REDIS,
+					VectorStoreObservationContext.Operation.QUERY);
+			observationRegistry.clear();
+
 			// Remove all documents from the store
 			vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.REDIS,
+					VectorStoreObservationContext.Operation.DELETE);
+			observationRegistry.clear();
+
 			results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 			assertThat(results).isEmpty();
 		});
@@ -87,6 +107,11 @@ class RedisVectorStoreAutoConfigurationIT {
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/typesense/TypesenseVectorStoreAutoConfigurationIT.java

@@ -15,13 +15,22 @@
  */
 package org.springframework.ai.autoconfigure.vectorstore.typesense;
 
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
+
+import java.time.Duration;
+import java.util.List;
+import java.util.Map;
+
 import org.junit.jupiter.api.Test;
 import org.springframework.ai.ResourceUtils;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
 import org.springframework.context.annotation.Bean;
@@ -30,16 +39,13 @@ import org.testcontainers.containers.GenericContainer;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
 
-import java.time.Duration;
-import java.util.List;
-import java.util.Map;
-
-import static org.assertj.core.api.Assertions.assertThat;
+import io.micrometer.observation.tck.TestObservationRegistry;
 
 /**
  * @author Pablo Sanchidrian Herrera
  * @author Eddú Meléndez
  * @author Soby Chacko
+ * @author Christian Tzolov
  */
 @Testcontainers
 public class TypesenseVectorStoreAutoConfigurationIT {
@@ -71,8 +77,14 @@ public class TypesenseVectorStoreAutoConfigurationIT {
 					"spring.ai.vectorstore.typesense.client.port=" + typesenseContainer.getMappedPort(8108).toString())
 			.run(context -> {
 				VectorStore vectorStore = context.getBean(VectorStore.class);
+				TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
 				vectorStore.add(documents);
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.TYPESENSE,
+						VectorStoreObservationContext.Operation.ADD);
+				observationRegistry.clear();
+
 				List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 
 				assertThat(results).hasSize(1);
@@ -83,8 +95,16 @@ public class TypesenseVectorStoreAutoConfigurationIT {
 				assertThat(resultDoc.getMetadata()).hasSize(2);
 				assertThat(resultDoc.getMetadata()).containsKeys("spring", "distance");
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.TYPESENSE,
+						VectorStoreObservationContext.Operation.QUERY);
+				observationRegistry.clear();
+
 				vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
 
+				assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.TYPESENSE,
+						VectorStoreObservationContext.Operation.DELETE);
+				observationRegistry.clear();
+
 				results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
 				assertThat(results).hasSize(0);
 			});
@@ -93,6 +113,11 @@ public class TypesenseVectorStoreAutoConfigurationIT {
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/weaviate/WeaviateVectorStoreAutoConfigurationIT.java

@@ -24,17 +24,22 @@ import org.testcontainers.junit.jupiter.Testcontainers;
 
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.transformers.TransformersEmbeddingModel;
 import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.VectorStore;
 import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig.MetadataField;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
 import org.springframework.boot.autoconfigure.AutoConfigurations;
 import org.springframework.boot.test.context.runner.ApplicationContextRunner;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
 import org.testcontainers.weaviate.WeaviateContainer;
 
+import io.micrometer.observation.tck.TestObservationRegistry;
+
 import static org.assertj.core.api.Assertions.assertThat;
+import static org.springframework.ai.autoconfigure.vectorstore.observation.ObservationTestUtil.assertObservationRegistry;
 
 /**
  * @author Christian Tzolov
@@ -73,6 +78,8 @@ public class WeaviateVectorStoreAutoConfigurationIT {
 
 			VectorStore vectorStore = context.getBean(VectorStore.class);
 
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
 			var bgDocument = new Document("The World is Big and Salvation Lurks Around the Corner",
 					Map.of("country", "Bulgaria", "price", 3.14, "active", true, "year", 2020));
 			var nlDocument = new Document("The World is Big and Salvation Lurks Around the Corner",
@@ -80,6 +87,10 @@ public class WeaviateVectorStoreAutoConfigurationIT {
 
 			vectorStore.add(List.of(bgDocument, nlDocument));
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.WEAVIATE,
+					VectorStoreObservationContext.Operation.ADD);
+			observationRegistry.clear();
+
 			var request = SearchRequest.query("The World").withTopK(5);
 
 			List<Document> results = vectorStore.similaritySearch(request);
@@ -90,6 +101,9 @@ public class WeaviateVectorStoreAutoConfigurationIT {
 			assertThat(results).hasSize(1);
 			assertThat(results.get(0).getId()).isEqualTo(bgDocument.getId());
 
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.WEAVIATE,
+					VectorStoreObservationContext.Operation.QUERY);
+
 			results = vectorStore.similaritySearch(
 					request.withSimilarityThresholdAll().withFilterExpression("country == 'Netherlands'"));
 			assertThat(results).hasSize(1);
@@ -109,14 +123,24 @@ public class WeaviateVectorStoreAutoConfigurationIT {
 			assertThat(results).hasSize(1);
 			assertThat(results.get(0).getId()).isEqualTo(nlDocument.getId());
 
+			observationRegistry.clear();
+
 			// Remove all documents from the store
 			vectorStore.delete(List.of(bgDocument, nlDocument).stream().map(doc -> doc.getId()).toList());
+
+			assertObservationRegistry(observationRegistry, "vector_store", VectorStoreProvider.WEAVIATE,
+					VectorStoreObservationContext.Operation.DELETE);
 		});
 	}
 
 	@Configuration(proxyBeanMethods = false)
 	static class Config {
 
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
 		@Bean
 		public EmbeddingModel embeddingModel() {
 			return new TransformersEmbeddingModel();

spring-ai-spring-boot-testcontainers/src/test/java/org/springframework/ai/testcontainers/service/connection/ollama/OllamaContainerConnectionDetailsFactoryTest.java

@@ -18,6 +18,7 @@ package org.springframework.ai.testcontainers.service.connection.ollama;
 import org.apache.commons.logging.Log;
 import org.apache.commons.logging.LogFactory;
 import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
 import org.springframework.ai.autoconfigure.ollama.OllamaAutoConfiguration;
 import org.springframework.ai.embedding.EmbeddingResponse;
@@ -42,6 +43,7 @@ import static org.assertj.core.api.Assertions.assertThat;
  * @author Eddú Meléndez
  */
 @SpringJUnitConfig
+@Disabled("requires more memory than is often available on dev machines")
 @Testcontainers
 @TestPropertySource(properties = "spring.ai.ollama.embedding.options.model="
 		+ OllamaContainerConnectionDetailsFactoryTest.MODEL_NAME)

spring-ai-test/src/main/java/org/springframework/ai/evaluation/BasicEvaluationTest.java

@@ -15,23 +15,22 @@
  */
 package org.springframework.ai.evaluation;
 
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
-import org.springframework.ai.chat.model.ChatModel;
-import org.springframework.ai.chat.model.ChatResponse;
-import org.springframework.ai.chat.prompt.Prompt;
-import org.springframework.ai.chat.prompt.PromptTemplate;
-import org.springframework.ai.chat.messages.Message;
-import org.springframework.ai.chat.messages.SystemMessage;
-import org.springframework.beans.factory.annotation.Autowired;
-import org.springframework.beans.factory.annotation.Value;
-import org.springframework.core.io.Resource;
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.assertj.core.api.Assertions.fail;
 
 import java.util.List;
 import java.util.Map;
 
-import static org.assertj.core.api.Assertions.assertThat;
-import static org.assertj.core.api.Assertions.fail;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.ai.chat.messages.Message;
+import org.springframework.ai.chat.messages.SystemMessage;
+import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.ai.chat.prompt.Prompt;
+import org.springframework.ai.chat.prompt.PromptTemplate;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.core.io.Resource;
 
 public class BasicEvaluationTest {
 

vector-stores/spring-ai-azure-store/pom.xml

@@ -80,6 +80,11 @@
 			<artifactId>awaitility</artifactId>
 			<scope>test</scope>
 		</dependency>
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
 
 	</dependencies>
 

vector-stores/spring-ai-azure-store/src/main/java/org/springframework/ai/vectorstore/azure/AzureVectorStore.java

@@ -15,6 +15,31 @@
  */
 package org.springframework.ai.vectorstore.azure;
 
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+import java.util.stream.Collectors;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.model.EmbeddingUtils;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
+import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext.Builder;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.InitializingBean;
+import org.springframework.util.Assert;
+import org.springframework.util.CollectionUtils;
+import org.springframework.util.StringUtils;
+
 import com.alibaba.fastjson2.JSONObject;
 import com.alibaba.fastjson2.TypeReference;
 import com.azure.core.util.Context;
@@ -34,25 +59,8 @@ import com.azure.search.documents.models.IndexingResult;
 import com.azure.search.documents.models.SearchOptions;
 import com.azure.search.documents.models.VectorSearchOptions;
 import com.azure.search.documents.models.VectorizedQuery;
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
-import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.EmbeddingModel;
-import org.springframework.ai.model.EmbeddingUtils;
-import org.springframework.ai.vectorstore.SearchRequest;
-import org.springframework.ai.vectorstore.VectorStore;
-import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
-import org.springframework.beans.factory.InitializingBean;
-import org.springframework.util.Assert;
-import org.springframework.util.CollectionUtils;
-import org.springframework.util.StringUtils;
 
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.List;
-import java.util.Map;
-import java.util.Optional;
-import java.util.stream.Collectors;
+import io.micrometer.observation.ObservationRegistry;
 
 /**
  * Uses Azure Cognitive Search as a backing vector store. Documents can be preloaded into
@@ -65,7 +73,7 @@ import java.util.stream.Collectors;
  * @author Christian Tzolov
  * @author Josh Long
  */
-public class AzureVectorStore implements VectorStore, InitializingBean {
+public class AzureVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	private static final Logger logger = LoggerFactory.getLogger(AzureVectorStore.class);
 
@@ -166,6 +174,25 @@ public class AzureVectorStore implements VectorStore, InitializingBean {
 	 */
 	public AzureVectorStore(SearchIndexClient searchIndexClient, EmbeddingModel embeddingModel,
 			boolean initializeSchema, List<MetadataField> filterMetadataFields) {
+		this(searchIndexClient, embeddingModel, initializeSchema, filterMetadataFields, ObservationRegistry.NOOP, null);
+	}
+
+	/**
+	 * Constructs a new AzureCognitiveSearchVectorStore.
+	 * @param searchIndexClient A pre-configured Azure {@link SearchIndexClient} that CRUD
+	 * for Azure search indexes and factory for {@link SearchClient}.
+	 * @param embeddingModel The client for embedding operations.
+	 * @param filterMetadataFields List of metadata fields (as field name and type) that
+	 * can be used in similarity search query filter expressions.
+	 * @param observationRegistry The observation registry to use.
+	 * @param customObservationConvention The optional, custom search observation
+	 * convention to use.
+	 */
+	public AzureVectorStore(SearchIndexClient searchIndexClient, EmbeddingModel embeddingModel,
+			boolean initializeSchema, List<MetadataField> filterMetadataFields, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
 
 		Assert.notNull(embeddingModel, "The embedding model can not be null.");
 		Assert.notNull(searchIndexClient, "The search index client can not be null.");
@@ -208,7 +235,7 @@ public class AzureVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 
 		Assert.notNull(documents, "The document list should not be null.");
 		if (CollectionUtils.isEmpty(documents)) {
@@ -243,7 +270,7 @@ public class AzureVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> documentIds) {
+	public Optional<Boolean> doDelete(List<String> documentIds) {
 
 		Assert.notNull(documentIds, "The document ID list should not be null.");
 		if (CollectionUtils.isEmpty(documentIds)) {
@@ -278,7 +305,7 @@ public class AzureVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 
 		Assert.notNull(request, "The search request must not be null.");
 
@@ -379,4 +406,13 @@ public class AzureVectorStore implements VectorStore, InitializingBean {
 		this.searchClient = this.searchIndexClient.getSearchClient(this.indexName);
 	}
 
+	@Override
+	public Builder createObservationContextBuilder(String operationName) {
+
+		return VectorStoreObservationContext.builder(VectorStoreProvider.AZURE.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withSimilarityMetric(this.initializeSchema ? VectorStoreSimilarityMetric.COSINE.value() : null)
+			.withIndexName(this.indexName);
+	}
+
 }

vector-stores/spring-ai-azure-store/src/test/java/org/springframework/ai/vectorstore/azure/AzureVectorStoreObservationIT.java

@@ -0,0 +1,183 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore.azure;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.time.Duration;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.TimeUnit;
+
+import org.awaitility.Awaitility;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.transformers.TransformersEmbeddingModel;
+import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.azure.AzureVectorStore.MetadataField;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+
+import com.azure.core.credential.AzureKeyCredential;
+import com.azure.search.documents.indexes.SearchIndexClient;
+import com.azure.search.documents.indexes.SearchIndexClientBuilder;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+/**
+ * Integration tests for observation instrumentation AbstractObservationVectorStore in
+ * {@link AzureVectorStore}.
+ *
+ * @author Christian Tzolov
+ */
+@EnabledIfEnvironmentVariable(named = "AZURE_AI_SEARCH_API_KEY", matches = ".+")
+@EnabledIfEnvironmentVariable(named = "AZURE_AI_SEARCH_ENDPOINT", matches = ".+")
+public class AzureVectorStoreObservationIT {
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	@BeforeAll
+	public static void beforeAll() {
+		Awaitility.setDefaultPollInterval(2, TimeUnit.SECONDS);
+		Awaitility.setDefaultPollDelay(Duration.ZERO);
+		Awaitility.setDefaultTimeout(Duration.ofMinutes(1));
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store azure add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(), "azure")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store azure query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(), "azure")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public SearchIndexClient searchIndexClient() {
+			return new SearchIndexClientBuilder().endpoint(System.getenv("AZURE_AI_SEARCH_ENDPOINT"))
+				.credential(new AzureKeyCredential(System.getenv("AZURE_AI_SEARCH_API_KEY")))
+				.buildClient();
+		}
+
+		@Bean
+		public VectorStore vectorStore(SearchIndexClient searchIndexClient, EmbeddingModel embeddingModel,
+				ObservationRegistry observationRegistry) {
+			var filterableMetaFields = List.of(MetadataField.text("country"), MetadataField.int64("year"),
+					MetadataField.date("activationDate"));
+			return new AzureVectorStore(searchIndexClient, embeddingModel, true, filterableMetaFields,
+					observationRegistry, null);
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new TransformersEmbeddingModel();
+		}
+
+	}
+
+}

vector-stores/spring-ai-cassandra-store/pom.xml

@@ -71,6 +71,11 @@
 			<scope>test</scope>
 		</dependency>
 
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
 	</dependencies>
 
 </project>

vector-stores/spring-ai-cassandra-store/src/main/java/org/springframework/ai/vectorstore/CassandraVectorStore.java

@@ -29,14 +29,22 @@ import com.datastax.oss.driver.api.querybuilder.insert.InsertInto;
 import com.datastax.oss.driver.api.querybuilder.insert.RegularInsert;
 import com.datastax.oss.driver.shaded.guava.common.base.Preconditions;
 
