From 48f537398d09a7420720d2ecdec41dc42369741d Mon Sep 17 00:00:00 2001 From: Marcin Grzejszczak Date: Tue, 13 Sep 2016 14:18:43 +0200 Subject: [PATCH] Brought back the proper home page --- index.html | 2307 ++-------------------------------------------------- 1 file changed, 80 insertions(+), 2227 deletions(-) diff --git a/index.html b/index.html index 449b32f68..1c815a8af 100644 --- a/index.html +++ b/index.html @@ -1,2254 +1,107 @@ - - - - - - - - -Spring Cloud Sleuth - - - - - -
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1.0.5.BUILD-SNAPSHOT

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Spring Cloud Sleuth implements a distributed tracing solution for Spring Cloud.

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Terminology

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Spring Cloud Sleuth borrows Dapper’s terminology.

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Span: The basic unit of work. For example, sending an RPC is a new span, as is sending a response to an -RPC. Span’s are identified by a unique 64-bit ID for the span and another 64-bit ID for the trace the span -is a part of. Spans also have other data, such as descriptions, timestamped events, key-value -annotations (tags), the ID of the span that caused them, and process ID’s (normally IP address).

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Spans are started and stopped, and they keep track of their timing information. Once you create a -span, you must stop it at some point in the future.

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Trace: A set of spans forming a tree-like structure. For example, if you are running a distributed -big-data store, a trace might be formed by a put request.

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Annotation: is used to record existence of an event in time. Some of the core annotations used to define -the start and stop of a request are:

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    cs - Client Sent - The client has made a request. This annotation depicts the start of the span.

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    sr - Server Received - The server side got the request and will start processing it. -If one subtracts the cs timestamp from this timestamp one will receive the network latency.

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    ss - Server Sent - Annotated upon completion of request processing (when the response -got sent back to the client). If one subtracts the sr timestamp from this timestamp one -will receive the time needed by the server side to process the request.

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    cr - Client Received - Signifies the end of the span. The client has successfully received the -response from the server side. If one subtracts the cs timestamp from this timestamp one -will receive the whole time needed by the client to receive the response from the server.

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Visualization of what Span and Trace will look in a system together with the Zipkin annotations:

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-Trace Info propagation -
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Each color of a note signifies a span (7 spans - from A to G). If you have such information in the note:

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Trace Id = X
-Span Id = D
-Client Sent
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That means that the current span has Trace-Id set to X, Span-Id set to D. It also has emitted - Client Sent event.

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This is how the visualization of the parent / child relationship of spans would look like:

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-Parent child relationship -
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Purpose

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In the following sections the example from the image above will be taken into consideration.

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Distributed tracing with Zipkin

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Altogether there are 10 spans . If you go to traces in Zipkin you will see this number:

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-Traces -
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However if you pick a particular trace then you will see 7 spans:

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-Traces Info propagation -
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Note
-		 -When picking a particular trace you will see merged spans. That means that if there were 2 spans sent to -Zipkin with Server Received and Server Sent / Client Received and Client Sent -annotations then they will presented as a single span. -
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In the image depicting the visualization of what Span and Trace is you can see 20 -colorful labels. How does it happen that in Zipkin 10 spans are received?

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    2 span A labels signify span started and closed. Upon closing a single span is sent to Zipkin.

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    4 span B labels are in fact are single span with 4 annotations. However this span is composed of -two separate instances. One sent from service 1 and one from service 2. So in fact two span instances will be sent -to Zipkin and merged there.

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    2 span C labels signify span started and closed. Upon closing a single span is sent to Zipkin.

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    4 span B labels are in fact are single span with 4 annotations. However this span is composed of -two separate instances. One sent from service 2 and one from service 3. So in fact two span instances will be sent -to Zipkin and merged there.

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    2 span E labels signify span started and closed. Upon closing a single span is sent to Zipkin.

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    4 span B labels are in fact are single span with 4 annotations. However this span is composed of -two separate instances. One sent from service 2 and one from service 4. So in fact two span instances will be sent -to Zipkin and merged there.

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    2 span G labels signify span started and closed. Upon closing a single span is sent to Zipkin.

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So 1 span from A, 2 spans from B, 1 span from C, 2 spans from D, 1 span from E, 2 spans from F and 1 from G. -Altogether 10 spans.

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-Zipkin deployed on Pivotal Web Services -
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Click Pivotal Web Services icon to see it live!Click Pivotal Web Services icon to see it live!
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The dependency graph in Zipkin would look like this:

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-Dependencies -
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-Zipkin deployed on Pivotal Web Services -
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Click Pivotal Web Services icon to see it live!Click Pivotal Web Services icon to see it live!
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Log correlation

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When grepping the logs of those four applications by trace id equal to e.g. 2485ec27856c56f4 one would get the following:

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service1.log:2016-02-26 11:15:47.561  INFO [service1,2485ec27856c56f4,2485ec27856c56f4,true] 68058 --- [nio-8081-exec-1] i.s.c.sleuth.docs.service1.Application   : Hello from service1. Calling service2
-service2.log:2016-02-26 11:15:47.710  INFO [service2,2485ec27856c56f4,9aa10ee6fbde75fa,true] 68059 --- [nio-8082-exec-1] i.s.c.sleuth.docs.service2.Application   : Hello from service2. Calling service3 and then service4
-service3.log:2016-02-26 11:15:47.895  INFO [service3,2485ec27856c56f4,1210be13194bfe5,true] 68060 --- [nio-8083-exec-1] i.s.c.sleuth.docs.service3.Application   : Hello from service3
-service2.log:2016-02-26 11:15:47.924  INFO [service2,2485ec27856c56f4,9aa10ee6fbde75fa,true] 68059 --- [nio-8082-exec-1] i.s.c.sleuth.docs.service2.Application   : Got response from service3 [Hello from service3]
-service4.log:2016-02-26 11:15:48.134  INFO [service4,2485ec27856c56f4,1b1845262ffba49d,true] 68061 --- [nio-8084-exec-1] i.s.c.sleuth.docs.service4.Application   : Hello from service4
-service2.log:2016-02-26 11:15:48.156  INFO [service2,2485ec27856c56f4,9aa10ee6fbde75fa,true] 68059 --- [nio-8082-exec-1] i.s.c.sleuth.docs.service2.Application   : Got response from service4 [Hello from service4]
-service1.log:2016-02-26 11:15:48.182  INFO [service1,2485ec27856c56f4,2485ec27856c56f4,true] 68058 --- [nio-8081-exec-1] i.s.c.sleuth.docs.service1.Application   : Got response from service2 [Hello from service2, response from service3 [Hello from service3] and from service4 [Hello from service4]]
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If you’re using a log aggregating tool like Kibana, -Splunk etc. you can order the events that took place. An example of -Kibana would look like this:

