From ac2e47e5bcfb8df4b51d7e0bffa49366a5d1b1f6 Mon Sep 17 00:00:00 2001 From: buildmaster Date: Thu, 9 Apr 2020 11:40:43 +0000 Subject: [PATCH] Sync docs from master to gh-pages --- reference/html/README.html | 954 ++++++------------ reference/html/features.html | 413 ++++++-- reference/html/images/zipkin-dependencies.png | Bin 0 -> 46703 bytes .../images/zipkin-error-trace-screenshot.png | Bin 211221 -> 69605 bytes reference/html/images/zipkin-error-trace.png | Bin 0 -> 67467 bytes reference/html/images/zipkin-error-traces.png | Bin 118844 -> 36680 bytes .../html/images/zipkin-trace-screenshot.png | Bin 169485 -> 53157 bytes reference/html/index.html | 914 ++++++----------- reference/html/overview.html | 170 ++++ reference/html/setup.html | 453 +++++++++ reference/html/spring-cloud-sleuth.html | 914 ++++++----------- .../htmlsingle/images/zipkin-dependencies.png | Bin 0 -> 46703 bytes .../images/zipkin-error-trace-screenshot.png | Bin 211221 -> 69605 bytes .../htmlsingle/images/zipkin-error-trace.png | Bin 0 -> 67467 bytes .../htmlsingle/images/zipkin-error-traces.png | Bin 118844 -> 36680 bytes .../images/zipkin-trace-screenshot.png | Bin 169485 -> 53157 bytes 16 files changed, 1863 insertions(+), 1955 deletions(-) create mode 100644 reference/html/images/zipkin-dependencies.png create mode 100644 reference/html/images/zipkin-error-trace.png create mode 100644 reference/html/overview.html create mode 100644 reference/html/setup.html create mode 100644 reference/htmlsingle/images/zipkin-dependencies.png create mode 100644 reference/htmlsingle/images/zipkin-error-trace.png diff --git a/reference/html/README.html b/reference/html/README.html index 1ebde52f9..5dc947bd8 100644 --- a/reference/html/README.html +++ b/reference/html/README.html @@ -119,30 +119,26 @@ $(globalSwitch);
  • Quick Start
    • -
  • Introduction +
  • Overview
    • -
  • Additional Resources
    • -
  • 1. Features
    • -
  • 2. Building +
  • 1. Building
    • -
  • 3. Contributing +
  • 2. Contributing
    • @@ -172,12 +168,21 @@ $(globalSwitch);

    Spring Cloud Sleuth

    -

    Spring Cloud Sleuth is a distributed tracing tool for Spring Cloud. It borrows from Dapper, Zipkin, and HTrace.

    +

    Spring Cloud Sleuth provides Spring Boot auto-configuration for distributed +tracing. Underneath, Spring Cloud Sleuth is a layer over a Tracer library named +Brave.

    +
    +
    +

    Sleuth configures everything you need to get started. This includes where trace +data (spans) are reported to, how many traces to keep (sampling), if remote +fields (baggage) are sent, and which libraries are traced.

    Quick Start

    -

    Add sleuth to the classpath of a Spring Boot application (see “Adding Sleuth to the Project” for Maven and Gradle examples), and you can see the correlation data being collected in logs, as long as you are logging requests.

    +

    Add sleuth to the classpath of a Spring Boot application +(see “Adding Sleuth to the Project” for Maven and Gradle examples), and you will +see trace IDs in logs.

    For example, consider the following HTTP handler:

    @@ -187,6 +192,7 @@ $(globalSwitch); 
    @RestController
 public class DemoController {
   private static Logger log = LoggerFactory.getLogger(DemoController.class);
+
   @RequestMapping("/")
   public String home() {
     log.info("Handling home");
@@ -197,7 +203,8 @@ public class DemoController {
    -

    If you add that handler to a controller, you can see the calls to home() being traced in the logs and in Zipkin, if Zipkin is configured.

    +

    If you add that handler to a controller, you can see the calls to home() +being traced in the logs as well in Zipkin, if configured.

    @@ -219,7 +226,8 @@ could set logging.level.org.springframework.web.servlet.DispatcherServlet=
    -Set spring.application.name=myService (for instance) to see the service name as well as the trace and span IDs. +Set spring.application.name=myService (for instance) to see the service +name as well as the trace and span IDs.
    @@ -228,185 +236,70 @@ Set spring.application.name=myService (for instance) to see the ser
    -

    Introduction

    +

    Overview

    -

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

    +

    Spring Cloud Sleuth provides Spring Boot auto-configuration for distributed +tracing. Underneath, Spring Cloud Sleuth is a layer over a Tracer library named +Brave.