+import io.micrometer.observation.ObservationRegistry;
+
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.model.EmbeddingUtils;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.vectorstore.CassandraVectorStoreConfig.SchemaColumn;
 import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext.Builder;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 
 import java.util.ArrayList;
 import java.util.HashMap;
@@ -86,12 +94,13 @@ import java.util.concurrent.ConcurrentMap;
  * also serve as a protecting throttle against your embedding model.
  *
  * @author Mick Semb Wever
+ * @author Christian Tzolov
  * @see VectorStore
  * @see org.springframework.ai.vectorstore.CassandraVectorStoreConfig
  * @see EmbeddingModel
  * @since 1.0.0
  */
-public class CassandraVectorStore implements VectorStore, AutoCloseable {
+public class CassandraVectorStore extends AbstractObservationVectorStore implements AutoCloseable {
 
 	/**
 	 * Indexes are automatically created with COSINE. This can be changed manually via
@@ -127,11 +136,14 @@ public class CassandraVectorStore implements VectorStore, AutoCloseable {
 
 	private final Similarity similarity;
 
-	public static CassandraVectorStore create(CassandraVectorStoreConfig conf, EmbeddingModel embeddingModel) {
-		return new CassandraVectorStore(conf, embeddingModel);
+	public CassandraVectorStore(CassandraVectorStoreConfig conf, EmbeddingModel embeddingModel) {
+		this(conf, embeddingModel, ObservationRegistry.NOOP, null);
 	}
 
-	public CassandraVectorStore(CassandraVectorStoreConfig conf, EmbeddingModel embeddingModel) {
+	public CassandraVectorStore(CassandraVectorStoreConfig conf, EmbeddingModel embeddingModel,
+			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
 
 		Preconditions.checkArgument(null != conf, "Config must not be null");
 		Preconditions.checkArgument(null != embeddingModel, "Embedding model must not be null");
@@ -156,7 +168,7 @@ public class CassandraVectorStore implements VectorStore, AutoCloseable {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		var futures = new CompletableFuture[documents.size()];
 
 		int i = 0;
@@ -194,7 +206,7 @@ public class CassandraVectorStore implements VectorStore, AutoCloseable {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 		CompletableFuture[] futures = new CompletableFuture[idList.size()];
 		int i = 0;
 		for (String id : idList) {
@@ -207,7 +219,7 @@ public class CassandraVectorStore implements VectorStore, AutoCloseable {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 		Preconditions.checkArgument(request.getTopK() <= 1000);
 		var embedding = toFloatArray(this.embeddingModel.embed(request.getQuery()));
 		CqlVector<Float> cqlVector = CqlVector.newInstance(embedding);
@@ -366,4 +378,25 @@ public class CassandraVectorStore implements VectorStore, AutoCloseable {
 		return embeddingFloat;
 	}
 
+	@Override
+	public Builder createObservationContextBuilder(String operationName) {
+		return VectorStoreObservationContext.builder(VectorStoreProvider.CASSANDRA.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withCollectionName(this.conf.schema.table())
+			.withNamespace(this.conf.schema.keyspace())
+			.withSimilarityMetric(getSimilarityMetric())
+			.withIndexName(this.conf.schema.index());
+	}
+
+	private static Map<Similarity, VectorStoreSimilarityMetric> SIMILARITY_TYPE_MAPPING = Map.of(Similarity.COSINE,
+			VectorStoreSimilarityMetric.COSINE, Similarity.EUCLIDEAN, VectorStoreSimilarityMetric.EUCLIDEAN,
+			Similarity.DOT_PRODUCT, VectorStoreSimilarityMetric.DOT);
+
+	private String getSimilarityMetric() {
+		if (!SIMILARITY_TYPE_MAPPING.containsKey(this.similarity)) {
+			return this.similarity.name();
+		}
+		return SIMILARITY_TYPE_MAPPING.get(this.similarity).value();
+	}
+
 }

vector-stores/spring-ai-cassandra-store/src/test/java/org/springframework/ai/vectorstore/CassandraRichSchemaVectorStoreIT.java

@@ -195,7 +195,7 @@ class CassandraRichSchemaVectorStoreIT {
 
 		contextRunner.run(context -> {
 
-			try (CassandraVectorStore store = CassandraVectorStore.create(
+			try (CassandraVectorStore store = new CassandraVectorStore(
 					storeBuilder(context, List.of()).withFixedThreadPoolExecutorSize(nThreads).build(),
 					context.getBean(EmbeddingModel.class))) {
 

vector-stores/spring-ai-cassandra-store/src/test/java/org/springframework/ai/vectorstore/CassandraVectorStoreIT.java

@@ -396,7 +396,7 @@ class CassandraVectorStoreIT {
 				.build();
 
 			conf.dropKeyspace();
-			return CassandraVectorStore.create(conf, embeddingModel);
+			return new CassandraVectorStore(conf, embeddingModel);
 		}
 
 		@Bean
@@ -432,7 +432,7 @@ class CassandraVectorStoreIT {
 			CassandraVectorStoreConfig.Builder builder) {
 		CassandraVectorStoreConfig conf = builder.build();
 		conf.dropKeyspace();
-		return CassandraVectorStore.create(conf, context.getBean(EmbeddingModel.class));
+		return new CassandraVectorStore(conf, context.getBean(EmbeddingModel.class));
 	}
 
 }

vector-stores/spring-ai-cassandra-store/src/test/java/org/springframework/ai/vectorstore/CassandraVectorStoreObservationIT.java

@@ -0,0 +1,187 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.transformers.TransformersEmbeddingModel;
+import org.springframework.ai.vectorstore.CassandraVectorStoreConfig.SchemaColumn;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.testcontainers.containers.CassandraContainer;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+import org.testcontainers.utility.DockerImageName;
+
+import com.datastax.oss.driver.api.core.CqlSession;
+import com.datastax.oss.driver.api.core.CqlSessionBuilder;
+import com.datastax.oss.driver.api.core.type.DataTypes;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+public class CassandraVectorStoreObservationIT {
+
+	static final DockerImageName DEFAULT_IMAGE_NAME = DockerImageName.parse("cassandra");
+
+	@Container
+	static CassandraContainer cassandraContainer = new CassandraContainer(DEFAULT_IMAGE_NAME.withTag("5.0"));
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store cassandra add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(), "cassandra")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "ai_vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "test_springframework")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store cassandra query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(), "cassandra")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "ai_vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "test_springframework")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new TransformersEmbeddingModel();
+		}
+
+		@Bean
+		public CassandraVectorStore store(CqlSession cqlSession, EmbeddingModel embeddingModel,
+				ObservationRegistry observationRegistry) {
+
+			CassandraVectorStoreConfig conf = storeBuilder(cqlSession)
+				.addMetadataColumns(new SchemaColumn("meta1", DataTypes.TEXT),
+						new SchemaColumn("meta2", DataTypes.TEXT), new SchemaColumn("country", DataTypes.TEXT),
+						new SchemaColumn("year", DataTypes.SMALLINT))
+				.build();
+
+			conf.dropKeyspace();
+			return new CassandraVectorStore(conf, embeddingModel, observationRegistry, null);
+		}
+
+		@Bean
+		public CqlSession cqlSession() {
+			return new CqlSessionBuilder()
+				// comment next two lines out to connect to a local C* cluster
+				.addContactPoint(cassandraContainer.getContactPoint())
+				.withLocalDatacenter(cassandraContainer.getLocalDatacenter())
+				.build();
+		}
+
+	}
+
+	private static CassandraVectorStoreConfig.Builder storeBuilder(CqlSession cqlSession) {
+		return CassandraVectorStoreConfig.builder()
+			.withCqlSession(cqlSession)
+			.withKeyspaceName("test_" + CassandraVectorStoreConfig.DEFAULT_KEYSPACE_NAME);
+	}
+
+}

vector-stores/spring-ai-cassandra-store/src/test/java/org/springframework/ai/vectorstore/WikiVectorStoreExample.java

@@ -119,7 +119,7 @@ class WikiVectorStoreExample {
 				})
 				.build();
 
-			return CassandraVectorStore.create(conf, embeddingModel());
+			return new CassandraVectorStore(conf, embeddingModel());
 		}
 
 		@Bean

vector-stores/spring-ai-chroma-store/pom.xml

@@ -1,6 +1,7 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project xmlns="http://maven.apache.org/POM/4.0.0"
-	xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
+	xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+	xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
 	<modelVersion>4.0.0</modelVersion>
 	<parent>
 		<groupId>org.springframework.ai</groupId>
@@ -58,6 +59,18 @@
 			<scope>test</scope>
 		</dependency>
 
+		<dependency>
+			<groupId>org.springframework.ai</groupId>
+			<artifactId>spring-ai-test</artifactId>
+			<version>${project.parent.version}</version>
+			<scope>test</scope>
+		</dependency>
+
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
 	</dependencies>
 
-</project>
+</project>

vector-stores/spring-ai-chroma-store/src/main/java/org/springframework/ai/vectorstore/ChromaVectorStore.java

@@ -27,12 +27,19 @@ import org.springframework.ai.chroma.ChromaApi.DeleteEmbeddingsRequest;
 import org.springframework.ai.chroma.ChromaApi.Embedding;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext.Builder;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.InitializingBean;
 import org.springframework.util.Assert;
 import org.springframework.util.CollectionUtils;
 import org.springframework.util.StringUtils;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * {@link ChromaVectorStore} is a concrete implementation of the {@link VectorStore}
  * interface. It is responsible for adding, deleting, and searching documents based on
@@ -40,7 +47,7 @@ import org.springframework.util.StringUtils;
  * embedding calculations. For more information about how it does this, see the official
  * <a href="https://www.trychroma.com/">Chroma website</a>.
  */
-public class ChromaVectorStore implements VectorStore, InitializingBean {
+public class ChromaVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	public static final String DISTANCE_FIELD_NAME = "distance";
 
@@ -68,6 +75,15 @@ public class ChromaVectorStore implements VectorStore, InitializingBean {
 
 	public ChromaVectorStore(EmbeddingModel embeddingModel, ChromaApi chromaApi, String collectionName,
 			boolean initializeSchema) {
+		this(embeddingModel, chromaApi, collectionName, initializeSchema, ObservationRegistry.NOOP, null);
+	}
+
+	public ChromaVectorStore(EmbeddingModel embeddingModel, ChromaApi chromaApi, String collectionName,
+			boolean initializeSchema, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		this.embeddingModel = embeddingModel;
 		this.chromaApi = chromaApi;
 		this.collectionName = collectionName;
@@ -81,7 +97,7 @@ public class ChromaVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		Assert.notNull(documents, "Documents must not be null");
 		if (CollectionUtils.isEmpty(documents)) {
 			return;
@@ -105,7 +121,7 @@ public class ChromaVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 		Assert.notNull(idList, "Document id list must not be null");
 		List<String> deletedIds = this.chromaApi.deleteEmbeddings(this.collectionId,
 				new DeleteEmbeddingsRequest(idList));
@@ -113,7 +129,7 @@ public class ChromaVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 
 		String nativeFilterExpression = (request.getFilterExpression() != null)
 				? this.filterExpressionConverter.convertExpression(request.getFilterExpression()) : "";
@@ -149,6 +165,14 @@ public class ChromaVectorStore implements VectorStore, InitializingBean {
 		return responseDocuments;
 	}
 
+	public String getCollectionName() {
+		return this.collectionName;
+	}
+
+	public String getCollectionId() {
+		return this.collectionId;
+	}
+
 	@Override
 	public void afterPropertiesSet() throws Exception {
 
@@ -162,4 +186,12 @@ public class ChromaVectorStore implements VectorStore, InitializingBean {
 		this.collectionId = collection.id();
 	}
 
+	@Override
+	public Builder createObservationContextBuilder(String operationName) {
+		return VectorStoreObservationContext.builder(VectorStoreProvider.CHROMA.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withCollectionName(this.collectionName + ":" + this.collectionId)
+			.withFieldName(this.initializeSchema ? DISTANCE_FIELD_NAME : null);
+	}
+
 }

vector-stores/spring-ai-chroma-store/src/test/java/org/springframework/ai/vectorstore/ChromaVectorStoreObservationIT.java

@@ -0,0 +1,175 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.chroma.ChromaApi;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
+import org.springframework.ai.openai.api.OpenAiApi;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.springframework.http.client.SimpleClientHttpRequestFactory;
+import org.springframework.web.client.RestClient;
+import org.testcontainers.chromadb.ChromaDBContainer;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+public class ChromaVectorStoreObservationIT {
+
+	@Container
+	static ChromaDBContainer chromaContainer = new ChromaDBContainer("ghcr.io/chroma-core/chroma:0.5.0");
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			ChromaVectorStore vectorStore = context.getBean(ChromaVectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store chroma add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.CHROMA.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(),
+						"TestCollection:" + vectorStore.getCollectionId())
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "distance")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store chroma query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.CHROMA.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(),
+						"TestCollection:" + vectorStore.getCollectionId())
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "distance")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public RestClient.Builder builder() {
+			return RestClient.builder().requestFactory(new SimpleClientHttpRequestFactory());
+		}
+
+		@Bean
+		public ChromaApi chromaApi(RestClient.Builder builder) {
+			return new ChromaApi(chromaContainer.getEndpoint(), builder);
+		}
+
+		@Bean
+		public VectorStore chromaVectorStore(EmbeddingModel embeddingModel, ChromaApi chromaApi,
+				ObservationRegistry observationRegistry) {
+			return new ChromaVectorStore(embeddingModel, chromaApi, "TestCollection", true, observationRegistry, null);
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new OpenAiEmbeddingModel(new OpenAiApi(System.getenv("OPENAI_API_KEY")));
+		}
+
+	}
+
+}

vector-stores/spring-ai-elasticsearch-store/pom.xml

@@ -71,6 +71,11 @@
 			<scope>test</scope>
 		</dependency>
 
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
 	</dependencies>
 
 </project>

vector-stores/spring-ai-elasticsearch-store/src/main/java/org/springframework/ai/vectorstore/ElasticsearchVectorStore.java

@@ -15,6 +15,35 @@
  */
 package org.springframework.ai.vectorstore;
 
+import static java.lang.Math.sqrt;
+
+import java.io.IOException;
+import java.util.List;
+import java.util.Map;
+import java.util.Objects;
+import java.util.Optional;
+import java.util.stream.Collectors;
+
+import org.elasticsearch.client.RestClient;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.model.EmbeddingUtils;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
+import org.springframework.ai.vectorstore.filter.Filter;
+import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext.Builder;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.InitializingBean;
+import org.springframework.util.Assert;
+
+import com.fasterxml.jackson.databind.DeserializationFeature;
+import com.fasterxml.jackson.databind.ObjectMapper;
+
 import co.elastic.clients.elasticsearch.ElasticsearchClient;
 import co.elastic.clients.elasticsearch.core.BulkRequest;
 import co.elastic.clients.elasticsearch.core.BulkResponse;
@@ -23,27 +52,7 @@ import co.elastic.clients.elasticsearch.core.bulk.BulkResponseItem;
 import co.elastic.clients.elasticsearch.core.search.Hit;
 import co.elastic.clients.json.jackson.JacksonJsonpMapper;
 import co.elastic.clients.transport.rest_client.RestClientTransport;
-import com.fasterxml.jackson.databind.DeserializationFeature;
-import com.fasterxml.jackson.databind.ObjectMapper;
-import org.elasticsearch.client.RestClient;
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
-import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.EmbeddingModel;
-import org.springframework.ai.model.EmbeddingUtils;
-import org.springframework.ai.vectorstore.filter.Filter;
-import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
-import org.springframework.beans.factory.InitializingBean;
-import org.springframework.util.Assert;
-
-import java.io.IOException;
-import java.util.List;
-import java.util.Objects;
-import java.util.Optional;
-import java.util.stream.Collectors;
-
-import static java.lang.Math.sqrt;
-import static org.springframework.ai.vectorstore.SimilarityFunction.l2_norm;
+import io.micrometer.observation.ObservationRegistry;
 