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-Log correlation with Kibana -
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If you want to use Logstash here is the Grok pattern for Logstash:

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filter {
-       # pattern matching logback pattern
-       grok {
-              match => { "message" => "%{TIMESTAMP_ISO8601:timestamp}\s+%{LOGLEVEL:severity}\s+\[%{DATA:service},%{DATA:trace},%{DATA:span},%{DATA:exportable}\]\s+%{DATA:pid}---\s+\[%{DATA:thread}\]\s+%{DATA:class}\s+:\s+%{GREEDYDATA:rest}" }
-       }
-}
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Note
-		 -If you want to use Grok together with the logs from Cloud Foundry you have to use this pattern: -
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filter {
-       # pattern matching logback pattern
-       grok {
-              match => { "message" => "(?m)OUT\s+%{TIMESTAMP_ISO8601:timestamp}\s+%{LOGLEVEL:severity}\s+\[%{DATA:service},%{DATA:trace},%{DATA:span},%{DATA:exportable}\]\s+%{DATA:pid}---\s+\[%{DATA:thread}\]\s+%{DATA:class}\s+:\s+%{GREEDYDATA:rest}" }
-       }
-}
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JSON Logback with Logstash
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Often you do not want to store your logs in a text file but in a JSON file that Logstash can immediately pick. To do that you have to do the following (for readability -we’re passing the dependencies in the groupId:artifactId:version notation.

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Dependencies setup

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    Ensure that Logback is on the classpath (ch.qos.logback:logback-core)

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    Add Logstash Logback encode - example for version 4.6 : net.logstash.logback:logstash-logback-encoder:4.6

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Logback setup

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Below you can find an example of a Logback configuration (file named https://github.com/spring-cloud-samples/sleuth-documentation-apps/blob/master/service1/src/main/resources/logback-spring.xml[logback-spring.xml]) that:

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    logs information from the application in a JSON format to a build/${spring.application.name}.json file

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    has commented out two additional appenders - console and standard log file

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    has the same logging pattern as the one presented in the previous section

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<?xml version="1.0" encoding="UTF-8"?>
-<configuration>
-	<include resource="org/springframework/boot/logging/logback/defaults.xml"/>
-	​
-	<springProperty scope="context" name="springAppName" source="spring.application.name"/>
-	<!-- Example for logging into the build folder of your project -->
-	<property name="LOG_FILE" value="${BUILD_FOLDER:-build}/${springAppName}"/>​
+---
+# The name of your project
+title: Spring Cloud Sleuth
 
-	<property name="CONSOLE_LOG_PATTERN"
-			  value="%clr(%d{yyyy-MM-dd HH:mm:ss.SSS}){faint} %clr(${LOG_LEVEL_PATTERN:-%5p}) %clr([${springAppName:-},%X{X-B3-TraceId:-},%X{X-B3-SpanId:-},%X{X-Span-Export:-}]){yellow} %clr(${PID:- }){magenta} %clr(---){faint} %clr([%15.15t]){faint} %clr(%-40.40logger{39}){cyan} %clr(:){faint} %m%n${LOG_EXCEPTION_CONVERSION_WORD:-%wEx}"/>
+badges:
 
-	<!-- Appender to log to console -->
-	<appender name="console" class="ch.qos.logback.core.ConsoleAppender">
-		<filter class="ch.qos.logback.classic.filter.ThresholdFilter">
-			<!-- Minimum logging level to be presented in the console logs-->
-			<level>INFO</level>
-		</filter>
-		<encoder>
-			<pattern>${CONSOLE_LOG_PATTERN}</pattern>
-			<charset>utf8</charset>
-		</encoder>
-	</appender>
+  # Customize your project's badges. Delete any entries that do not apply.
+  custom:
+    - name: Source (GitHub)
+      url:  https://github.com/spring-cloud/spring-cloud-sleuth
+      icon: github
 
-	<!-- Appender to log to file -->​
-	<appender name="flatfile" class="ch.qos.logback.core.rolling.RollingFileAppender">
-		<file>${LOG_FILE}</file>
-		<rollingPolicy class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy">
-			<fileNamePattern>${LOG_FILE}.%d{yyyy-MM-dd}.gz</fileNamePattern>
-			<maxHistory>7</maxHistory>
-		</rollingPolicy>
-		<encoder>
-			<pattern>${CONSOLE_LOG_PATTERN}</pattern>
-			<charset>utf8</charset>
-		</encoder>
-	</appender>
-	​
-	<!-- Appender to log to file in a JSON format -->
-	<appender name="logstash" class="ch.qos.logback.core.rolling.RollingFileAppender">
-		<file>${LOG_FILE}.json</file>
-		<rollingPolicy class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy">
-			<fileNamePattern>${LOG_FILE}.json.%d{yyyy-MM-dd}.gz</fileNamePattern>
-			<maxHistory>7</maxHistory>
-		</rollingPolicy>
-		<encoder class="net.logstash.logback.encoder.LoggingEventCompositeJsonEncoder">
-			<providers>
-				<timestamp>
-					<timeZone>UTC</timeZone>
-				</timestamp>
-				<pattern>
-					<pattern>
-						{
-						"severity": "%level",
-						"service": "${springAppName:-}",
-						"trace": "%X{X-B3-TraceId:-}",
-						"span": "%X{X-B3-SpanId:-}",
-						"exportable": "%X{X-Span-Export:-}",
-						"pid": "${PID:-}",
-						"thread": "%thread",
-						"class": "%logger{40}",
-						"rest": "%message"
-						}
-					</pattern>
-				</pattern>
-			</providers>
-		</encoder>
-	</appender>
-	​
-	<root level="INFO">
-		<!--<appender-ref ref="console"/>-->
-		<appender-ref ref="logstash"/>
-		<!--<appender-ref ref="flatfile"/>-->
-	</root>
-</configuration>
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Adding to the project

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Only Sleuth (log correlation)

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If you want to profit only from Spring Cloud Sleuth without the Zipkin integration just add -the spring-cloud-starter-sleuth module to your project.

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Maven
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<dependencyManagement> (1)
-         <dependencies>
-             <dependency>
-                 <groupId>org.springframework.cloud</groupId>
-                 <artifactId>spring-cloud-dependencies</artifactId>
-                 <version>Brixton.RELEASE</version>
-                 <type>pom</type>
-                 <scope>import</scope>
-             </dependency>
-         </dependencies>
-   </dependencyManagement>
+    - name: StackOverflow
+      url:  http://stackoverflow.com/questions/tagged/spring-cloud
+      icon: stackoverflow
 
-   <dependency> (2)
-       <groupId>org.springframework.cloud</groupId>
-       <artifactId>spring-cloud-starter-sleuth</artifactId>
-   </dependency>
-
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  1. -

    In order not to pick versions by yourself it’s much better if you add the dependency management via -the Spring BOM

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    Add the dependency to spring-cloud-starter-sleuth

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Gradle
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dependencyManagement { (1)
-    imports {
-        mavenBom "org.springframework.cloud:spring-cloud-dependencies:Brixton.RELEASE"
-    }
-}
+---
+
+
 
-dependencies { (2)
-    compile "org.springframework.cloud:spring-cloud-starter-sleuth"
-}
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    In order not to pick versions by yourself it’s much better if you add the dependency management via -the Spring BOM

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    Add the dependency to spring-cloud-starter-sleuth

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Sleuth with Zipkin via HTTP

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If you want both Sleuth and Zipkin just add the spring-cloud-starter-zipkin dependency.

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Maven
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<dependencyManagement> (1)
-         <dependencies>
-             <dependency>
-                 <groupId>org.springframework.cloud</groupId>
-                 <artifactId>spring-cloud-dependencies</artifactId>
-                 <version>Brixton.RELEASE</version>
-                 <type>pom</type>
-                 <scope>import</scope>
-             </dependency>
-         </dependencies>
-   </dependencyManagement>
+
+{% capture parent_link %}
+[Spring Cloud]({{ site.projects_site_url }}/spring-cloud)
+{% endcapture %}
 
-   <dependency> (2)
-       <groupId>org.springframework.cloud</groupId>
-       <artifactId>spring-cloud-starter-zipkin</artifactId>
-   </dependency>
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  1. -

    In order not to pick versions by yourself it’s much better if you add the dependency management via -the Spring BOM

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    Add the dependency to spring-cloud-starter-zipkin

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Gradle
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dependencyManagement { (1)
-    imports {
-        mavenBom "org.springframework.cloud:spring-cloud-dependencies:Brixton.RELEASE"
-    }
-}
 
-dependencies { (2)
-    compile "org.springframework.cloud:spring-cloud-starter-zipkin"
-}
-
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    -
  1. -

    In order not to pick versions by yourself it’s much better if you add the dependency management via -the Spring BOM

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    Add the dependency to spring-cloud-starter-zipkin

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Sleuth with Zipkin via Spring Cloud Stream

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If you want both Sleuth and Zipkin just add the spring-cloud-sleuth-stream dependency.

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Maven
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<dependencyManagement> (1)
-         <dependencies>
-             <dependency>
-                 <groupId>org.springframework.cloud</groupId>
-                 <artifactId>spring-cloud-dependencies</artifactId>
-                 <version>Brixton.RELEASE</version>
-                 <type>pom</type>
-                 <scope>import</scope>
-             </dependency>
-         </dependencies>
-   </dependencyManagement>
+{% capture billboard_description %}
 
-   <dependency> (2)
-       <groupId>org.springframework.cloud</groupId>
-       <artifactId>spring-cloud-sleuth-stream</artifactId>
-   </dependency>
-   <dependency> (3)
-       <groupId>org.springframework.cloud</groupId>
-       <artifactId>spring-cloud-starter-sleuth</artifactId>
-   </dependency>
-   <!-- EXAMPLE FOR RABBIT BINDING -->
-   <dependency> (4)
-       <groupId>org.springframework.cloud</groupId>
-       <artifactId>spring-cloud-stream-binder-rabbit</artifactId>
-   </dependency>
-
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    -
  1. -

    In order not to pick versions by yourself it’s much better if you add the dependency management via -the Spring BOM

    -
    2. -
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    Add the dependency to spring-cloud-sleuth-stream

    -
    3. -
  3. -

    Add the dependency to spring-cloud-starter-sleuth - that way all dependant dependencies will be downloaded

    -
    4. -
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    Add a binder (e.g. Rabbit binder) to tell Spring Cloud Stream what it should bind to

    -
    5. -
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Gradle
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dependencyManagement { (1)
-    imports {
-        mavenBom "org.springframework.cloud:spring-cloud-dependencies:Brixton.RELEASE"
-    }
-}
+Spring Cloud Sleuth implements a distributed tracing solution for Spring Cloud, borrowing heavily from [Dapper](http://research.google.com/pubs/pub36356.html), [Zipkin](https://github.com/openzipkin/zipkin) and HTrace. For most users Sleuth should be invisible, and all your interactions with external systems should be instrumented automatically. You can capture data simply in logs, or by sending it to a remote collector service.
 
-dependencies {
-    compile "org.springframework.cloud:spring-cloud-sleuth-stream" (2)
-    compile "org.springframework.cloud:spring-cloud-starter-sleuth" (3)
-    // Example for Rabbit binding
-    compile "org.springframework.cloud:spring-cloud-stream-binder-rabbit" (4)
-}
-
-
-
-
    -
  1. -

    In order not to pick versions by yourself it’s much better if you add the dependency management via -the Spring BOM

    -
    2. -
  2. -

    Add the dependency to spring-cloud-sleuth-stream

    -
    3. -
  3. -

    Add the dependency to spring-cloud-starter-sleuth - that way all dependant dependencies will be downloaded

    -
    4. -
  4. -

    Add a binder (e.g. Rabbit binder) to tell Spring Cloud Stream what it should bind to

    -
    5. -
-
-
-
-

Spring Cloud Sleuth Stream Zipkin Collector

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If you want to start a Spring Cloud Sleuth Stream Zipkin collector just add the spring-cloud-sleuth-zipkin-stream -dependency

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-
-
Maven
-
-
<dependencyManagement> (1)
-         <dependencies>
-             <dependency>
-                 <groupId>org.springframework.cloud</groupId>
-                 <artifactId>spring-cloud-dependencies</artifactId>
-                 <version>Brixton.RELEASE</version>
-                 <type>pom</type>
-                 <scope>import</scope>
-             </dependency>
-         </dependencies>
-   </dependencyManagement>
+{% endcapture %}
 
-   <dependency> (2)
-       <groupId>org.springframework.cloud</groupId>
-       <artifactId>spring-cloud-sleuth-zipkin-stream</artifactId>
-   </dependency>
-   <dependency> (3)
-       <groupId>org.springframework.cloud</groupId>
-       <artifactId>spring-cloud-starter-sleuth</artifactId>
-   </dependency>
-   <!-- EXAMPLE FOR RABBIT BINDING -->
-   <dependency> (4)
-       <groupId>org.springframework.cloud</groupId>
-       <artifactId>spring-cloud-stream-binder-rabbit</artifactId>
-   </dependency>
-
-
-
-
    -
  1. -

    In order not to pick versions by yourself it’s much better if you add the dependency management via -the Spring BOM