 /**
  * The ElasticsearchVectorStore class implements the VectorStore interface and provides
@@ -58,9 +67,10 @@ import static org.springframework.ai.vectorstore.SimilarityFunction.l2_norm;
  * @author Wei Jiang
  * @author Laura Trotta
  * @author Soby Chacko
+ * @author Christian Tzolov
  * @since 1.0.0
  */
-public class ElasticsearchVectorStore implements VectorStore, InitializingBean {
+public class ElasticsearchVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	private static final Logger logger = LoggerFactory.getLogger(ElasticsearchVectorStore.class);
 
@@ -80,6 +90,15 @@ public class ElasticsearchVectorStore implements VectorStore, InitializingBean {
 
 	public ElasticsearchVectorStore(ElasticsearchVectorStoreOptions options, RestClient restClient,
 			EmbeddingModel embeddingModel, boolean initializeSchema) {
+		this(options, restClient, embeddingModel, initializeSchema, ObservationRegistry.NOOP, null);
+	}
+
+	public ElasticsearchVectorStore(ElasticsearchVectorStoreOptions options, RestClient restClient,
+			EmbeddingModel embeddingModel, boolean initializeSchema, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		this.initializeSchema = initializeSchema;
 		Objects.requireNonNull(embeddingModel, "RestClient must not be null");
 		Objects.requireNonNull(embeddingModel, "EmbeddingModel must not be null");
@@ -91,7 +110,7 @@ public class ElasticsearchVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		BulkRequest.Builder bulkRequestBuilder = new BulkRequest.Builder();
 
 		for (Document document : documents) {
@@ -119,7 +138,7 @@ public class ElasticsearchVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 		BulkRequest.Builder bulkRequestBuilder = new BulkRequest.Builder();
 		// We call operations on BulkRequest.Builder only if the index exists.
 		// For the index to be present, either it must be pre-created or set the
@@ -142,12 +161,12 @@ public class ElasticsearchVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest searchRequest) {
+	public List<Document> doSimilaritySearch(SearchRequest searchRequest) {
 		Assert.notNull(searchRequest, "The search request must not be null.");
 		try {
 			float threshold = (float) searchRequest.getSimilarityThreshold();
 			// reverting l2_norm distance to its original value
-			if (options.getSimilarity().equals(l2_norm)) {
+			if (options.getSimilarity().equals(SimilarityFunction.l2_norm)) {
 				threshold = 1 - threshold;
 			}
 			final float finalThreshold = threshold;
@@ -230,4 +249,24 @@ public class ElasticsearchVectorStore implements VectorStore, InitializingBean {
 		}
 	}
 
+	@Override
+	public Builder createObservationContextBuilder(String operationName) {
+		return VectorStoreObservationContext.builder(VectorStoreProvider.ELASTICSEARCH.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withIndexName(this.options.getIndexName())
+			.withSimilarityMetric(getSimilarityMetric());
+
+	}
+
+	private static Map<SimilarityFunction, VectorStoreSimilarityMetric> SIMILARITY_TYPE_MAPPING = Map.of(
+			SimilarityFunction.cosine, VectorStoreSimilarityMetric.COSINE, SimilarityFunction.l2_norm,
+			VectorStoreSimilarityMetric.EUCLIDEAN, SimilarityFunction.dot_product, VectorStoreSimilarityMetric.DOT);
+
+	private String getSimilarityMetric() {
+		if (!SIMILARITY_TYPE_MAPPING.containsKey(this.options.getSimilarity())) {
+			return this.options.getSimilarity().name();
+		}
+		return SIMILARITY_TYPE_MAPPING.get(this.options.getSimilarity()).value();
+	}
+
 }

vector-stores/spring-ai-elasticsearch-store/src/test/java/org/springframework/ai/vectorstore/ElasticsearchVectorStoreObservationIT.java

@@ -0,0 +1,217 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.time.Duration;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.TimeUnit;
+
+import org.apache.http.HttpHost;
+import org.awaitility.Awaitility;
+import org.elasticsearch.client.RestClient;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
+import org.springframework.ai.openai.api.OpenAiApi;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.testcontainers.elasticsearch.ElasticsearchContainer;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+
+import com.fasterxml.jackson.databind.DeserializationFeature;
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import co.elastic.clients.elasticsearch.ElasticsearchClient;
+import co.elastic.clients.elasticsearch.cat.indices.IndicesRecord;
+import co.elastic.clients.json.jackson.JacksonJsonpMapper;
+import co.elastic.clients.transport.rest_client.RestClientTransport;
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+import static org.hamcrest.Matchers.greaterThan;;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
+public class ElasticsearchVectorStoreObservationIT {
+
+	@Container
+	private static final ElasticsearchContainer elasticsearchContainer = new ElasticsearchContainer(
+			"docker.elastic.co/elasticsearch/elasticsearch:8.13.3")
+		.withEnv("xpack.security.enabled", "false");
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	private ApplicationContextRunner getContextRunner() {
+		return new ApplicationContextRunner().withUserConfiguration(Config.class);
+	}
+
+	@BeforeAll
+	public static void beforeAll() {
+		Awaitility.setDefaultPollInterval(2, TimeUnit.SECONDS);
+		Awaitility.setDefaultPollDelay(Duration.ZERO);
+		Awaitility.setDefaultTimeout(Duration.ofMinutes(1));
+	}
+
+	@BeforeEach
+	void cleanDatabase() {
+		getContextRunner().run(context -> {
+			// deleting indices and data before following tests
+			ElasticsearchClient elasticsearchClient = context.getBean(ElasticsearchClient.class);
+			List indices = elasticsearchClient.cat().indices().valueBody().stream().map(IndicesRecord::index).toList();
+			if (!indices.isEmpty()) {
+				elasticsearchClient.indices().delete(del -> del.index(indices));
+			}
+		});
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		getContextRunner().run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store elasticsearch add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.ELASTICSEARCH.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			Awaitility.await()
+				.until(() -> vectorStore
+					.similaritySearch(SearchRequest.query("What is Great Depression").withSimilarityThresholdAll())
+					.size(), greaterThan(1));
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store elasticsearch query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.ELASTICSEARCH.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration(exclude = { DataSourceAutoConfiguration.class })
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public ElasticsearchVectorStore vectorStoreDefault(EmbeddingModel embeddingModel, RestClient restClient,
+				ObservationRegistry observationRegistry) {
+			return new ElasticsearchVectorStore(new ElasticsearchVectorStoreOptions(), restClient, embeddingModel, true,
+					observationRegistry, null);
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new OpenAiEmbeddingModel(new OpenAiApi(System.getenv("OPENAI_API_KEY")));
+		}
+
+		@Bean
+		RestClient restClient() {
+			return RestClient.builder(HttpHost.create(elasticsearchContainer.getHttpHostAddress())).build();
+		}
+
+		@Bean
+		ElasticsearchClient elasticsearchClient(RestClient restClient) {
+			return new ElasticsearchClient(new RestClientTransport(restClient, new JacksonJsonpMapper(
+					new ObjectMapper().configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false))));
+		}
+
+	}
+
+}

vector-stores/spring-ai-gemfire-store/pom.xml

@@ -78,7 +78,11 @@
             <version>3.0.0</version>
             <scope>test</scope>
         </dependency>
-
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
     </dependencies>
 
 </project>

vector-stores/spring-ai-gemfire-store/src/main/java/org/springframework/ai/vectorstore/GemFireVectorStore.java

@@ -23,15 +23,15 @@ import java.util.List;
 import java.util.Map;
 import java.util.Optional;
 
-import com.fasterxml.jackson.annotation.JsonCreator;
-import com.fasterxml.jackson.annotation.JsonInclude;
-import com.fasterxml.jackson.annotation.JsonProperty;
-import com.fasterxml.jackson.core.JsonProcessingException;
-import com.fasterxml.jackson.databind.ObjectMapper;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext.Builder;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.InitializingBean;
 import org.springframework.http.HttpMethod;
 import org.springframework.http.MediaType;
@@ -41,6 +41,14 @@ import org.springframework.web.reactive.function.client.WebClient;
 import org.springframework.web.reactive.function.client.WebClientException;
 import org.springframework.web.reactive.function.client.WebClientResponseException;
 import org.springframework.web.util.UriComponentsBuilder;
+
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonInclude;
+import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import io.micrometer.observation.ObservationRegistry;
 import reactor.util.annotation.NonNull;
 
 /**
@@ -48,8 +56,9 @@ import reactor.util.annotation.NonNull;
  * deleting, and similarity searching of documents in a GemFire index.
  *
  * @author Geet Rawat
+ * @author Christian Tzolov
  */
-public class GemFireVectorStore implements VectorStore, InitializingBean {
+public class GemFireVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	private static final Logger logger = LoggerFactory.getLogger(GemFireVectorStore.class);
 
@@ -70,10 +79,29 @@ public class GemFireVectorStore implements VectorStore, InitializingBean {
 	 * configuration.
 	 * @param config the configuration for the GemFireVectorStore
 	 * @param embeddingModel the embedding client used for generating embeddings
+	 * @param initializeSchema whether to initialize the schema during initialization
 	 */
-
 	public GemFireVectorStore(GemFireVectorStoreConfig config, EmbeddingModel embeddingModel,
 			boolean initializeSchema) {
+		this(config, embeddingModel, initializeSchema, ObservationRegistry.NOOP, null);
+	}
+
+	/**
+	 * Configures and initializes a GemFireVectorStore instance based on the provided
+	 * configuration.
+	 * @param config the configuration for the GemFireVectorStore
+	 * @param embeddingModel the embedding client used for generating embeddings
+	 * @param initializeSchema whether to initialize the schema during initialization
+	 * @param observationRegistry the observation registry to use for recording
+	 * observations
+	 * @param customObservationConvention the custom observation convention to use for
+	 * observing operations
+	 */
+	public GemFireVectorStore(GemFireVectorStoreConfig config, EmbeddingModel embeddingModel, boolean initializeSchema,
+			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		Assert.notNull(config, "GemFireVectorStoreConfig must not be null");
 		Assert.notNull(embeddingModel, "EmbeddingModel must not be null");
 		this.initializeSchema = initializeSchema;
@@ -374,7 +402,7 @@ public class GemFireVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		UploadRequest upload = new UploadRequest(documents.stream().map(document -> {
 			// Compute and assign an embedding to the document.
 			document.setEmbedding(this.embeddingModel.embed(document));
@@ -404,7 +432,7 @@ public class GemFireVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 		try {
 			client.method(HttpMethod.DELETE)
 				.uri("/" + indexName + EMBEDDINGS)
@@ -421,7 +449,7 @@ public class GemFireVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 		if (request.hasFilterExpression()) {
 			throw new UnsupportedOperationException("GemFire currently does not support metadata filter expressions.");
 		}
@@ -507,4 +535,12 @@ public class GemFireVectorStore implements VectorStore, InitializingBean {
 		}
 	}
 
+	@Override
+	public Builder createObservationContextBuilder(String operationName) {
+		return VectorStoreObservationContext.builder(VectorStoreProvider.GEMFIRE.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withIndexName(this.indexName)
+			.withFieldName(EMBEDDINGS);
+	}
+
 }

vector-stores/spring-ai-gemfire-store/src/test/java/org/springframework/ai/vectorstore/GemFireVectorStoreObservationIT.java

@@ -0,0 +1,210 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+
+import org.awaitility.Awaitility;
+import org.junit.jupiter.api.AfterAll;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.transformers.TransformersEmbeddingModel;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+
+import com.github.dockerjava.api.model.ExposedPort;
+import com.github.dockerjava.api.model.PortBinding;
+import com.github.dockerjava.api.model.Ports;
+import com.vmware.gemfire.testcontainers.GemFireCluster;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+import static java.util.concurrent.TimeUnit.MINUTES;
+import static org.hamcrest.Matchers.hasSize;
+
+/**
+ * @author Christian Tzolov
+ */
+public class GemFireVectorStoreObservationIT {
+
+	public static final String INDEX_NAME = "spring-ai-index1";
+
+	private static GemFireCluster gemFireCluster;
+
+	private static final int HTTP_SERVICE_PORT = 9090;
+
+	private static final int LOCATOR_COUNT = 1;
+
+	private static final int SERVER_COUNT = 1;
+
+	@AfterAll
+	public static void stopGemFireCluster() {
+		gemFireCluster.close();
+	}
+
+	@BeforeAll
+	public static void startGemFireCluster() {
+		Ports.Binding hostPort = Ports.Binding.bindPort(HTTP_SERVICE_PORT);
+		ExposedPort exposedPort = new ExposedPort(HTTP_SERVICE_PORT);
+		PortBinding mappedPort = new PortBinding(hostPort, exposedPort);
+		gemFireCluster = new GemFireCluster("gemfire/gemfire-all:10.1-jdk17", LOCATOR_COUNT, SERVER_COUNT);
+		gemFireCluster.withConfiguration(GemFireCluster.SERVER_GLOB,
+				container -> container.withExposedPorts(HTTP_SERVICE_PORT)
+					.withCreateContainerCmdModifier(cmd -> cmd.getHostConfig().withPortBindings(mappedPort)));
+		gemFireCluster.withGemFireProperty(GemFireCluster.SERVER_GLOB, "http-service-port",
+				Integer.toString(HTTP_SERVICE_PORT));
+		gemFireCluster.acceptLicense().start();
+
+		System.setProperty("spring.data.gemfire.pool.locators",
+				String.format("localhost[%d]", gemFireCluster.getLocatorPort()));
+	}
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store gemfire add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.GEMFIRE.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "/embeddings")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.INDEX_NAME.asString(), INDEX_NAME)
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			Awaitility.await()
+				.atMost(1, MINUTES)
+				.until(() -> vectorStore
+					.similaritySearch(SearchRequest.query("Great Depression").withTopK(5).withSimilarityThresholdAll()),
+						hasSize(3));
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store gemfire query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.GEMFIRE.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "/embeddings")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.INDEX_NAME.asString(), INDEX_NAME)
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public GemFireVectorStoreConfig gemfireVectorStoreConfig() {
+			return new GemFireVectorStoreConfig().setHost("localhost")
+				.setPort(HTTP_SERVICE_PORT)
+				.setIndexName(INDEX_NAME);
+		}
+
+		@Bean
+		public GemFireVectorStore vectorStore(GemFireVectorStoreConfig config, EmbeddingModel embeddingModel,
+				ObservationRegistry observationRegistry) {
+			return new GemFireVectorStore(config, embeddingModel, true, observationRegistry, null);
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new TransformersEmbeddingModel();
+		}
+
+	}
+
+}

vector-stores/spring-ai-hanadb-store/pom.xml

@@ -1,6 +1,7 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project xmlns="http://maven.apache.org/POM/4.0.0"
-         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
+    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+    xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
     <modelVersion>4.0.0</modelVersion>
     <parent>
         <groupId>org.springframework.ai</groupId>
@@ -71,6 +72,10 @@
             <version>${parent.version}</version>
             <scope>test</scope>
         </dependency>
-
+        <dependency>
+            <groupId>io.micrometer</groupId>
+            <artifactId>micrometer-observation-test</artifactId>
+            <scope>test</scope>
+        </dependency>
     </dependencies>
-</project>
+</project>

vector-stores/spring-ai-hanadb-store/src/main/java/org/springframework/ai/vectorstore/HanaCloudVectorStore.java