    -
    2. -
  2. -

    Add the dependency to spring-cloud-sleuth-zipkin-stream

    -
    3. -
  3. -

    Add the dependency to spring-cloud-starter-sleuth - that way all dependant dependencies will be downloaded

    -
    4. -
  4. -

    Add a binder (e.g. Rabbit binder) to tell Spring Cloud Stream what it should bind to

    -
    5. -
-
-
-
Gradle
-
-
dependencyManagement { (1)
-    imports {
-        mavenBom "org.springframework.cloud:spring-cloud-dependencies:Brixton.RELEASE"
-    }
-}
+{% capture main_content %}
 
-dependencies {
-    compile "org.springframework.cloud:spring-cloud-sleuth-zipkin-stream" (2)
-    compile "org.springframework.cloud:spring-cloud-starter-sleuth" (3)
-    // Example for Rabbit binding
-    compile "org.springframework.cloud:spring-cloud-stream-binder-rabbit" (4)
-}
-
-
-
-
    -
  1. -

    In order not to pick versions by yourself it’s much better if you add the dependency management via -the Spring BOM

    -
    2. -
  2. -

    Add the dependency to spring-cloud-sleuth-zipkin-stream

    -
    3. -
  3. -

    Add the dependency to spring-cloud-starter-sleuth - that way all dependant dependencies will be downloaded

    -
    4. -
  4. -

    Add a binder (e.g. Rabbit binder) to tell Spring Cloud Stream what it should bind to

    -
    5. -
-
-
-

and then just annotate your main class with @EnableZipkinStreamServer annotation:

-
-
-
-
package example;
+## Features
 
-import org.springframework.boot.SpringApplication;
-import org.springframework.boot.autoconfigure.SpringBootApplication;
-import org.springframework.cloud.sleuth.zipkin.stream.EnableZipkinStreamServer;
+A Span is the basic unit of work. For example, sending an RPC is a new span, as is sending a response to an RPC. Span’s are identified by a unique 64-bit ID for the span and another 64-bit ID for the trace the span is a part of. Spans also have other data, such as descriptions, key-value annotations, the ID of the span that caused them, and process ID’s (normally IP address). Spans are started and stopped, and they keep track of their timing information. Once you create a span, you must stop it at some point in the future. A set of spans forming a tree-like structure called a Trace. For example, if you are running a distributed big-data store, a trace might be formed by a put request.
 
+Spring Cloud Sleuth features:
+
+* Adds trace and span ids to the Slf4J MDC, so you can extract all the logs from a given trace or span in a log aggregator.
+
+* Provides an abstraction over common distributed tracing data models: traces, spans (forming a DAG), annotations, key-value annotations. Loosely based on HTrace, but Zipkin (Dapper) compatible.
+
+* Instruments common ingress and egress points from Spring applications (servlet filter, rest template, scheduled actions, message channels, zuul filters, feign client).
+
+* If `spring-cloud-sleuth-zipkin` is available then the app will generate and collect Zipkin-compatible traces via HTTP. By default it sends them to a Zipkin collector service on localhost (port 9411). Configure the location of the service using `spring.zipkin.[host,port]`.
+
+
+
+## Quick Start
+
+{% include download_widget.md %}
+
+
+
+As long as Spring Cloud Sleuth is on the classpath any Spring Boot
+application will generate trace data:
+
+```java
 @SpringBootApplication
-@EnableZipkinStreamServer
-public class ZipkinStreamServerApplication {
+@RestController
+public class Application {
 
-	public static void main(String[] args) throws Exception {
-		SpringApplication.run(ZipkinStreamServerApplication.class, args);
-	}
+  private static Logger log = LoggerFactory.getLogger(DemoController.class);
 
-}
-
-
-
-
-
-

Features

-
-
-
    -
  • -

    Adds trace and span ids to the Slf4J MDC, so you can extract all the logs from a given trace or span in a log aggregator. Example logs:

    -
    -
    -
    2016-02-02 15:30:57.902  INFO [bar,6bfd228dc00d216b,6bfd228dc00d216b,false] 23030 --- [nio-8081-exec-3] ...
-2016-02-02 15:30:58.372 ERROR [bar,6bfd228dc00d216b,6bfd228dc00d216b,false] 23030 --- [nio-8081-exec-3] ...
-2016-02-02 15:31:01.936  INFO [bar,46ab0d418373cbc9,46ab0d418373cbc9,false] 23030 --- [nio-8081-exec-4] ...
    -
    -
    -
    -

    notice the [appname,traceId,spanId,exportable] entries from the MDC:

    -
    -
    -
      -
    • -

      spanId - the id of a specific operation that took place

      -
      • -
    • -

      appname - the name of the application that logged the span

      -
      • -
    • -

      traceId - the id of the latency graph that contains the span

      -
      • -
    • -

      exportable - whether the log should be exported to Zipkin or not. When would you like the span not to be -exportable? In the case in which you want to wrap some operation in a Span and have it written to the logs -only.

      -
      • -
    -
    -
    • -
  • -

    Provides an abstraction over common distributed tracing data models: traces, spans (forming a DAG), annotations, -key-value annotations. Loosely based on HTrace, but Zipkin (Dapper) compatible.

    -
    • -
  • -

    Sleuth records timing information to aid in latency analysis. Using sleuth, you can pinpoint causes of -latency in your applications. Sleuth is written to not log too much, and to not cause your production application to crash.

    -
    -
      -
    • -

      propagates structural data about your call-graph in-band, and the rest out-of-band.

      -
      • -
    • -

      includes opinionated instrumentation of layers such as HTTP

      -
      • -
    • -

      includes sampling policy to manage volume

      -
      • -
    • -

      can report to a Zipkin system for query and visualization

      -
      • -
    -
    -
    • -
  • -

    Instruments common ingress and egress points from Spring applications (servlet filter, async endpoints, -rest template, scheduled actions, message channels, zuul filters, feign client).

    -
    • -
  • -

    Sleuth includes default logic to join a trace across http or messaging boundaries. For example, http propagation -works via Zipkin-compatible request headers. This propagation logic is defined and customized via -SpanInjector and SpanExtractor implementations.

    -
    • -
  • -

    Provides simple metrics of accepted / dropped spans.

    -
    • -
  • -

    If spring-cloud-sleuth-zipkin then the app will generate and collect Zipkin-compatible traces. -By default it sends them via HTTP to a Zipkin server on localhost (port 9411). -Configure the location of the service using spring.zipkin.baseUrl.

    -
    • -
  • -

    If spring-cloud-sleuth-stream then the app will generate and collect traces via Spring Cloud Stream. -Your app automatically becomes a producer of tracer messages that are sent over your broker of choice -(e.g. RabbitMQ, Apache Kafka, Redis).