@@ -16,11 +16,20 @@
 package org.springframework.ai.vectorstore;
 
 import com.fasterxml.jackson.core.JsonProcessingException;
+
+import io.micrometer.observation.ObservationRegistry;
+
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.model.EmbeddingUtils;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext.Builder;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 
 import java.util.Collections;
 import java.util.List;
@@ -54,12 +63,13 @@ import java.util.stream.Collectors;
  * generated by <code>org.springframework.ai.embedding.EmbeddingModel</code>
  *
  * @author Rahul Mittal
+ * @author Christian Tzolov
  * @see <a href=
  * "https://help.sap.com/docs/hana-cloud-database/sap-hana-cloud-sap-hana-database-vector-engine-guide/introduction">SAP
  * HANA Database Vector Engine Guide</a>
  * @since 1.0.0
  */
-public class HanaCloudVectorStore implements VectorStore {
+public class HanaCloudVectorStore extends AbstractObservationVectorStore {
 
 	private static final Logger logger = LoggerFactory.getLogger(HanaCloudVectorStore.class);
 
@@ -71,13 +81,23 @@ public class HanaCloudVectorStore implements VectorStore {
 
 	public HanaCloudVectorStore(HanaVectorRepository<? extends HanaVectorEntity> repository,
 			EmbeddingModel embeddingModel, HanaCloudVectorStoreConfig config) {
+
+		this(repository, embeddingModel, config, ObservationRegistry.NOOP, null);
+	}
+
+	public HanaCloudVectorStore(HanaVectorRepository<? extends HanaVectorEntity> repository,
+			EmbeddingModel embeddingModel, HanaCloudVectorStoreConfig config, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		this.repository = repository;
 		this.embeddingModel = embeddingModel;
 		this.config = config;
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		int count = 1;
 		for (Document document : documents) {
 			logger.info("[{}/{}] Calling EmbeddingModel for document id = {}", count++, documents.size(),
@@ -90,7 +110,7 @@ public class HanaCloudVectorStore implements VectorStore {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 		int deleteCount = repository.deleteEmbeddingsById(config.getTableName(), idList);
 		logger.info("{} embeddings deleted", deleteCount);
 		return Optional.of(deleteCount == idList.size());
@@ -108,7 +128,7 @@ public class HanaCloudVectorStore implements VectorStore {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 		if (request.hasFilterExpression()) {
 			throw new UnsupportedOperationException(
 					"SAPHanaVectorEngine does not support metadata filter expressions yet.");
@@ -144,4 +164,13 @@ public class HanaCloudVectorStore implements VectorStore {
 			.collect(Collectors.joining(", ")) + "]";
 	}
 
+	@Override
+	public Builder createObservationContextBuilder(String operationName) {
+
+		return VectorStoreObservationContext.builder(VectorStoreProvider.HANA.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withCollectionName(this.config.getTableName())
+			.withSimilarityMetric(VectorStoreSimilarityMetric.COSINE.value());
+	}
+
 }

vector-stores/spring-ai-hanadb-store/src/test/java/org/springframework/ai/vectorstore/HanaVectorStoreObservationIT.java

@@ -0,0 +1,195 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+
+import javax.sql.DataSource;
+
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
+import org.springframework.ai.openai.api.OpenAiApi;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.springframework.jdbc.datasource.DriverManagerDataSource;
+import org.springframework.orm.jpa.JpaVendorAdapter;
+import org.springframework.orm.jpa.LocalContainerEntityManagerFactoryBean;
+import org.springframework.orm.jpa.vendor.HibernateJpaVendorAdapter;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+/**
+ * @author Christian Tzolov
+ */
+@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
+@EnabledIfEnvironmentVariable(named = "HANA_DATASOURCE_URL", matches = ".+")
+@EnabledIfEnvironmentVariable(named = "HANA_DATASOURCE_USERNAME", matches = ".+")
+@EnabledIfEnvironmentVariable(named = "HANA_DATASOURCE_PASSWORD", matches = ".+")
+public class HanaVectorStoreObservationIT {
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store hana add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.HANA.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "CRICKET_WORLD_CUP")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store hana query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.HANA.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "CRICKET_WORLD_CUP")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public VectorStore hanaCloudVectorStore(CricketWorldCupRepository cricketWorldCupRepository,
+				EmbeddingModel embeddingModel, ObservationRegistry observationRegistry) {
+			return new HanaCloudVectorStore(cricketWorldCupRepository, embeddingModel,
+					HanaCloudVectorStoreConfig.builder().tableName("CRICKET_WORLD_CUP").topK(1).build(),
+					observationRegistry, null);
+		}
+
+		@Bean
+		public CricketWorldCupRepository cricketWorldCupRepository() {
+			return new CricketWorldCupRepository();
+		}
+
+		@Bean
+		public DataSource dataSource() {
+			DriverManagerDataSource dataSource = new DriverManagerDataSource();
+
+			dataSource.setDriverClassName("com.sap.db.jdbc.Driver");
+			dataSource.setUrl(System.getenv("HANA_DATASOURCE_URL"));
+			dataSource.setUsername(System.getenv("HANA_DATASOURCE_USERNAME"));
+			dataSource.setPassword(System.getenv("HANA_DATASOURCE_PASSWORD"));
+
+			return dataSource;
+		}
+
+		@Bean
+		public LocalContainerEntityManagerFactoryBean entityManagerFactory() {
+			LocalContainerEntityManagerFactoryBean em = new LocalContainerEntityManagerFactoryBean();
+			em.setDataSource(dataSource());
+			em.setPackagesToScan("org.springframework.ai.vectorstore");
+
+			JpaVendorAdapter vendorAdapter = new HibernateJpaVendorAdapter();
+			em.setJpaVendorAdapter(vendorAdapter);
+
+			return em;
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new OpenAiEmbeddingModel(new OpenAiApi(System.getenv("OPENAI_API_KEY")));
+		}
+
+	}
+
+}

vector-stores/spring-ai-milvus-store/pom.xml

@@ -74,6 +74,11 @@
 			<scope>test</scope>
 		</dependency>
 
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
 	</dependencies>
 
 </project>

vector-stores/spring-ai-milvus-store/src/main/java/org/springframework/ai/vectorstore/MilvusVectorStore.java

@@ -17,6 +17,7 @@ package org.springframework.ai.vectorstore;
 
 import java.util.ArrayList;
 import java.util.List;
+import java.util.Map;
 import java.util.Optional;
 import java.util.stream.Collectors;
 
@@ -25,13 +26,19 @@ import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.model.EmbeddingUtils;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.InitializingBean;
 import org.springframework.util.Assert;
 import org.springframework.util.StringUtils;
 
 import com.alibaba.fastjson.JSONObject;
 
+import io.micrometer.observation.ObservationRegistry;
 import io.milvus.client.MilvusServiceClient;
 import io.milvus.common.clientenum.ConsistencyLevelEnum;
 import io.milvus.grpc.DataType;
@@ -61,7 +68,7 @@ import io.milvus.response.SearchResultsWrapper;
 /**
  * @author Christian Tzolov
  */
-public class MilvusVectorStore implements VectorStore, InitializingBean {
+public class MilvusVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	private static final Logger logger = LoggerFactory.getLogger(MilvusVectorStore.class);
 
@@ -250,6 +257,15 @@ public class MilvusVectorStore implements VectorStore, InitializingBean {
 
 	public MilvusVectorStore(MilvusServiceClient milvusClient, EmbeddingModel embeddingModel,
 			MilvusVectorStoreConfig config, boolean initializeSchema) {
+		this(milvusClient, embeddingModel, config, initializeSchema, ObservationRegistry.NOOP, null);
+	}
+
+	public MilvusVectorStore(MilvusServiceClient milvusClient, EmbeddingModel embeddingModel,
+			MilvusVectorStoreConfig config, boolean initializeSchema, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		this.initializeSchema = initializeSchema;
 
 		Assert.notNull(milvusClient, "MilvusServiceClient must not be null");
@@ -261,7 +277,7 @@ public class MilvusVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 
 		Assert.notNull(documents, "Documents must not be null");
 
@@ -300,7 +316,7 @@ public class MilvusVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 		Assert.notNull(idList, "Document id list must not be null");
 
 		String deleteExpression = String.format("%s in [%s]", DOC_ID_FIELD_NAME,
@@ -320,7 +336,7 @@ public class MilvusVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 
 		String nativeFilterExpressions = (request.getFilterExpression() != null)
 				? this.filterExpressionConverter.convertExpression(request.getFilterExpression()) : "";
@@ -520,4 +536,27 @@ public class MilvusVectorStore implements VectorStore, InitializingBean {
 		}
 	}
 
+	@Override
+	public org.springframework.ai.vectorstore.observation.VectorStoreObservationContext.Builder createObservationContextBuilder(
+			String operationName) {
+
+		return VectorStoreObservationContext.builder(VectorStoreProvider.MILVUS.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withCollectionName(this.config.collectionName)
+			.withIndexName(this.config.indexType.name())
+			.withSimilarityMetric(getSimilarityMetric())
+			.withNamespace(this.config.databaseName);
+	}
+
+	private static Map<MetricType, VectorStoreSimilarityMetric> SIMILARITY_TYPE_MAPPING = Map.of(MetricType.COSINE,
+			VectorStoreSimilarityMetric.COSINE, MetricType.L2, VectorStoreSimilarityMetric.EUCLIDEAN, MetricType.IP,
+			VectorStoreSimilarityMetric.DOT);
+
+	private String getSimilarityMetric() {
+		if (!SIMILARITY_TYPE_MAPPING.containsKey(this.config.metricType)) {
+			return this.config.metricType.name();
+		}
+		return SIMILARITY_TYPE_MAPPING.get(this.config.metricType).value();
+	}
+
 }

vector-stores/spring-ai-milvus-store/src/test/java/org/springframework/ai/vectorstore/MilvusVectorStoreObservationIT.java

@@ -0,0 +1,179 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
+import org.springframework.ai.openai.api.OpenAiApi;
+import org.springframework.ai.vectorstore.MilvusVectorStore.MilvusVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+import org.testcontainers.milvus.MilvusContainer;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+import io.milvus.client.MilvusServiceClient;
+import io.milvus.param.ConnectParam;
+import io.milvus.param.IndexType;
+import io.milvus.param.MetricType;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+public class MilvusVectorStoreObservationIT {
+
+	@Container
+	private static MilvusContainer milvusContainer = new MilvusContainer("milvusdb/milvus:v2.3.8");
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store milvus add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.MILVUS.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "test_vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "default")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store milvus query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.MILVUS.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "test_vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "default")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public VectorStore vectorStore(MilvusServiceClient milvusClient, EmbeddingModel embeddingModel,
+				ObservationRegistry observationRegistry) {
+			MilvusVectorStoreConfig config = MilvusVectorStoreConfig.builder()
+				.withCollectionName("test_vector_store")
+				.withDatabaseName("default")
+				.withIndexType(IndexType.IVF_FLAT)
+				.withMetricType(MetricType.COSINE)
+				.build();
+			return new MilvusVectorStore(milvusClient, embeddingModel, config, true, observationRegistry, null);
+		}
+
+		@Bean
+		public MilvusServiceClient milvusClient() {
+			return new MilvusServiceClient(ConnectParam.newBuilder()
+				.withAuthorization("minioadmin", "minioadmin")
+				.withUri(milvusContainer.getEndpoint())
+				.build());
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new OpenAiEmbeddingModel(new OpenAiApi(System.getenv("OPENAI_API_KEY")));
+		}
+
+	}
+
+}

vector-stores/spring-ai-mongodb-atlas-store/pom.xml

@@ -54,5 +54,11 @@
             <artifactId>junit-jupiter</artifactId>
             <scope>test</scope>
         </dependency>
+
+        <dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
     </dependencies>
 </project>

vector-stores/spring-ai-mongodb-atlas-store/src/main/java/org/springframework/ai/vectorstore/MongoDBAtlasVectorStore.java

@@ -15,16 +15,21 @@
  */
 package org.springframework.ai.vectorstore;
 
+import static org.springframework.data.mongodb.core.query.Criteria.where;
+
 import java.util.ArrayList;
 import java.util.Collections;
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
 
-import com.mongodb.MongoCommandException;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.model.EmbeddingUtils;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.InitializingBean;
 import org.springframework.data.mongodb.UncategorizedMongoDbException;
 import org.springframework.data.mongodb.core.MongoTemplate;
@@ -33,14 +38,17 @@ import org.springframework.data.mongodb.core.query.Criteria;
 import org.springframework.data.mongodb.core.query.Query;
 import org.springframework.util.Assert;
 
-import static org.springframework.data.mongodb.core.query.Criteria.where;
+import com.mongodb.MongoCommandException;
+
+import io.micrometer.observation.ObservationRegistry;
 
 /**
  * @author Chris Smith
  * @author Soby Chacko
+ * @author Christian Tzolov
  * @since 1.0.0
  */
-public class MongoDBAtlasVectorStore implements VectorStore, InitializingBean {
+public class MongoDBAtlasVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	public static final String ID_FIELD_NAME = "_id";
 
@@ -79,6 +87,15 @@ public class MongoDBAtlasVectorStore implements VectorStore, InitializingBean {
 
 	public MongoDBAtlasVectorStore(MongoTemplate mongoTemplate, EmbeddingModel embeddingModel,
 			MongoDBVectorStoreConfig config, boolean initializeSchema) {
+		this(mongoTemplate, embeddingModel, config, initializeSchema, ObservationRegistry.NOOP, null);
+	}
+
+	public MongoDBAtlasVectorStore(MongoTemplate mongoTemplate, EmbeddingModel embeddingModel,
+			MongoDBVectorStoreConfig config, boolean initializeSchema, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		this.mongoTemplate = mongoTemplate;
 		this.embeddingModel = embeddingModel;
 		this.config = config;
@@ -156,7 +173,7 @@ public class MongoDBAtlasVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		for (Document document : documents) {
 			float[] embedding = this.embeddingModel.embed(document);
 			document.setEmbedding(embedding);
@@ -165,7 +182,7 @@ public class MongoDBAtlasVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 		Query query = new Query(where(ID_FIELD_NAME).in(idList));
 
 		var deleteRes = this.mongoTemplate.remove(query, this.config.collectionName);
@@ -180,7 +197,7 @@ public class MongoDBAtlasVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 
 		String nativeFilterExpressions = (request.getFilterExpression() != null)
 				? this.filterExpressionConverter.convertExpression(request.getFilterExpression()) : "";
@@ -299,4 +316,14 @@ public class MongoDBAtlasVectorStore implements VectorStore, InitializingBean {
 