    -
    • -
-
-
- - - - - -
-
Important
-		 -If using Zipkin or Stream, configure the percentage of spans exported using spring.sleuth.sampler.percentage -(default 0.1, i.e. 10%). Otherwise you might think that Sleuth is not working cause it’s omitting some spans. -
-
-
- - - - - -
-
Note
-		 -the SLF4J MDC is always set and logback users will immediately see the trace and span ids in logs per the example - above. Other logging systems have to configure their own formatter to get the same result. The default is - logging.pattern.level set to %clr(%5p) %clr([${spring.application.name:},%X{X-B3-TraceId:-},%X{X-B3-SpanId:-},%X{X-Span-Export:-}]){yellow} - (this is a Spring Boot feature for logback users). - This means that if you’re not using SLF4J this pattern WILL NOT be automatically applied. -
-
-
-
-
-

Sampling

-
-
-

In distributed tracing the data volumes can be very high so sampling -can be important (you usually don’t need to export all spans to get a -good picture of what is happening). Spring Cloud Sleuth has a -Sampler strategy that you can implement to take control of the -sampling algorithm. Samplers do not stop span (correlation) ids from -being generated, but they do prevent the tags and events being -attached and exported. By default you get a strategy that continues to -trace if a span is already active, but new ones are always marked as -non-exportable. If all your apps run with this sampler you will see -traces in logs, but not in any remote store. For testing the default -is often enough, and it probably is all you need if you are only using -the logs (e.g. with an ELK aggregator). If you are exporting span data -to Zipkin or Spring Cloud Stream, there is also an AlwaysSampler -that exports everything and a PercentageBasedSampler that samples a -fixed fraction of spans.

-
-
- - - - - -
-
Note
-		 -the PercentageBasedSampler is the default if you are using -spring-cloud-sleuth-zipkin or spring-cloud-sleuth-stream. You can -configure the exports using spring.sleuth.sampler.percentage. -
-
-
-

A sampler can be installed just by creating a bean definition, e.g:

-
-
-
-
@Bean
-public Sampler defaultSampler() {
-	return new AlwaysSampler();
-}
-
-
-
-
-
-

Instrumentation

-
-
-

Spring Cloud Sleuth instruments all your Spring application -automatically, so you shouldn’t have to do anything to activate -it. The instrumentation is added using a variety of technologies -according to the stack that is available, e.g. for a servlet web -application we use a Filter, and for Spring Integration we use -ChannelInterceptors.

-
-
-

You can customize the keys used in span tags. To limit the volume of -span data, by default an HTTP request will be tagged only with a -handful of metadata like the status code, host and URL. You can add -request headers by configuring spring.sleuth.keys.http.headers (a -list of header names).

-
-
- - - - - -
-
Note
-		 -Remember that tags are only collected and exported if there is a -Sampler that allows it (by default there is not, so there is no -danger of accidentally collecting too much data without configuring -something). -
-
-
- - - - - -
-
Note
-		 -Currently the instrumentation in Spring Cloud Sleuth is eager - it means that -we’re actively trying to pass the tracing context between threads. Also timing events -are captured even when sleuth isn’t exporting data to a tracing system. -This approach may change in the future towards being lazy on this matter. -
-
-
-
-
-

Span lifecycle

-
-
-

You can do the following operations on the Span by means of Tracer interface:

-
-
-
    -
  • -

    start - when you start a span its name is assigned and start timestamp is recorded.

    -
    • -
  • -

    close - the span gets finished (the end time of the span is recorded) and if -the span is exportable then it will be eligible for collection to Zipkin. -The span is also removed from the current thread.

    -
    • -
  • -

    continue - a new instance of span will be created whereas it will be a copy of the -one that it continues.

    -
    • -
  • -

    detach - the span doesn’t get stopped or closed. It only gets removed from the current thread.

    -
    • -
  • -

    create with explicit parent - you can create a new span and set an explicit parent to it

    -
    • -
-
-
-

Creating and closing spans

-
-

You can manually create spans by using the Tracer interface.

-
-
-
-
// Start a span. If there was a span present in this thread it will become
-// the `newSpan`'s parent.
-Span newSpan = this.tracer.createSpan("calculateTax");
-try {
-	// ...
-	// You can tag a span
-	this.tracer.addTag("taxValue", taxValue);
-	// ...
-	// You can log an event on a span
-	newSpan.logEvent("taxCalculated");
-} finally {
-	// Once done remember to close the span. This will allow collecting
-	// the span to send it to Zipkin
-	this.tracer.close(newSpan);
-}
-
-
-
-

In this example we could see how to create a new instance of span. Assuming that there already -was a span present in this thread then it would become the parent of that span.

-
-
- - - - - -
-
Important
-		 -Always clean after you create a span! Don’t forget to close a span if you want to send it to Zipkin. -
-
-
-
-

Continuing spans

-
-

Sometimes you don’t want to create a new span but you want to continue one. Example of such a -situation might be (of course it all depends on the use-case):

-
-
-
    -
  • -

    AOP - If there was already a span created before an aspect was reached then you might not want to create a new span.

    -
    • -
  • -

    Hystrix - executing a Hystrix command is most likely a logical part of the current processing. It’s in fact -only a technical implementation detail that you wouldn’t necessarily want to reflect in tracing as a separate being.

    -
    • -
-
-
-

The continued instance of span is equal to the one that it continues:

-
-
-
-
Span continuedSpan = this.tracer.continueSpan(spanToContinue);
-assertThat(continuedSpan).isEqualTo(spanToContinue);
-
-
-
-

To continue a span you can use the Tracer interface.

-
-
-
-
// let's assume that we're in a thread Y and we've received
-// the `initialSpan` from thread X
-Span continuedSpan = this.tracer.continueSpan(initialSpan);
-try {
-	// ...
-	// You can tag a span
-	this.tracer.addTag("taxValue", taxValue);
-	// ...
-	// You can log an event on a span
-	continuedSpan.logEvent("taxCalculated");
-} finally {
-	// Once done remember to detach the span. That way you'll
-	// safely remove it from the current thread without closing it
-	this.tracer.detach(continuedSpan);
-}
-
-
-
- - - - - -
-
Important
-		 -Always clean after you create a span! Don’t forget to detach a span if some work was done started in one - thread (e.g. thread X) and it’s waiting for other threads (e.g. Y, Z) to finish. - Then the spans in the threads Y, Z should be detached at the end of their work. When the results are collected - the span in thread X should be closed. -
-
-
-
-

Creating spans with an explicit parent

-
-

There is a possibility that you want to start a new span and provide an explicit parent of that span. -Let’s assume that the parent of a span is in one thread and you want to start a new span in another thread. The -startSpan method of the Tracer interface is the method you are looking for.