 	}
 
+	@Override
+	public VectorStoreObservationContext.Builder createObservationContextBuilder(String operationName) {
+
+		return VectorStoreObservationContext.builder(VectorStoreProvider.MONGODB.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withCollectionName(this.config.collectionName)
+			.withFieldName(this.config.pathName)
+			.withIndexName(this.config.vectorIndexName);
+	}
+
 }

vector-stores/spring-ai-mongodb-atlas-store/src/test/java/org/springframework/ai/vectorstore/MongoDBAtlasVectorStoreIT.java

@@ -44,7 +44,7 @@ import static org.assertj.core.api.Assertions.assertThat;
  * @author Chris Smith
  */
 @Testcontainers
-@Disabled("Disabled due to https://github.com/spring-projects/spring-ai/issues/698")
+// @Disabled("Disabled due to https://github.com/spring-projects/spring-ai/issues/698")
 class MongoDBAtlasVectorStoreIT {
 
 	@Container

vector-stores/spring-ai-mongodb-atlas-store/src/test/java/org/springframework/ai/vectorstore/MongoDbVectorStoreObservationIT.java

@@ -0,0 +1,187 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+import java.util.Vector;
+
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
+import org.springframework.ai.openai.api.OpenAiApi;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.springframework.data.mongodb.core.MongoTemplate;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+
+import com.mongodb.client.MongoClient;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
+public class MongoDbVectorStoreObservationIT {
+
+	@Container
+	private static MongoDBAtlasContainer container = new MongoDBAtlasContainer();
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class)
+		.withPropertyValues("spring.data.mongodb.database=springaisample",
+				String.format("spring.data.mongodb.uri=" + container.getConnectionString()));
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	@BeforeEach
+	public void beforeEach() {
+		contextRunner.run(context -> {
+			MongoTemplate mongoTemplate = context.getBean(MongoTemplate.class);
+			mongoTemplate.getCollection("vector_store").deleteMany(new org.bson.Document());
+		});
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store mongodb add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.MONGODB.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "embedding")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.INDEX_NAME.asString(), "vector_index")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store mongodb query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.MONGODB.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "embedding")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.INDEX_NAME.asString(), "vector_index")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public VectorStore vectorStore(MongoTemplate mongoTemplate, EmbeddingModel embeddingModel,
+				ObservationRegistry observationRegistry) {
+			return new MongoDBAtlasVectorStore(mongoTemplate, embeddingModel,
+					MongoDBAtlasVectorStore.MongoDBVectorStoreConfig.builder()
+						.withMetadataFieldsToFilter(List.of("country", "year"))
+						.build(),
+					true, observationRegistry, null);
+		}
+
+		@Bean
+		public MongoTemplate mongoTemplate(MongoClient mongoClient) {
+			return new MongoTemplate(mongoClient, "springaisample");
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new OpenAiEmbeddingModel(new OpenAiApi(System.getenv("OPENAI_API_KEY")));
+		}
+
+	}
+
+}

vector-stores/spring-ai-neo4j-store/pom.xml

@@ -75,6 +75,18 @@
 			<scope>test</scope>
 		</dependency>
 
+		<dependency>
+			<groupId>org.springframework.ai</groupId>
+			<artifactId>spring-ai-test</artifactId>
+			<version>${project.parent.version}</version>
+			<scope>test</scope>
+		</dependency>
+		
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
 
 	</dependencies>
 

vector-stores/spring-ai-neo4j-store/src/main/java/org/springframework/ai/vectorstore/Neo4jVectorStore.java

@@ -27,15 +27,23 @@ import org.neo4j.driver.SessionConfig;
 import org.neo4j.driver.Values;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.vectorstore.filter.Neo4jVectorFilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.InitializingBean;
 import org.springframework.util.Assert;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * @author Gerrit Meier
  * @author Michael Simons
+ * @author Christian Tzolov
  */
-public class Neo4jVectorStore implements VectorStore, InitializingBean {
+public class Neo4jVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	/**
 	 * An enum to configure the distance function used in the Neo4j vector index.
@@ -277,6 +285,15 @@ public class Neo4jVectorStore implements VectorStore, InitializingBean {
 
 	public Neo4jVectorStore(Driver driver, EmbeddingModel embeddingModel, Neo4jVectorStoreConfig config,
 			boolean initializeSchema) {
+		this(driver, embeddingModel, config, initializeSchema, ObservationRegistry.NOOP, null);
+	}
+
+	public Neo4jVectorStore(Driver driver, EmbeddingModel embeddingModel, Neo4jVectorStoreConfig config,
+			boolean initializeSchema, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		this.initializeSchema = initializeSchema;
 
 		Assert.notNull(driver, "Neo4j driver must not be null");
@@ -289,7 +306,7 @@ public class Neo4jVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 
 		var rows = documents.stream().map(this::documentToRecord).toList();
 
@@ -311,7 +328,7 @@ public class Neo4jVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 
 		try (var session = this.driver.session(this.config.sessionConfig)) {
 
@@ -327,7 +344,7 @@ public class Neo4jVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 		Assert.isTrue(request.getTopK() > 0, "The number of documents to returned must be greater than zero");
 		Assert.isTrue(request.getSimilarityThreshold() >= 0 && request.getSimilarityThreshold() <= 1,
 				"The similarity score is bounded between 0 and 1; least to most similar respectively.");
@@ -412,4 +429,24 @@ public class Neo4jVectorStore implements VectorStore, InitializingBean {
 				Map.copyOf(metaData));
 	}
 
+	@Override
+	public VectorStoreObservationContext.Builder createObservationContextBuilder(String operationName) {
+
+		return VectorStoreObservationContext.builder(VectorStoreProvider.NEO4J.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withIndexName(this.config.indexName)
+			.withSimilarityMetric(getSimilarityMetric());
+	}
+
+	private static Map<Neo4jDistanceType, VectorStoreSimilarityMetric> SIMILARITY_TYPE_MAPPING = Map.of(
+			Neo4jDistanceType.COSINE, VectorStoreSimilarityMetric.COSINE, Neo4jDistanceType.EUCLIDEAN,
+			VectorStoreSimilarityMetric.EUCLIDEAN);
+
+	private String getSimilarityMetric() {
+		if (!SIMILARITY_TYPE_MAPPING.containsKey(this.config.distanceType)) {
+			return this.config.distanceType.name();
+		}
+		return SIMILARITY_TYPE_MAPPING.get(this.config.distanceType).value();
+	}
+
 }

vector-stores/spring-ai-neo4j-store/src/test/java/org/springframework/ai/vectorstore/Neo4jVectorStoreObservationIT.java

@@ -0,0 +1,183 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.neo4j.driver.AuthTokens;
+import org.neo4j.driver.Driver;
+import org.neo4j.driver.GraphDatabase;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
+import org.springframework.ai.openai.api.OpenAiApi;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.testcontainers.containers.Neo4jContainer;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+import org.testcontainers.utility.DockerImageName;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
+public class Neo4jVectorStoreObservationIT {
+
+	@Container
+	static Neo4jContainer<?> neo4jContainer = new Neo4jContainer<>(DockerImageName.parse("neo4j:5.18"))
+		.withRandomPassword();
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	@BeforeEach
+	void cleanDatabase() {
+		this.contextRunner
+			.run(context -> context.getBean(Driver.class).executableQuery("MATCH (n) DETACH DELETE n").execute());
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store neo4j add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.NEO4J.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store neo4j query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.NEO4J.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration(exclude = { DataSourceAutoConfiguration.class })
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public VectorStore vectorStore(Driver driver, EmbeddingModel embeddingModel,
+				ObservationRegistry observationRegistry) {
+
+			return new Neo4jVectorStore(driver, embeddingModel, Neo4jVectorStore.Neo4jVectorStoreConfig.defaultConfig(),
+					true, observationRegistry, null);
+		}
+
+		@Bean
+		public Driver driver() {
+			return GraphDatabase.driver(neo4jContainer.getBoltUrl(),
+					AuthTokens.basic("neo4j", neo4jContainer.getAdminPassword()));
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new OpenAiEmbeddingModel(new OpenAiApi(System.getenv("OPENAI_API_KEY")));
+		}
+
+	}
+
+}

vector-stores/spring-ai-opensearch-store/pom.xml

@@ -80,6 +80,12 @@
 			<scope>test</scope>
 		</dependency>
 
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
+		
 	</dependencies>
 
 </project>

vector-stores/spring-ai-opensearch-store/src/main/java/org/springframework/ai/vectorstore/OpenSearchVectorStore.java

@@ -31,11 +31,19 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.vectorstore.filter.Filter;
 import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext.Builder;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.InitializingBean;
 import org.springframework.util.Assert;
 
+import io.micrometer.observation.ObservationRegistry;
+
 import java.io.IOException;
 import java.io.StringReader;
 import java.util.List;
@@ -46,9 +54,10 @@ import java.util.stream.Collectors;
 /**
  * @author Jemin Huh
  * @author Soby Chacko
+ * @author Christian Tzolov
  * @since 1.0.0
  */
-public class OpenSearchVectorStore implements VectorStore, InitializingBean {
+public class OpenSearchVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	public static final String COSINE_SIMILARITY_FUNCTION = "cosinesimil";
 
@@ -94,6 +103,15 @@ public class OpenSearchVectorStore implements VectorStore, InitializingBean {
 
 	public OpenSearchVectorStore(String index, OpenSearchClient openSearchClient, EmbeddingModel embeddingModel,
 			String mappingJson, boolean initializeSchema) {
+		this(index, openSearchClient, embeddingModel, mappingJson, initializeSchema, ObservationRegistry.NOOP, null);
+	}
+
+	public OpenSearchVectorStore(String index, OpenSearchClient openSearchClient, EmbeddingModel embeddingModel,
+			String mappingJson, boolean initializeSchema, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		Objects.requireNonNull(embeddingModel, "RestClient must not be null");
 		Objects.requireNonNull(embeddingModel, "EmbeddingModel must not be null");
 		this.openSearchClient = openSearchClient;
@@ -113,7 +131,7 @@ public class OpenSearchVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		BulkRequest.Builder bulkRequestBuilder = new BulkRequest.Builder();
 		for (Document document : documents) {
 			if (Objects.isNull(document.getEmbedding()) || document.getEmbedding().length == 0) {
@@ -127,7 +145,7 @@ public class OpenSearchVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 		BulkRequest.Builder bulkRequestBuilder = new BulkRequest.Builder();
 		for (String id : idList)
 			bulkRequestBuilder.operations(op -> op.delete(idx -> idx.index(this.index).id(id)));
@@ -144,7 +162,7 @@ public class OpenSearchVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest searchRequest) {
+	public List<Document> doSimilaritySearch(SearchRequest searchRequest) {
 		Assert.notNull(searchRequest, "The search request must not be null.");
 		return similaritySearch(this.embeddingModel.embed(searchRequest.getQuery()), searchRequest.getTopK(),
 				searchRequest.getSimilarityThreshold(), searchRequest.getFilterExpression());
@@ -240,4 +258,23 @@ public class OpenSearchVectorStore implements VectorStore, InitializingBean {
 		}
 	}
 
+	@Override
+	public Builder createObservationContextBuilder(String operationName) {
+		return VectorStoreObservationContext.builder(VectorStoreProvider.OPENSEARCH.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withSimilarityMetric(getSimilarityFunction())
+			.withIndexName(this.index);
+	}
+
+	private String getSimilarityFunction() {
+		if ("cosinesimil".equalsIgnoreCase(this.similarityFunction)) {
+			return VectorStoreSimilarityMetric.COSINE.value();
+		}
+		else if ("l2".equalsIgnoreCase(this.similarityFunction)) {
+			return VectorStoreSimilarityMetric.EUCLIDEAN.value();
+		}
+
+		return this.similarityFunction;
+	}
+
 }

vector-stores/spring-ai-opensearch-store/src/test/java/org/springframework/ai/vectorstore/OpenSearchVectorStoreObservationIT.java

@@ -0,0 +1,215 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.net.URISyntaxException;
+import java.nio.charset.StandardCharsets;
+import java.time.Duration;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.TimeUnit;
+
+import org.apache.hc.core5.http.HttpHost;
+import org.awaitility.Awaitility;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.opensearch.client.opensearch.OpenSearchClient;
+import org.opensearch.client.transport.httpclient5.ApacheHttpClient5TransportBuilder;
+import org.opensearch.testcontainers.OpensearchContainer;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
+import org.springframework.ai.openai.api.OpenAiApi;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+import org.testcontainers.utility.DockerImageName;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+import static org.hamcrest.Matchers.hasSize;
+
+/**
+ * @author Christian Tzolov
+ */
+@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
+@Testcontainers
+public class OpenSearchVectorStoreObservationIT {
+
+	@Container
+	private static final OpensearchContainer<?> opensearchContainer = new OpensearchContainer<>(
+			DockerImageName.parse("opensearchproject/opensearch:2.13.0"));
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	private ApplicationContextRunner getContextRunner() {
+		return new ApplicationContextRunner().withUserConfiguration(Config.class);
+	}
+
+	@BeforeAll
+	public static void beforeAll() {
+		Awaitility.setDefaultPollInterval(2, TimeUnit.SECONDS);
+		Awaitility.setDefaultPollDelay(Duration.ZERO);
+		Awaitility.setDefaultTimeout(Duration.ofMinutes(1));
+	}
+
+	@BeforeEach
+	void cleanDatabase() {
+		getContextRunner().run(context -> {
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+			vectorStore.delete(List.of("_all"));
+		});
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		getContextRunner().run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store opensearch add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.OPENSEARCH.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			Awaitility.await()
+				.until(() -> vectorStore
+					.similaritySearch(SearchRequest.query("Great Depression").withTopK(1).withSimilarityThreshold(0)),
+						hasSize(1));
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store opensearch query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.OPENSEARCH.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			vectorStore.delete(documents.stream().map(Document::getId).toList());
+
+			Awaitility.await()
+				.until(() -> vectorStore
+					.similaritySearch(SearchRequest.query("Great Depression").withTopK(1).withSimilarityThreshold(0)),
+						hasSize(0));
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration(exclude = { DataSourceAutoConfiguration.class })
+	static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public OpenSearchVectorStore vectorStore(EmbeddingModel embeddingModel,
+				ObservationRegistry observationRegistry) {
+			try {
+				return new OpenSearchVectorStore(OpenSearchVectorStore.DEFAULT_INDEX_NAME,
+						new OpenSearchClient(ApacheHttpClient5TransportBuilder
+							.builder(HttpHost.create(opensearchContainer.getHttpHostAddress()))
+							.build()),
+						embeddingModel, OpenSearchVectorStore.DEFAULT_MAPPING_EMBEDDING_TYPE_KNN_VECTOR_DIMENSION_1536,
+						true, observationRegistry, null);
+			}
+			catch (URISyntaxException e) {
+				throw new RuntimeException(e);
+			}
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new OpenAiEmbeddingModel(new OpenAiApi(System.getenv("OPENAI_API_KEY")));
+		}
+
+	}
+
+}

vector-stores/spring-ai-oracle-store/pom.xml

@@ -95,7 +95,11 @@
 			<artifactId>junit-jupiter</artifactId>
 			<scope>test</scope>
 		</dependency>
-
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
 	</dependencies>
 
 </project>

vector-stores/spring-ai-oracle-store/src/main/java/org/springframework/ai/vectorstore/OracleVectorStore.java

@@ -15,22 +15,8 @@
  */
 package org.springframework.ai.vectorstore;
 
-import oracle.jdbc.OracleType;
-import oracle.sql.VECTOR;
-import oracle.sql.json.OracleJsonFactory;
-import oracle.sql.json.OracleJsonGenerator;
-import oracle.sql.json.OracleJsonObject;
-import oracle.sql.json.OracleJsonValue;
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
-import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.EmbeddingModel;
-import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
-import org.springframework.beans.factory.InitializingBean;
-import org.springframework.jdbc.core.BatchPreparedStatementSetter;
-import org.springframework.jdbc.core.JdbcTemplate;
-import org.springframework.jdbc.core.RowMapper;
-import org.springframework.util.StringUtils;
+import static org.springframework.ai.vectorstore.OracleVectorStore.OracleVectorStoreDistanceType.DOT;
+import static org.springframework.jdbc.core.StatementCreatorUtils.setParameterValue;
 
 import java.io.ByteArrayOutputStream;
 import java.sql.PreparedStatement;
@@ -44,8 +30,30 @@ import java.util.List;
 import java.util.Map;
 import java.util.Optional;
 
-import static org.springframework.ai.vectorstore.OracleVectorStore.OracleVectorStoreDistanceType.DOT;
-import static org.springframework.jdbc.core.StatementCreatorUtils.setParameterValue;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
+import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext.Builder;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.beans.factory.InitializingBean;
+import org.springframework.jdbc.core.BatchPreparedStatementSetter;
+import org.springframework.jdbc.core.JdbcTemplate;
+import org.springframework.jdbc.core.RowMapper;
+import org.springframework.util.StringUtils;
+
+import io.micrometer.observation.ObservationRegistry;
+import oracle.jdbc.OracleType;
+import oracle.sql.VECTOR;
+import oracle.sql.json.OracleJsonFactory;
+import oracle.sql.json.OracleJsonGenerator;
+import oracle.sql.json.OracleJsonObject;
+import oracle.sql.json.OracleJsonValue;
 
 /**
  * <p>
@@ -69,8 +77,9 @@ import static org.springframework.jdbc.core.StatementCreatorUtils.setParameterVa
  * </ul>
  *
  * @author Loïc Lefèvre
+ * @author Christian Tzolov
  */
-public class OracleVectorStore implements VectorStore, InitializingBean {
+public class OracleVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	private static final Logger logger = LoggerFactory.getLogger(OracleVectorStore.class);
 
@@ -126,7 +135,7 @@ public class OracleVectorStore implements VectorStore, InitializingBean {
 	public enum OracleVectorStoreDistanceType {
 
 		/**
-		 * Default metric. It calculates the cosine distane between two vectors.
+		 * Default metric. It calculates the cosine distance between two vectors.
 		 */
 		COSINE,
 
@@ -220,6 +229,18 @@ public class OracleVectorStore implements VectorStore, InitializingBean {
 			OracleVectorStoreIndexType indexType, OracleVectorStoreDistanceType distanceType, int dimensions,
 			int searchAccuracy, boolean initializeSchema, boolean removeExistingVectorStoreTable,
 			boolean forcedNormalization) {
+		this(jdbcTemplate, embeddingModel, tableName, indexType, distanceType, dimensions, searchAccuracy,
+				initializeSchema, removeExistingVectorStoreTable, forcedNormalization, ObservationRegistry.NOOP, null);
+	}
+
+	public OracleVectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel, String tableName,
+			OracleVectorStoreIndexType indexType, OracleVectorStoreDistanceType distanceType, int dimensions,
+			int searchAccuracy, boolean initializeSchema, boolean removeExistingVectorStoreTable,
+			boolean forcedNormalization, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		if (dimensions != DEFAULT_DIMENSIONS) {
 			if (dimensions <= 0) {
 				throw new RuntimeException("Number of dimensions must be strictly positive");
@@ -251,7 +272,7 @@ public class OracleVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(final List<Document> documents) {
+	public void doAdd(final List<Document> documents) {
 		this.jdbcTemplate.batchUpdate(getIngestStatement(), new BatchPreparedStatementSetter() {
 			@Override
 			public void setValues(PreparedStatement ps, int i) throws SQLException {
@@ -366,7 +387,7 @@ public class OracleVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(final List<String> idList) {
+	public Optional<Boolean> doDelete(final List<String> idList) {
 		final String sql = String.format("delete from %s where id=?", tableName);
 		final int[] argTypes = { Types.VARCHAR };
 
@@ -429,7 +450,7 @@ public class OracleVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 		try {
 			// From the provided query, generate a vector using the embedding model
 			final VECTOR embeddingVector = toVECTOR(embeddingModel.embed(request.getQuery()));
@@ -599,4 +620,24 @@ public class OracleVectorStore implements VectorStore, InitializingBean {
 		return tableName;
 	}
 
+	@Override
+	public Builder createObservationContextBuilder(String operationName) {
+		return VectorStoreObservationContext.builder(VectorStoreProvider.ORACLE.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withCollectionName(this.getTableName())
+			.withFieldName(getSimilarityMetric());
+	}
+
+	private static Map<OracleVectorStoreDistanceType, VectorStoreSimilarityMetric> SIMILARITY_TYPE_MAPPING = Map.of(
+			OracleVectorStoreDistanceType.COSINE, VectorStoreSimilarityMetric.COSINE,
+			OracleVectorStoreDistanceType.EUCLIDEAN, VectorStoreSimilarityMetric.EUCLIDEAN,
+			OracleVectorStoreDistanceType.DOT, VectorStoreSimilarityMetric.DOT);
+
+	private String getSimilarityMetric() {
+		if (!SIMILARITY_TYPE_MAPPING.containsKey(this.distanceType)) {
+			return this.distanceType.name();
+		}
+		return SIMILARITY_TYPE_MAPPING.get(this.distanceType).value();
+	}
+
 }

vector-stores/spring-ai-oracle-store/src/test/java/org/springframework/ai/vectorstore/OracleVectorStoreObservationIT.java

@@ -0,0 +1,206 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+
+import javax.sql.DataSource;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.transformers.TransformersEmbeddingModel;
+import org.springframework.ai.vectorstore.OracleVectorStore.OracleVectorStoreDistanceType;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
+import org.springframework.boot.autoconfigure.jdbc.DataSourceProperties;
+import org.springframework.boot.context.properties.ConfigurationProperties;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.ApplicationContext;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Primary;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.springframework.jdbc.core.JdbcTemplate;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+import org.testcontainers.oracle.OracleContainer;
+import org.testcontainers.utility.MountableFile;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+import oracle.jdbc.pool.OracleDataSource;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+public class OracleVectorStoreObservationIT {
+
+	@Container
+	static OracleContainer oracle23aiContainer = new OracleContainer("gvenzl/oracle-free:23-slim")
+		.withCopyFileToContainer(MountableFile.forClasspathResource("/initialize.sql"),
+				"/container-entrypoint-initdb.d/initialize.sql");
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class)
+		.withPropertyValues("test.spring.ai.vectorstore.oracle.dimensions=384",
+				// JdbcTemplate configuration
+				String.format("app.datasource.url=%s", oracle23aiContainer.getJdbcUrl()),
+				String.format("app.datasource.username=%s", oracle23aiContainer.getUsername()),
+				String.format("app.datasource.password=%s", oracle23aiContainer.getPassword()),
+				"app.datasource.type=oracle.jdbc.pool.OracleDataSource");
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	private static void dropTable(ApplicationContext context, String tableName) {
+		JdbcTemplate jdbcTemplate = context.getBean(JdbcTemplate.class);
+		jdbcTemplate.execute("DROP TABLE IF EXISTS " + tableName + " PURGE");
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store oracle add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.ORACLE.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(),
+						OracleVectorStore.DEFAULT_TABLE_NAME)
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "cosine")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store oracle query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.ORACLE.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(),
+						OracleVectorStore.DEFAULT_TABLE_NAME)
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			dropTable(context, ((OracleVectorStore) vectorStore).getTableName());
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration(exclude = { DataSourceAutoConfiguration.class })
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public VectorStore vectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel,
+				ObservationRegistry observationRegistry) {
+			return new OracleVectorStore(jdbcTemplate, embeddingModel, OracleVectorStore.DEFAULT_TABLE_NAME,
+					OracleVectorStore.OracleVectorStoreIndexType.IVF, OracleVectorStoreDistanceType.COSINE, 384,
+					OracleVectorStore.DEFAULT_SEARCH_ACCURACY, true, true, true, observationRegistry, null);
+		}
+
+		@Bean
+		public JdbcTemplate myJdbcTemplate(DataSource dataSource) {
+			return new JdbcTemplate(dataSource);
+		}
+
+		@Bean
+		@Primary
+		@ConfigurationProperties("app.datasource")
+		public DataSourceProperties dataSourceProperties() {
+			return new DataSourceProperties();
+		}
+
+		@Bean
+		public OracleDataSource dataSource(DataSourceProperties dataSourceProperties) {
+			return dataSourceProperties.initializeDataSourceBuilder().type(OracleDataSource.class).build();
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new TransformersEmbeddingModel();
+		}
+
+	}
+
+}

vector-stores/spring-ai-pgvector-store/src/main/java/org/springframework/ai/vectorstore/PgVectorStore.java

@@ -139,10 +139,9 @@ public class PgVectorStore extends AbstractObservationVectorStore implements Ini
 	private PgVectorStore(String schemaName, String vectorTableName, boolean vectorTableValidationsEnabled,
 			JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel, int dimensions, PgDistanceType distanceType,
 			boolean removeExistingVectorStoreTable, PgIndexType createIndexMethod, boolean initializeSchema,
-			ObservationRegistry observationRegistry,
-			VectorStoreObservationConvention customSearchObservationConvention) {
+			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention) {
 
-		super(observationRegistry, customSearchObservationConvention);
+		super(observationRegistry, customObservationConvention);
 
 		this.vectorTableName = (null == vectorTableName || vectorTableName.isEmpty()) ? DEFAULT_TABLE_NAME
 				: vectorTableName.trim();
@@ -554,9 +553,8 @@ public class PgVectorStore extends AbstractObservationVectorStore implements Ini
 			return this;
 		}
 
-		public Builder withSearchObservationConvention(
-				VectorStoreObservationConvention customSearchObservationConvention) {
-			this.searchObservationConvention = customSearchObservationConvention;
+		public Builder withSearchObservationConvention(VectorStoreObservationConvention customObservationConvention) {
+			this.searchObservationConvention = customObservationConvention;
 			return this;
 		}
 

vector-stores/spring-ai-pgvector-store/src/test/java/org/springframework/ai/vectorstore/PgVectorObservationIT.java

@@ -122,6 +122,7 @@ public class PgVectorObservationIT {
 				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
 				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
 				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
 
 				.hasBeenStarted()
 				.hasBeenStopped();
@@ -149,6 +150,7 @@ public class PgVectorObservationIT {
 				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
 				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
 				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
 
 				.hasBeenStarted()
 				.hasBeenStopped();

vector-stores/spring-ai-pinecone-store/pom.xml

@@ -101,6 +101,11 @@
             <scope>test</scope>
         </dependency>
 
+        <dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
     </dependencies>
 
 </project>

vector-stores/spring-ai-pinecone-store/src/main/java/org/springframework/ai/vectorstore/PineconeVectorStore.java

@@ -21,11 +21,25 @@ import java.util.List;
 import java.util.Map;
 import java.util.Optional;
 
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.model.EmbeddingUtils;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
+import org.springframework.ai.vectorstore.filter.converter.PineconeFilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.util.Assert;
+import org.springframework.util.StringUtils;
+
 import com.fasterxml.jackson.core.type.TypeReference;
 import com.fasterxml.jackson.databind.ObjectMapper;
 import com.google.protobuf.Struct;
 import com.google.protobuf.Value;
 import com.google.protobuf.util.JsonFormat;
+
+import io.micrometer.observation.ObservationRegistry;
 import io.pinecone.PineconeClient;
 import io.pinecone.PineconeClientConfig;
 import io.pinecone.PineconeConnection;
@@ -36,14 +50,6 @@ import io.pinecone.proto.QueryResponse;
 import io.pinecone.proto.UpsertRequest;
 import io.pinecone.proto.Vector;
 
-import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.EmbeddingModel;
-import org.springframework.ai.model.EmbeddingUtils;
-import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
-import org.springframework.ai.vectorstore.filter.converter.PineconeFilterExpressionConverter;
-import org.springframework.util.Assert;
-import org.springframework.util.StringUtils;
-
 /**
  * A VectorStore implementation backed by Pinecone, a cloud-based vector database. This
  * store supports creating, updating, deleting, and similarity searching of documents in a
@@ -52,7 +58,7 @@ import org.springframework.util.StringUtils;
  * @author Christian Tzolov
  * @author Adam Bchouti
  */
-public class PineconeVectorStore implements VectorStore {
+public class PineconeVectorStore extends AbstractObservationVectorStore {
 
 	public static final String CONTENT_FIELD_NAME = "document_content";
 
@@ -252,6 +258,19 @@ public class PineconeVectorStore implements VectorStore {
 	 * @param embeddingModel The client for embedding operations.
 	 */
 	public PineconeVectorStore(PineconeVectorStoreConfig config, EmbeddingModel embeddingModel) {
+		this(config, embeddingModel, ObservationRegistry.NOOP, null);
+	}
+
+	/**
+	 * Constructs a new PineconeVectorStore.
+	 * @param config The configuration for the store.
+	 * @param embeddingModel The client for embedding operations.
+	 * @param observationRegistry The registry for observations.
+	 * @param customObservationConvention The custom observation convention.
+	 */
+	public PineconeVectorStore(PineconeVectorStoreConfig config, EmbeddingModel embeddingModel,
+			ObservationRegistry observationRegistry, VectorStoreObservationConvention customObservationConvention) {
+		super(observationRegistry, customObservationConvention);
 		Assert.notNull(config, "PineconeVectorStoreConfig must not be null");
 		Assert.notNull(embeddingModel, "EmbeddingModel must not be null");
 
@@ -294,7 +313,7 @@ public class PineconeVectorStore implements VectorStore {
 	 * @param documents The list of documents to be added.
 	 */
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		add(documents, this.pineconeNamespace);
 	}
 
@@ -352,7 +371,7 @@ public class PineconeVectorStore implements VectorStore {
 	 * @return An optional boolean indicating the deletion status.
 	 */
 	@Override
-	public Optional<Boolean> delete(List<String> documentIds) {
+	public Optional<Boolean> doDelete(List<String> documentIds) {
 		return delete(documentIds, this.pineconeNamespace);
 	}
 
@@ -390,7 +409,7 @@ public class PineconeVectorStore implements VectorStore {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 		return similaritySearch(request, this.pineconeNamespace);
 	}
 
@@ -424,4 +443,13 @@ public class PineconeVectorStore implements VectorStore {
 		}
 	}
 
+	@Override
+	public VectorStoreObservationContext.Builder createObservationContextBuilder(String operationName) {
+
+		return VectorStoreObservationContext.builder(VectorStoreProvider.PINECONE.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withNamespace(this.pineconeNamespace)
+			.withFieldName(this.pineconeContentFieldName);
+	}
+
 }

vector-stores/spring-ai-pinecone-store/src/test/java/org/springframework/ai/vectorstore/PineconeVectorStoreObservationIT.java