-
-
-
-
// let's assume that we're in a thread Y and we've received
-// the `initialSpan` from thread X. `initialSpan` will be the parent
-// of the `newSpan`
-Span newSpan = this.tracer.createSpan("calculateCommission", initialSpan);
-try {
-	// ...
-	// You can tag a span
-	this.tracer.addTag("commissionValue", commissionValue);
-	// ...
-	// You can log an event on a span
-	newSpan.logEvent("commissionCalculated");
-} finally {
-	// Once done remember to close the span. This will allow collecting
-	// the span to send it to Zipkin. The tags and events set on the
-	// newSpan will not be present on the parent
-	this.tracer.close(newSpan);
-}
-
-
-
- - - - - -
-
Important
-		 -After having created such a span remember to close it. Otherwise you will see a lot of warnings in your logs - related to the fact that you have a span present in the current thread other than the one you’re trying to close. - What’s worse your spans won’t get closed properly thus will not get collected to Zipkin. -
-
-
-
-
-
-

Naming spans

-
-
-

Picking a span name is not a trivial task. Span name should depict an operation name. The name should -be low cardinality (e.g. not include identifiers).

-
-
-

Since there is a lot of instrumentation going on some of the span names will be -artificial like:

-
-
-
    -
  • -

    controller-method-name when received by a Controller with a method name conrollerMethodName

    -
    • -
  • -

    async for asynchronous operations done via wrapped Callable and Runnable.

    -
    • -
  • -

    @Scheduled annotated methods will return the simple name of the class.

    -
    • -
-
-
-

Fortunately, for the asynchronous processing you can provide explicit naming.

-
-
-

@SpanName annotation

-
-

You can do name the span explicitly via the @SpanName annotation.

-
-
-
-
@SpanName("calculateTax")
-class TaxCountingRunnable implements Runnable {
+  @RequestMapping("/")
+  public String home() {
+    log.info("Handling home");
+    return "Hello World";
+  }
 
-	@Override public void run() {
-		// perform logic
-	}
-}
-
-
-
-

In this case, when processed in the following manner:

-
-
-
-
Runnable runnable = new TraceRunnable(tracer, spanNamer, new TaxCountingRunnable());
-Future<?> future = executorService.submit(runnable);
-// ... some additional logic ...
-future.get();
-
-
-
-

The span will be named calculateTax.

-
-
-
-

toString() method

-
-

It’s pretty rare to create separate classes for Runnable or Callable. Typically one creates an anonymous -instance of those classes. You can’t annotate such classes thus to override that, if there is no @SpanName annotation present, -we’re checking if the class has a custom implementation of the toString() method.

-
-
-

So executing such code:

-
-
-
-
Runnable runnable = new TraceRunnable(tracer, spanNamer, new Runnable() {
-	@Override public void run() {
-		// perform logic
-	}
+  public static void main(String[] args) {
+    SpringApplication.run(Application.class, args);
+  }
 
-	@Override public String toString() {
-		return "calculateTax";
-	}
-});
-Future<?> future = executorService.submit(runnable);
-// ... some additional logic ...
-future.get();
-
-
-
-

will lead in creating a span named calculateTax.

-
-
-
-
-
-

Customizations

-
-
-

Thanks to the SpanInjector and SpanExtractor you can customize the way spans -are created and propagated.

-
-
-

There are currently two built-in ways to pass tracing information between processes:

-
-
-
    -
  • -

    via Spring Integration

    -
    • -
  • -

    via HTTP

    -
    • -
-
-
-

Span ids are extracted from Zipkin-compatible (B3) headers (either Message -or HTTP headers), to start or join an existing trace. Trace information is -injected into any outbound requests so the next hop can extract them.

-
-
-

Spring Integration

-
-

For Spring Integration these are the beans responsible for creation of a Span from a Message - and filling in the MessageBuilder with tracing information.

-
-
-
-
@Bean
-public SpanExtractor<Message> messagingSpanExtractor() {
-    ...
 }
+```
 
-@Bean
-public SpanInjector<MessageBuilder> messagingSpanInjector() {
-    ...
-}
-
-
-
-

You can override them by providing your own implementation and by adding a @Primary annotation -to your bean definition.

-
-
-
-

HTTP

-
-

For HTTP these are the beans responsible for creation of a Span from a HttpServletRequest - and filling in the HttpServletResponse with tracing information.

-
-
-
-
@Bean
-public SpanExtractor<HttpServletRequest> httpServletRequestSpanExtractor() {
-    ...
-}
+Run this app and then hit the home page. You will see traceId and
+spanId populated in the logs. If this app calls out to another one
+(e.g. with `RestTemplate`) it will send the trace data in headers and
+if the receiver is another Sleuth app you will see the trace continue
+there.
 
-@Bean
-public SpanInjector<HttpServletResponse> httpServletResponseSpanInjector() {
-    ...
-}
-
-
-
-

You can override them by providing your own implementation and by adding a @Primary annotation -to your bean definition.

-
-
-
-

Example

-
-

Let’s assume that instead of the standard Zipkin compatible tracing HTTP header names -you have

-
-
-
    -
  • -

    for trace id - correlationId

    -
    • -
  • -

    for span id - mySpanId

    -
    • -
-
-
-

This is a an example of a SpanExtractor

-
-
-
-
static class CustomHttpServletRequestSpanExtractor
-		implements SpanExtractor<HttpServletRequest> {
+> NOTE: instead of logging the request in the handler explicitly, you
+could set
+`logging.level.org.springframework.web.servlet.DispatcherServlet=DEBUG`
 
-	@Override
-	public Span joinTrace(HttpServletRequest carrier) {
-		long traceId = Span.hexToId(carrier.getHeader("correlationId"));
-		long spanId = Span.hexToId(carrier.getHeader("mySpanId"));
-		// extract all necessary headers
-		Span.SpanBuilder builder = Span.builder().traceId(traceId).spanId(spanId);
-		// build rest of the Span
-		return builder.build();
-	}
-}
-
-
-
-

The following SpanInjector could be created

-
-
-
-
static class CustomHttpServletResponseSpanInjector
-		implements SpanInjector<HttpServletResponse> {
+> NOTE: Set `spring.application.name=bar` (for instance) to see the
+service name as well as the trace and span ids.
 