@@ -0,0 +1,202 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.hamcrest.Matchers.hasSize;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.TimeUnit;
+
+import org.awaitility.Awaitility;
+import org.awaitility.Duration;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.transformers.TransformersEmbeddingModel;
+import org.springframework.ai.vectorstore.PineconeVectorStore.PineconeVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+/**
+ * @author Christian Tzolov
+ */
+@EnabledIfEnvironmentVariable(named = "PINECONE_API_KEY", matches = ".+")
+public class PineconeVectorStoreObservationIT {
+
+	private static final String PINECONE_ENVIRONMENT = "gcp-starter";
+
+	private static final String PINECONE_PROJECT_ID = "814621f";
+
+	private static final String PINECONE_INDEX_NAME = "spring-ai-test-index";
+
+	// NOTE: Leave it empty as for free tier as later doesn't support namespaces.
+	private static final String PINECONE_NAMESPACE = "";
+
+	private static final String CUSTOM_CONTENT_FIELD_NAME = "article";
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	@BeforeAll
+	public static void beforeAll() {
+		Awaitility.setDefaultPollInterval(2, TimeUnit.SECONDS);
+		Awaitility.setDefaultPollDelay(Duration.ZERO);
+		Awaitility.setDefaultTimeout(Duration.ONE_MINUTE);
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store pinecone add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.PINECONE.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "article")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			Awaitility.await().until(() -> {
+				return vectorStore.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+			}, hasSize(1));
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store pinecone query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.PINECONE.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "article")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			// Remove all documents from the store
+			vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());
+
+			Awaitility.await().until(() -> {
+				return vectorStore.similaritySearch(SearchRequest.query("Hello").withTopK(1));
+			}, hasSize(0));
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public PineconeVectorStoreConfig pineconeVectorStoreConfig() {
+
+			return PineconeVectorStoreConfig.builder()
+				.withApiKey(System.getenv("PINECONE_API_KEY"))
+				.withEnvironment(PINECONE_ENVIRONMENT)
+				.withProjectId(PINECONE_PROJECT_ID)
+				.withIndexName(PINECONE_INDEX_NAME)
+				.withNamespace(PINECONE_NAMESPACE)
+				.withContentFieldName(CUSTOM_CONTENT_FIELD_NAME)
+				.build();
+		}
+
+		@Bean
+		public VectorStore vectorStore(PineconeVectorStoreConfig config, EmbeddingModel embeddingModel,
+				ObservationRegistry observationRegistry) {
+			return new PineconeVectorStore(config, embeddingModel, observationRegistry, null);
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new TransformersEmbeddingModel();
+		}
+
+	}
+
+}

vector-stores/spring-ai-qdrant-store/pom.xml

@@ -75,5 +75,18 @@
             <artifactId>junit-jupiter</artifactId>
             <scope>test</scope>
         </dependency>
+
+        <dependency>
+			<groupId>org.springframework.ai</groupId>
+			<artifactId>spring-ai-test</artifactId>
+			<version>${parent.version}</version>
+			<scope>test</scope>
+		</dependency>
+
+        <dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
     </dependencies>
 </project>

vector-stores/spring-ai-qdrant-store/src/main/java/org/springframework/ai/vectorstore/qdrant/QdrantVectorStore.java

@@ -29,11 +29,16 @@ import java.util.concurrent.ExecutionException;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.model.EmbeddingUtils;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.vectorstore.SearchRequest;
-import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.InitializingBean;
 import org.springframework.util.Assert;
 
+import io.micrometer.observation.ObservationRegistry;
 import io.qdrant.client.QdrantClient;
 import io.qdrant.client.grpc.Collections.Distance;
 import io.qdrant.client.grpc.Collections.VectorParams;
@@ -55,7 +60,7 @@ import io.qdrant.client.grpc.Points.UpdateStatus;
  * @author Josh Long
  * @since 0.8.1
  */
-public class QdrantVectorStore implements VectorStore, InitializingBean {
+public class QdrantVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	private static final String CONTENT_FIELD_NAME = "doc_content";
 
@@ -152,9 +157,28 @@ public class QdrantVectorStore implements VectorStore, InitializingBean {
 	 * @param qdrantClient A {@link QdrantClient} instance for interfacing with Qdrant.
 	 * @param collectionName The name of the collection to use in Qdrant.
 	 * @param embeddingModel The client for embedding operations.
+	 * @param initializeSchema A boolean indicating whether to initialize the schema.
 	 */
 	public QdrantVectorStore(QdrantClient qdrantClient, String collectionName, EmbeddingModel embeddingModel,
 			boolean initializeSchema) {
+		this(qdrantClient, collectionName, embeddingModel, initializeSchema, ObservationRegistry.NOOP, null);
+	}
+
+	/**
+	 * Constructs a new QdrantVectorStore.
+	 * @param qdrantClient A {@link QdrantClient} instance for interfacing with Qdrant.
+	 * @param collectionName The name of the collection to use in Qdrant.
+	 * @param embeddingModel The client for embedding operations.
+	 * @param initializeSchema A boolean indicating whether to initialize the schema.
+	 * @param observationRegistry The observation registry to use.
+	 * @param customObservationConvention The custom search observation convention to use.
+	 */
+	public QdrantVectorStore(QdrantClient qdrantClient, String collectionName, EmbeddingModel embeddingModel,
+			boolean initializeSchema, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		Assert.notNull(qdrantClient, "QdrantClient must not be null");
 		Assert.notNull(collectionName, "collectionName must not be null");
 		Assert.notNull(embeddingModel, "EmbeddingModel must not be null");
@@ -170,7 +194,7 @@ public class QdrantVectorStore implements VectorStore, InitializingBean {
 	 * @param documents The list of documents to be added.
 	 */
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		try {
 			List<PointStruct> points = documents.stream().map(document -> {
 				// Compute and assign an embedding to the document.
@@ -196,7 +220,7 @@ public class QdrantVectorStore implements VectorStore, InitializingBean {
 	 * @return An optional boolean indicating the deletion status.
 	 */
 	@Override
-	public Optional<Boolean> delete(List<String> documentIds) {
+	public Optional<Boolean> doDelete(List<String> documentIds) {
 		try {
 			List<PointId> ids = documentIds.stream().map(id -> id(UUID.fromString(id))).toList();
 			var result = this.qdrantClient.deleteAsync(this.collectionName, ids)
@@ -216,7 +240,7 @@ public class QdrantVectorStore implements VectorStore, InitializingBean {
 	 * @return A list of documents that are similar to the query.
 	 */
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 		try {
 			Filter filter = (request.getFilterExpression() != null)
 					? this.filterExpressionConverter.convertExpression(request.getFilterExpression())
@@ -307,4 +331,13 @@ public class QdrantVectorStore implements VectorStore, InitializingBean {
 		}
 	}
 
+	@Override
+	public VectorStoreObservationContext.Builder createObservationContextBuilder(String operationName) {
+
+		return VectorStoreObservationContext.builder(VectorStoreProvider.QDRANT.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withCollectionName(this.collectionName);
+
+	}
+
 }

vector-stores/spring-ai-qdrant-store/src/test/java/org/springframework/ai/vectorstore/qdrant/QdrantVectorStoreObservationIT.java

@@ -0,0 +1,209 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore.qdrant;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.ExecutionException;
+
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.springframework.ai.azure.openai.AzureOpenAiEmbeddingModel;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+import org.testcontainers.qdrant.QdrantContainer;
+
+import com.azure.ai.openai.OpenAIClient;
+import com.azure.ai.openai.OpenAIClientBuilder;
+import com.azure.core.credential.AzureKeyCredential;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.Distance;
+import io.qdrant.client.grpc.Collections.VectorParams;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+@EnabledIfEnvironmentVariable(named = "AZURE_AI_SEARCH_API_KEY", matches = ".+")
+@EnabledIfEnvironmentVariable(named = "AZURE_AI_SEARCH_ENDPOINT", matches = ".+")
+public class QdrantVectorStoreObservationIT {
+
+	private static final String COLLECTION_NAME = "test_collection";
+
+	private static final int EMBEDDING_DIMENSION = 1536;
+
+	@Container
+	static QdrantContainer qdrantContainer = new QdrantContainer("qdrant/qdrant:v1.9.2");
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	@BeforeAll
+	static void setup() throws InterruptedException, ExecutionException {
+
+		String host = qdrantContainer.getHost();
+		int port = qdrantContainer.getGrpcPort();
+		QdrantClient client = new QdrantClient(QdrantGrpcClient.newBuilder(host, port, false).build());
+
+		client
+			.createCollectionAsync(COLLECTION_NAME,
+					VectorParams.newBuilder().setDistance(Distance.Cosine).setSize(EMBEDDING_DIMENSION).build())
+			.get();
+
+		client.close();
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store qdrant add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.QDRANT.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "test_collection")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store qdrant query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.QDRANT.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "test_collection")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public QdrantClient qdrantClient() {
+			String host = qdrantContainer.getHost();
+			int port = qdrantContainer.getGrpcPort();
+			QdrantClient qdrantClient = new QdrantClient(QdrantGrpcClient.newBuilder(host, port, false).build());
+			return qdrantClient;
+		}
+
+		@Bean
+		public VectorStore qdrantVectorStore(EmbeddingModel embeddingModel, QdrantClient qdrantClient,
+				ObservationRegistry observationRegistry) {
+			return new QdrantVectorStore(qdrantClient, COLLECTION_NAME, embeddingModel, true, observationRegistry,
+					null);
+		}
+
+		@Bean
+		public OpenAIClient openAIClient() {
+			return new OpenAIClientBuilder().credential(new AzureKeyCredential(System.getenv("AZURE_OPENAI_API_KEY")))
+				.endpoint(System.getenv("AZURE_OPENAI_ENDPOINT"))
+				.buildClient();
+		}
+
+		@Bean
+		public AzureOpenAiEmbeddingModel azureEmbeddingModel(OpenAIClient openAIClient) {
+			return new AzureOpenAiEmbeddingModel(openAIClient);
+		}
+
+	}
+
+}

vector-stores/spring-ai-redis-store/pom.xml

@@ -79,6 +79,11 @@
 			<scope>test</scope>
 		</dependency>
 
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
 
 	</dependencies>
 

vector-stores/spring-ai-redis-store/src/main/java/org/springframework/ai/vectorstore/RedisVectorStore.java

@@ -30,10 +30,16 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
 import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.InitializingBean;
 import org.springframework.util.Assert;
 import org.springframework.util.CollectionUtils;
+
+import io.micrometer.observation.ObservationRegistry;
 import redis.clients.jedis.JedisPooled;
 import redis.clients.jedis.Pipeline;
 import redis.clients.jedis.json.Path2;
@@ -72,7 +78,7 @@ import redis.clients.jedis.search.schemafields.VectorField.VectorAlgorithm;
  * @see RedisVectorStoreConfig
  * @see EmbeddingModel
  */
-public class RedisVectorStore implements VectorStore, InitializingBean {
+public class RedisVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	public enum Algorithm {
 
@@ -274,6 +280,15 @@ public class RedisVectorStore implements VectorStore, InitializingBean {
 	public RedisVectorStore(RedisVectorStoreConfig config, EmbeddingModel embeddingModel, JedisPooled jedis,
 			boolean initializeSchema) {
 
+		this(config, embeddingModel, jedis, initializeSchema, ObservationRegistry.NOOP, null);
+	}
+
+	public RedisVectorStore(RedisVectorStoreConfig config, EmbeddingModel embeddingModel, JedisPooled jedis,
+			boolean initializeSchema, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		Assert.notNull(config, "Config must not be null");
 		Assert.notNull(embeddingModel, "Embedding model must not be null");
 		this.initializeSchema = initializeSchema;
@@ -289,7 +304,7 @@ public class RedisVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		try (Pipeline pipeline = this.jedis.pipelined()) {
 			for (Document document : documents) {
 				var embedding = this.embeddingModel.embed(document);
@@ -318,7 +333,7 @@ public class RedisVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 		try (Pipeline pipeline = this.jedis.pipelined()) {
 			for (String id : idList) {
 				pipeline.jsonDel(key(id));
@@ -336,7 +351,7 @@ public class RedisVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 
 		Assert.isTrue(request.getTopK() > 0, "The number of documents to returned must be greater than zero");
 		Assert.isTrue(request.getSimilarityThreshold() >= 0 && request.getSimilarityThreshold() <= 1,
@@ -457,13 +472,15 @@ public class RedisVectorStore implements VectorStore, InitializingBean {
 		return JSON_PATH_PREFIX + field;
 	}
 
-	private static float[] toFloatArray(List<Float> embedding) {
-		float[] embeddingFloat = new float[embedding.size()];
-		int i = 0;
-		for (Float d : embedding) {
-			embeddingFloat[i++] = d.floatValue();
-		}
-		return embeddingFloat;
+	@Override
+	public VectorStoreObservationContext.Builder createObservationContextBuilder(String operationName) {
+
+		return VectorStoreObservationContext.builder(VectorStoreProvider.REDIS.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withFieldName(this.config.embeddingFieldName)
+			.withSimilarityMetric(vectorAlgorithm().name())
+			.withIndexName(this.config.indexName);
+
 	}
 
 }

vector-stores/spring-ai-redis-store/src/test/java/org/springframework/ai/vectorstore/RedisVectorStoreObservationIT.java

@@ -0,0 +1,184 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.transformers.TransformersEmbeddingModel;
+import org.springframework.ai.vectorstore.RedisVectorStore.MetadataField;
+import org.springframework.ai.vectorstore.RedisVectorStore.RedisVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.AutoConfigurations;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.autoconfigure.data.redis.RedisAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.springframework.data.redis.connection.jedis.JedisConnectionFactory;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+
+import com.redis.testcontainers.RedisStackContainer;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+import redis.clients.jedis.JedisPooled;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+public class RedisVectorStoreObservationIT {
+
+	@Container
+	static RedisStackContainer redisContainer = new RedisStackContainer(
+			RedisStackContainer.DEFAULT_IMAGE_NAME.withTag(RedisStackContainer.DEFAULT_TAG));
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withConfiguration(AutoConfigurations.of(RedisAutoConfiguration.class))
+		.withUserConfiguration(Config.class)
+		.withPropertyValues("spring.data.redis.url=" + redisContainer.getRedisURI());
+
+	@BeforeEach
+	void cleanDatabase() {
+		this.contextRunner.run(context -> context.getBean(RedisVectorStore.class).getJedis().flushAll());
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store redis add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.REDIS.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "embedding")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "HNSW")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.INDEX_NAME.asString(), "spring-ai-index")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store redis query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.REDIS.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "embedding")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "HNSW")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.INDEX_NAME.asString(), "spring-ai-index")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public RedisVectorStore vectorStore(EmbeddingModel embeddingModel,
+				JedisConnectionFactory jedisConnectionFactory, ObservationRegistry observationRegistry) {
+			return new RedisVectorStore(
+					RedisVectorStoreConfig.builder()
+						.withMetadataFields(MetadataField.tag("meta1"), MetadataField.tag("meta2"),
+								MetadataField.tag("country"), MetadataField.numeric("year"))
+						.build(),
+					embeddingModel,
+					new JedisPooled(jedisConnectionFactory.getHostName(), jedisConnectionFactory.getPort()), true,
+					observationRegistry, null);
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new TransformersEmbeddingModel();
+		}
+
+	}
+
+}

vector-stores/spring-ai-typesense-store/pom.xml

@@ -62,6 +62,13 @@
             <scope>test</scope>
         </dependency>
 
+
+		<dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
+
     </dependencies>
 