-	@Override
-	public void inject(Span span, HttpServletResponse carrier) {
-		carrier.addHeader("correlationId", Span.idToHex(span.getTraceId()));
-		carrier.addHeader("mySpanId", Span.idToHex(span.getSpanId()));
-		// inject the rest of Span values to the header
-	}
-}
-
-
-
-

And you could register them like this:

-
-
-
-
@Bean
-@Primary
-SpanExtractor<HttpServletRequest> customHttpServletRequestSpanExtractor() {
-	return new CustomHttpServletRequestSpanExtractor();
-}
+{% endcapture %}
 
-@Bean
-@Primary
-SpanInjector<HttpServletResponse> customHttpServletResponseSpanInjector() {
-	return new CustomHttpServletResponseSpanInjector();
-}
-
-
-
-
-
-
-

Span Data as Messages

-
-
-

You can accumulate and send span data over -Spring Cloud Stream by -including the spring-cloud-sleuth-stream jar as a dependency, and -adding a Channel Binder implementation -(e.g. spring-cloud-starter-stream-rabbit for RabbitMQ or -spring-cloud-starter-stream-kafka for Kafka). This will -automatically turn your app into a producer of messages with payload -type Spans.

-
-
-

Zipkin Consumer

-
-

There is a special convenience annotation for setting up a message consumer -for the Span data and pushing it into a Zipkin SpanStore. This application

-
-
-
-
@SpringBootApplication
-@EnableZipkinStreamServer
-public class Consumer {
-	public static void main(String[] args) {
-		SpringApplication.run(Consumer.class, args);
-	}
-}
-
-
-
-

will listen for the Span data on whatever transport you provide via a -Spring Cloud Stream Binder (e.g. include -spring-cloud-starter-stream-rabbit for RabbitMQ, and similar -starters exist for Redis and Kafka). If you add the following UI dependency

-
-
-
-
<groupId>io.zipkin.java</groupId>
-<artifactId>zipkin-autoconfigure-ui</artifactId>
-
-
-
-

Then you’ll have your app a -Zipkin server, which hosts -the UI and api on port 9411.

-
-
-

The default SpanStore is in-memory (good for demos and getting -started quickly). For a more robust solution you can add MySQL and -spring-boot-starter-jdbc to your classpath and enable the JDBC -SpanStore via configuration, e.g.:

-
-
-
-
spring:
-  rabbitmq:
-    host: ${RABBIT_HOST:localhost}
-  datasource:
-    schema: classpath:/mysql.sql
-    url: jdbc:mysql://${MYSQL_HOST:localhost}/test
-    username: root
-    password: root
-# Switch this on to create the schema on startup:
-    initialize: true
-    continueOnError: true
-  sleuth:
-    enabled: false
-zipkin:
-  storage:
-    type: mysql
-
-
-
- - - - - -
-
Note
-		 -The @EnableZipkinStreamServer is also annotated with -@EnableZipkinServer so the process will also expose the standard -Zipkin server endpoints for collecting spans over HTTP, and for -querying in the Zipkin Web UI. -
-
-
-
-

Custom Consumer

-
-

A custom consumer can also easily be implemented using -spring-cloud-sleuth-stream and binding to the SleuthSink. Example:

-
-
-
-
@EnableBinding(SleuthSink.class)
-@SpringBootApplication(exclude = SleuthStreamAutoConfiguration.class)
-@MessageEndpoint
-public class Consumer {
+{% capture related_resources %}
 
-    @ServiceActivator(inputChannel = SleuthSink.INPUT)
-    public void sink(Spans input) throws Exception {
-        // ... process spans
-    }
-}
-
-
-
- - - - - -
-
Note
-		 -the sample consumer application above explicitly excludes -SleuthStreamAutoConfiguration so it doesn’t send messages to itself, -but this is optional (you might actually want to trace requests into -the consumer app). -
-
-
-
-
-
-

Metrics

-
-
-

Currently Spring Cloud Sleuth registers very simple metrics related to spans. -It’s using the Spring Boot’s metrics support -to calculate the number of accepted and dropped spans. Each time a span gets -sent to Zipkin the number of accepted spans will increase. If there’s an error then -the number of dropped spans will get increased.

-
-
-
-
-

Integrations

-
-
-

Runnable and Callable

-
-

If you’re wrapping your logic in Runnable or Callable it’s enough to wrap those classes in their Sleuth representative.

-
-
-

Example for Runnable:

-
-
-
-
Runnable runnable = new Runnable() {
-	@Override
-	public void run() {
-		// do some work
-	}
+### Sample Projects
 
-	@Override
-	public String toString() {
-		return "spanNameFromToStringMethod";
-	}
-};
-// Manual `TraceRunnable` creation with explicit "calculateTax" Span name
-Runnable traceRunnable = new TraceRunnable(tracer, spanNamer, runnable, "calculateTax");
-// Wrapping `Runnable` with `Tracer`. The Span name will be taken either from the
-// `@SpanName` annotation or from `toString` method
-Runnable traceRunnableFromTracer = tracer.wrap(runnable);
-
-
-
-

Example for Callable:

-
-
-
-
Callable<String> callable = new Callable<String>() {
-	@Override
-	public String call() throws Exception {
-		return someLogic();
-	}
+* [Simple HTTP app](https://github.com/spring-cloud-samples/tests/tree/master/sleuth) that calls back to itself
+* [Using Zipkin](https://github.com/spring-cloud/spring-cloud-sleuth/tree/master/spring-cloud-sleuth-samples/spring-cloud-sleuth-sample-zipkin) to collect traces
+* [Messaging with Spring Integration](https://github.com/spring-cloud/spring-cloud-sleuth/tree/master/spring-cloud-sleuth-samples/spring-cloud-sleuth-sample-messaging)
 
-	@Override
-	public String toString() {
-		return "spanNameFromToStringMethod";
-	}
-};
-// Manual `TraceCallable` creation with explicit "calculateTax" Span name
-Callable<String> traceCallable = new TraceCallable<>(tracer, spanNamer, callable, "calculateTax");
-// Wrapping `Callable` with `Tracer`. The Span name will be taken either from the
-// `@SpanName` annotation or from `toString` method
-Callable<String> traceCallableFromTracer = tracer.wrap(callable);
-
-
-
-

That way you will ensure that a new Span is created and closed for each execution.

-
-
-
-

Hystrix

-
-

Custom Concurrency Strategy

-
-

We’re registering a custom HystrixConcurrencyStrategy -that wraps all Callable instances into their Sleuth representative - -the TraceCallable. The strategy either starts or continues a span depending on the fact whether tracing was already going -on before the Hystrix command was called. To disable the custom Hystrix Concurrency Strategy set the spring.sleuth.hystrix.strategy.enabled to false.

-
-
-
-

Manual Command setting

-
-

Assuming that you have the following HystrixCommand:

-
-
-
-
HystrixCommand<String> hystrixCommand = new HystrixCommand<String>(setter) {
-	@Override
-	protected String run() throws Exception {
-		return someLogic();
-	}
-};
-
-
-
-

In order to pass the tracing information you have to wrap the same logic in the Sleuth version of the HystrixCommand which is the -TraceCommand:

-
-
-
-
TraceCommand<String> traceCommand = new TraceCommand<String>(tracer, traceKeys, setter) {
-	@Override
-	public String doRun() throws Exception {
-		return someLogic();
-	}
-};
-
-
-
-
-
-

RxJava

-
-

We’re registering a custom RxJavaSchedulersHook -that wraps all Action0 instances into their Sleuth representative - -the TraceAction. The hook either starts or continues a span depending on the fact whether tracing was already going -on before the Action was scheduled. To disable the custom RxJavaSchedulersHook set the spring.sleuth.rxjava.schedulers.hook.enabled to false.

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You can define a list of regular expressions for thread names, for which you don’t want a Span to be created. Just provide a comma separated list -of regular expressions in the spring.sleuth.rxjava.schedulers.ignoredthreads property.

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HTTP integration

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Features from this section can be disabled by providing the spring.sleuth.web.enabled property with value equal to false.

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HTTP Filter

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Via the TraceFilter all sampled incoming requests result in creation of a Span. That Span’s name is http: + the path to which - the request was sent. E.g. if the request was sent to /foo/bar then the name will be http:/foo/bar. You can configure which URIs you would - like to skip via the spring.sleuth.web.skipPattern property. If you have ManagementServerProperties on classpath then - its value of contextPath gets appended to the provided skip pattern.

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HandlerInterceptor

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Since we want the span names to be precise we’re using a TraceHandlerInterceptor that either wraps an - existing HandlerInterceptor or is added directly to the list of existing HandlerInterceptors. The - TraceHandlerInterceptor adds a special request attribute to the given HttpServletRequest. If the - the TraceFilter doesn’t see this attribute set it will create a "fallback" span which is an additional - span created on the server side so that the trace is presented properly in the UI. Seeing that most likely - signifies that there is a missing instrumentation. In that case please file an issue in Spring Cloud Sleuth.

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Async Servlet support

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If your controller returns a Callable or a WebAsyncTask Spring Cloud Sleuth will continue the existing span instead of creating a new one.

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HTTP client integration

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Synchronous Rest Template

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We’re injecting a RestTemplate interceptor that ensures that all the tracing information is passed to the requests. Each time a -call is made a new Span is created. It gets closed upon receiving the response. In order to block the synchronous RestTemplate features -just set spring.sleuth.web.client.enabled to false.

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Important
-		 -You have to register RestTemplate as a bean so that the interceptors will get injected. -If you create a RestTemplate instance with a new keyword then the instrumentation WILL NOT work. -
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Asynchronous Rest Template

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Custom instrumentation is set to create and close Spans upon sending and receiving requests. You can customize the ClientHttpRequestFactory -and the AsyncClientHttpRequestFactory by registering your beans. Remember to use tracing compatible implementations (e.g. don’t forget to -wrap ThreadPoolTaskScheduler in a TraceAsyncListenableTaskExecutor). Example of custom request factories:

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Unresolved directive in spring-cloud-sleuth.adoc - include::../../../../spring-cloud-sleuth-core/src/test/java/org/springframework/cloud/sleuth/instrument/web/client/TraceWebAsyncClientAutoConfigurationTest.java[tags=async_template_factories,indent=0]
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To block the AsyncRestTemplate features set spring.sleuth.web.async.client.enabled to false. -To disable creation of the default TraceAsyncClientHttpRequestFactoryWrapper set spring.sleuth.web.async.client.factory.enabled -to false. If you don’t want to create AsyncRestClient at all set spring.sleuth.web.async.client.template.enabled to false.

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Feign

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By default Spring Cloud Sleuth provides integration with feign via the TraceFeignClientAutoConfiguration. You can disable it entirely -by setting spring.sleuth.feign.enabled to false. If you do so then no Feign related instrumentation will take place.

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Part of Feign instrumentation is done via a FeignBeanPostProcessor. You can disable it by providing the spring.sleuth.feign.processor.enabled equal to false. -If you set it like this then Spring Cloud Sleuth will not instrument any of your custom Feign components. All the default instrumentation -however will be still there.

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Asynchronous communication

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@Async annotated methods

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In Spring Cloud Sleuth we’re instrumenting async related components so that the tracing information is passed between threads. -You can disable this behaviour by setting the value of spring.sleuth.async.enabled to false.

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If you annotate your method with @Async then we’ll automatically create a new Span with the following characteristics:

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    the Span name will be the annotated method name

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    the Span will be tagged with that method’s class name and the method name too

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@Scheduled annotated methods

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In Spring Cloud Sleuth we’re instrumenting scheduled method execution so that the tracing information is passed between threads. You can disable this behaviour -by setting the value of spring.sleuth.scheduled.enabled to false.

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If you annotate your method with @Scheduled then we’ll automatically create a new Span with the following characteristics:

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    the Span will be tagged with that method’s class name and the method name too

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If you want to skip Span creation for some @Scheduled annotated classes you can set the -spring.sleuth.scheduled.skipPattern with a regular expression that will match the fully qualified name of the -@Scheduled annotated class.

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Executor, ExecutorService and ScheduledExecutorService

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We’re providing LazyTraceExecutor, TraceableExecutorService and TraceableScheduledExecutorService. Those implementations -are creating Spans each time a new task is submitted, invoked or scheduled.

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Here you can see an example of how to pass tracing information with TraceableExecutorService when working with CompletableFuture:

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CompletableFuture<Long> completableFuture = CompletableFuture.supplyAsync(() -> {
-	// perform some logic
-	return 1_000_000L;
-}, new TraceableExecutorService(executorService,
-		// 'calculateTax' explicitly names the span - this param is optional
-		tracer, traceKeys, spanNamer, "calculateTax"));
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Messaging

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Spring Cloud Sleuth integrates with Spring Integration. It creates spans for publish and -subscribe events. To disable Spring Integration instrumentation, set spring.sleuth.integration.enabled to false.

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Spring Cloud Sleuth up till version 1.0.4 is sending invalid tracing headers when using messaging. Those headers are actually -the same as the ones sent in HTTP (they contain a -) in its name. For the sake of -backwards compatibility in 1.0.4 we’ve started sending both valid and invalid headers. Please upgrade to 1.0.4 because -in Spring Cloud Sleuth 1.1 we will remove the support for the deprecated headers.

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Since 1.0.4 you can provide the spring.sleuth.integration.patterns pattern to explicitly -provide the names of channels that you want to include for tracing. By default all channels -are included.

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Zuul

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We’re registering Zuul filters to propagate the tracing information (the request header is enriched with tracing data). -To disable Zuul support set the spring.sleuth.zuul.enabled property to false.

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Running examples

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You can find the running examples deployed in the Pivotal Web Services. Check them out in the following links:

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- - - \ No newline at end of file +{% endcapture %} + + +{% include project_page.html %} +