 </project>

vector-stores/spring-ai-typesense-store/src/main/java/org/springframework/ai/vectorstore/TypesenseVectorStore.java

@@ -16,7 +16,6 @@
 
 package org.springframework.ai.vectorstore;
 
-import java.util.Arrays;
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
@@ -28,7 +27,12 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.observation.conventions.VectorStoreSimilarityMetric;
 import org.springframework.ai.vectorstore.filter.FilterExpressionConverter;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
 import org.springframework.beans.factory.InitializingBean;
 import org.springframework.util.Assert;
 import org.typesense.api.Client;
@@ -42,11 +46,14 @@ import org.typesense.model.MultiSearchCollectionParameters;
 import org.typesense.model.MultiSearchResult;
 import org.typesense.model.MultiSearchSearchesParameter;
 
+import io.micrometer.observation.ObservationRegistry;
+
 /**
  * @author Pablo Sanchidrian Herrera
  * @author Soby Chacko
+ * @author Christian Tzolov
  */
-public class TypesenseVectorStore implements VectorStore, InitializingBean {
+public class TypesenseVectorStore extends AbstractObservationVectorStore implements InitializingBean {
 
 	private static final Logger logger = LoggerFactory.getLogger(TypesenseVectorStore.class);
 
@@ -154,6 +161,16 @@ public class TypesenseVectorStore implements VectorStore, InitializingBean {
 
 	public TypesenseVectorStore(Client client, EmbeddingModel embeddingModel, TypesenseVectorStoreConfig config,
 			boolean initializeSchema) {
+
+		this(client, embeddingModel, config, initializeSchema, ObservationRegistry.NOOP, null);
+	}
+
+	public TypesenseVectorStore(Client client, EmbeddingModel embeddingModel, TypesenseVectorStoreConfig config,
+			boolean initializeSchema, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		Assert.notNull(client, "Typesense must not be null");
 		Assert.notNull(embeddingModel, "EmbeddingModel must not be null");
 
@@ -164,7 +181,7 @@ public class TypesenseVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 		Assert.notNull(documents, "Documents must not be null");
 
 		List<HashMap<String, Object>> documentList = documents.stream().map(document -> {
@@ -194,7 +211,7 @@ public class TypesenseVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> idList) {
+	public Optional<Boolean> doDelete(List<String> idList) {
 		DeleteDocumentsParameters deleteDocumentsParameters = new DeleteDocumentsParameters();
 		deleteDocumentsParameters.filterBy(DOC_ID_FIELD_NAME + ":=[" + String.join(",", idList) + "]");
 
@@ -217,7 +234,7 @@ public class TypesenseVectorStore implements VectorStore, InitializingBean {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 		Assert.notNull(request.getQuery(), "Query string must not be null");
 
 		String nativeFilterExpressions = (request.getFilterExpression() != null)
@@ -361,4 +378,14 @@ public class TypesenseVectorStore implements VectorStore, InitializingBean {
 
 	}
 
+	@Override
+	public VectorStoreObservationContext.Builder createObservationContextBuilder(String operationName) {
+
+		return VectorStoreObservationContext.builder(VectorStoreProvider.TYPESENSE.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withCollectionName(this.config.collectionName)
+			.withFieldName(EMBEDDING_FIELD_NAME)
+			.withSimilarityMetric(VectorStoreSimilarityMetric.COSINE.value());
+	}
+
 }

vector-stores/spring-ai-typesense-store/src/test/java/org/springframework/ai/vectorstore/TypesenseVectorStoreObservationIT.java

@@ -0,0 +1,185 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.time.Duration;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.transformers.TransformersEmbeddingModel;
+import org.springframework.ai.vectorstore.TypesenseVectorStore.TypesenseVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.testcontainers.containers.GenericContainer;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+import org.typesense.api.Client;
+import org.typesense.api.Configuration;
+import org.typesense.resources.Node;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+public class TypesenseVectorStoreObservationIT {
+
+	@Container
+	private static GenericContainer<?> typesenseContainer = new GenericContainer<>("typesense/typesense:26.0")
+		.withExposedPorts(8108)
+		.withCommand("--data-dir", "/tmp", "--api-key=xyz", "--enable-cors");
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store typesense add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.TYPESENSE.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "test_vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "embedding")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.INDEX_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store typesense query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.TYPESENSE.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "test_vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "embedding")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.INDEX_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public VectorStore vectorStore(Client client, EmbeddingModel embeddingModel,
+				ObservationRegistry observationRegistry) {
+
+			TypesenseVectorStoreConfig config = TypesenseVectorStoreConfig.builder()
+				.withCollectionName("test_vector_store")
+				.withEmbeddingDimension(embeddingModel.dimensions())
+				.build();
+
+			return new TypesenseVectorStore(client, embeddingModel, config, true, observationRegistry, null);
+		}
+
+		@Bean
+		public Client typesenseClient() {
+			List<Node> nodes = new ArrayList<>();
+			nodes
+				.add(new Node("http", typesenseContainer.getHost(), typesenseContainer.getMappedPort(8108).toString()));
+
+			Configuration configuration = new Configuration(nodes, Duration.ofSeconds(5), "xyz");
+			return new Client(configuration);
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new TransformersEmbeddingModel();
+		}
+
+	}
+
+}

vector-stores/spring-ai-weaviate-store/pom.xml

@@ -80,6 +80,12 @@
             <scope>test</scope>
         </dependency>
 
+        <dependency>
+			<groupId>io.micrometer</groupId>
+			<artifactId>micrometer-observation-test</artifactId>
+			<scope>test</scope>
+		</dependency>
+
     </dependencies>
 
 </project>

vector-stores/spring-ai-weaviate-store/src/main/java/org/springframework/ai/vectorstore/WeaviateVectorStore.java

@@ -23,8 +23,23 @@ import java.util.Map;
 import java.util.Optional;
 import java.util.stream.Collectors;
 
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.model.EmbeddingUtils;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig.ConsistentLevel;
+import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig.MetadataField;
+import org.springframework.ai.vectorstore.observation.AbstractObservationVectorStore;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationContext;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationConvention;
+import org.springframework.util.Assert;
+import org.springframework.util.CollectionUtils;
+import org.springframework.util.StringUtils;
+
 import com.fasterxml.jackson.core.JsonProcessingException;
 import com.fasterxml.jackson.databind.ObjectMapper;
+
+import io.micrometer.observation.ObservationRegistry;
 import io.weaviate.client.WeaviateClient;
 import io.weaviate.client.base.Result;
 import io.weaviate.client.base.WeaviateErrorMessage;
@@ -42,16 +57,6 @@ import io.weaviate.client.v1.graphql.query.builder.GetBuilder.GetBuilderBuilder;
 import io.weaviate.client.v1.graphql.query.fields.Field;
 import io.weaviate.client.v1.graphql.query.fields.Fields;
 
-import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.EmbeddingModel;
-import org.springframework.ai.model.EmbeddingUtils;
-import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig.ConsistentLevel;
-import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig.MetadataField;
-import org.springframework.beans.factory.InitializingBean;
-import org.springframework.util.Assert;
-import org.springframework.util.CollectionUtils;
-import org.springframework.util.StringUtils;
-
 /**
  * A VectorStore implementation backed by Weaviate vector database.
  *
@@ -65,7 +70,7 @@ import org.springframework.util.StringUtils;
  * @author Josh Long
  * @author Soby Chacko
  */
-public class WeaviateVectorStore implements VectorStore {
+public class WeaviateVectorStore extends AbstractObservationVectorStore {
 
 	public static final String DOCUMENT_METADATA_DISTANCE_KEY_NAME = "distance";
 
@@ -281,9 +286,27 @@ public class WeaviateVectorStore implements VectorStore {
 	 * Constructs a new WeaviateVectorStore.
 	 * @param vectorStoreConfig The configuration for the store.
 	 * @param embeddingModel The client for embedding operations.
+	 * @param weaviateClient The client for Weaviate operations.
 	 */
 	public WeaviateVectorStore(WeaviateVectorStoreConfig vectorStoreConfig, EmbeddingModel embeddingModel,
 			WeaviateClient weaviateClient) {
+		this(vectorStoreConfig, embeddingModel, weaviateClient, ObservationRegistry.NOOP, null);
+	}
+
+	/**
+	 * Constructs a new WeaviateVectorStore.
+	 * @param vectorStoreConfig The configuration for the store.
+	 * @param embeddingModel The client for embedding operations.
+	 * @param weaviateClient The client for Weaviate operations.
+	 * @param observationRegistry The registry for observations.
+	 * @param customObservationConvention The custom observation convention.
+	 */
+	public WeaviateVectorStore(WeaviateVectorStoreConfig vectorStoreConfig, EmbeddingModel embeddingModel,
+			WeaviateClient weaviateClient, ObservationRegistry observationRegistry,
+			VectorStoreObservationConvention customObservationConvention) {
+
+		super(observationRegistry, customObservationConvention);
+
 		Assert.notNull(vectorStoreConfig, "WeaviateVectorStoreConfig must not be null");
 		Assert.notNull(embeddingModel, "EmbeddingModel must not be null");
 
@@ -318,7 +341,7 @@ public class WeaviateVectorStore implements VectorStore {
 	}
 
 	@Override
-	public void add(List<Document> documents) {
+	public void doAdd(List<Document> documents) {
 
 		if (CollectionUtils.isEmpty(documents)) {
 			return;
@@ -395,7 +418,7 @@ public class WeaviateVectorStore implements VectorStore {
 	}
 
 	@Override
-	public Optional<Boolean> delete(List<String> documentIds) {
+	public Optional<Boolean> doDelete(List<String> documentIds) {
 
 		Result<BatchDeleteResponse> result = this.weaviateClient.batch()
 			.objectsBatchDeleter()
@@ -421,7 +444,7 @@ public class WeaviateVectorStore implements VectorStore {
 	}
 
 	@Override
-	public List<Document> similaritySearch(SearchRequest request) {
+	public List<Document> doSimilaritySearch(SearchRequest request) {
 
 		float[] embedding = this.embeddingModel.embed(request.getQuery());
 
@@ -518,4 +541,12 @@ public class WeaviateVectorStore implements VectorStore {
 		return document;
 	}
 
+	@Override
+	public VectorStoreObservationContext.Builder createObservationContextBuilder(String operationName) {
+
+		return VectorStoreObservationContext.builder(VectorStoreProvider.WEAVIATE.value(), operationName)
+			.withDimensions(this.embeddingModel.dimensions())
+			.withCollectionName(this.weaviateObjectClass);
+	}
+
 }

vector-stores/spring-ai-weaviate-store/src/test/java/org/springframework/ai/vectorstore/WeaviateVectorStoreObservationIT.java

@@ -0,0 +1,174 @@
+/*
+ * Copyright 2024 the original author or authors.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.springframework.ai.vectorstore;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.Map;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.observation.conventions.VectorStoreProvider;
+import org.springframework.ai.transformers.TransformersEmbeddingModel;
+import org.springframework.ai.vectorstore.WeaviateVectorStore.WeaviateVectorStoreConfig;
+import org.springframework.ai.vectorstore.observation.DefaultVectorStoreObservationConvention;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.HighCardinalityKeyNames;
+import org.springframework.ai.vectorstore.observation.VectorStoreObservationDocumentation.LowCardinalityKeyNames;
+import org.springframework.boot.SpringBootConfiguration;
+import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
+import org.springframework.boot.test.context.runner.ApplicationContextRunner;
+import org.springframework.context.annotation.Bean;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.testcontainers.containers.wait.strategy.Wait;
+import org.testcontainers.junit.jupiter.Container;
+import org.testcontainers.junit.jupiter.Testcontainers;
+import org.testcontainers.weaviate.WeaviateContainer;
+
+import io.micrometer.observation.ObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistry;
+import io.micrometer.observation.tck.TestObservationRegistryAssert;
+import io.weaviate.client.WeaviateClient;
+
+/**
+ * @author Christian Tzolov
+ */
+@Testcontainers
+public class WeaviateVectorStoreObservationIT {
+
+	@Container
+	static WeaviateContainer weaviateContainer = new WeaviateContainer("semitechnologies/weaviate:1.25.4")
+		.waitingFor(Wait.forHttp("/v1/.well-known/ready").forPort(8080));
+
+	List<Document> documents = List.of(
+			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
+			new Document(getText("classpath:/test/data/time.shelter.txt")),
+			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));
+
+	public static String getText(String uri) {
+		var resource = new DefaultResourceLoader().getResource(uri);
+		try {
+			return resource.getContentAsString(StandardCharsets.UTF_8);
+		}
+		catch (IOException e) {
+			throw new RuntimeException(e);
+		}
+	}
+
+	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
+		.withUserConfiguration(Config.class);
+
+	@Test
+	void observationVectorStoreAddAndQueryOperations() {
+
+		contextRunner.run(context -> {
+
+			VectorStore vectorStore = context.getBean(VectorStore.class);
+
+			TestObservationRegistry observationRegistry = context.getBean(TestObservationRegistry.class);
+
+			vectorStore.add(documents);
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store weaviate add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.WEAVIATE.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "SpringAiWeaviate")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.INDEX_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			observationRegistry.clear();
+
+			List<Document> results = vectorStore
+				.similaritySearch(SearchRequest.query("What is Great Depression").withTopK(1));
+
+			assertThat(results).isNotEmpty();
+
+			TestObservationRegistryAssert.assertThat(observationRegistry)
+				.doesNotHaveAnyRemainingCurrentObservation()
+				.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
+				.that()
+				.hasContextualNameEqualTo("vector_store weaviate query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
+						VectorStoreProvider.WEAVIATE.value())
+				.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
+
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "384")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "SpringAiWeaviate")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.INDEX_NAME.asString(), "none")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
+				.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
+
+				.hasBeenStarted()
+				.hasBeenStopped();
+
+			// vectorStore.delete(documents.stream().map(Document::getId).toList());
+
+		});
+	}
+
+	@SpringBootConfiguration
+	@EnableAutoConfiguration
+	public static class Config {
+
+		@Bean
+		public TestObservationRegistry observationRegistry() {
+			return TestObservationRegistry.create();
+		}
+
+		@Bean
+		public WeaviateVectorStore vectorStore(EmbeddingModel embeddingModel, ObservationRegistry observationRegistry) {
+			WeaviateClient weaviateClient = new WeaviateClient(
+					new io.weaviate.client.Config("http", weaviateContainer.getHttpHostAddress()));
+
+			WeaviateVectorStoreConfig config = WeaviateVectorStore.WeaviateVectorStoreConfig.builder()
+				.withConsistencyLevel(WeaviateVectorStoreConfig.ConsistentLevel.ONE)
+				.build();
+
+			return new WeaviateVectorStore(config, embeddingModel, weaviateClient, observationRegistry, null);
+
+		}
+
+		@Bean
+		public EmbeddingModel embeddingModel() {
+			return new TransformersEmbeddingModel();
+		}
+
+	}
+
+}