    +
    +
    +

    Sleuth configures everything you need to get started. This includes where trace +data (spans) are reported to, how many traces to keep (sampling), if remote +fields (baggage) are sent, and which libraries are traced.

    +
    +
    +

    We maintain an example app where two Spring Boot services collaborate on an +HTTP request. Sleuth configures these apps, so that timing of these requests are +recorded into Zipkin, a distributed tracing system. Tracing +UIs visualize latency, such as time in one service vs waiting for other +services.

    +
    +
    +

    Here’s an example of what it looks like:

    +
    +
    +
    +Zipkin Traces +
    +
    +
    +

    The source repository of this +example includes demonstrations ofmany things, including WebFlux and messaging. +Most features require only a property or dependency change to work. These +snippets showcase the value of Spring Cloud Sleuth: Through auto-configuration, +Sleuth make getting started with distributed tracing easy!

    +
    +
    +

    To keep things simple, the same example is used throughout documentation using +basic HTTP communication.

    -

    Terminology

    +

    .1. Features

    -

    Spring Cloud Sleuth borrows Dapper’s terminology.

    +

    Sleuth sets up instrumentation not only to track timing, but also to catch +errors so that they can be analyzed or correlated with logs. This works the +same way regardless of if the error came from a common instrumented library, +such as RestTemplate, or your own code annotated with @NewSpan or similar.

    -

    Span: The basic unit of work. For example, sending an RPC is a new span, as is sending a response to an RPC. -Spans 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 IDs (normally IP addresses).

    -
    -
    -

    Spans can be 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.

    -
    -
    - - - - - -
    - - -The initial span that starts a trace is called a root span. The value of the ID -of that span is equal to the trace ID. -
    -
    -
    -

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

    -
    -
    -

    Annotation: Used to record the existence of an event in time. With -Brave instrumentation, we no longer need to set special events -for Zipkin to understand who the client and server are, where -the request started, and where it ended. For learning purposes, -however, we mark these events to highlight what kind -of an action took place.

    -
    -
    -
      -
    • -

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

      -
      • -
    • -

      sr: Server Received: The server side got the request and started processing it. -Subtracting the cs timestamp from this timestamp reveals the network latency.

      -
      • -
    • -

      ss: Server Sent. Annotated upon completion of request processing (when the response got sent back to the client). -Subtracting the sr timestamp from this timestamp reveals the time needed by the server side to process the request.

      -
      • -
    • -

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

      -
      • -
    -
    -
    -

    The following image shows how Span and Trace look in a system, together with the Zipkin annotations:

    -
    -
    -
    -Trace Info propagation -
    -
    -
    -

    Each color of a note signifies a span (there are seven spans - from A to G). -Consider the following note:

    -
    -
    -
    -
    Trace Id = X
-Span Id = D
-Client Sent
    -
    -
    -
    -

    This note indicates that the current span has Trace Id set to X and Span Id set to D. -Also, the Client Sent event took place.

    -
    -
    -

    The following image shows how parent-child relationships of spans look:

    -
    -
    -
    -Parent child relationship -
    -
    -
    -
    -

    Purpose

    -
    -

    The following sections refer to the example shown in the preceding image.

    +

    Below, we’ll use the word Zipkin to describe the tracing system, and include +Zipkin screenshots. However, most services accepting Zipkin’s format[zipkin.io/zipkin-api/#/default/post_spans], +have similar base features. Sleuth can also be configured to send data in other +formats, something detailed later.

    -

    Distributed Tracing with Zipkin

    +

    .1.1. Contextualizing errors

    -

    This example has seven spans. -If you go to traces in Zipkin, you can see this number in the second trace, as shown in the following image:

    -
    -
    -
    -Traces -
    +

    Without distributed tracing, it can be difficult to understand the impact of a +an exception. For example, it can be hard to know if a specific request caused +the caller to fail or not.

    -

    However, if you pick a particular trace, you can see four spans, as shown in the following image:

    -
    -
    -
    -Traces Info propagation -
    -
    -
    - - - - - -
    - - -When you pick a particular trace, you see merged spans. -That means that, if there were two spans sent to Zipkin with Server Received and Server Sent or Client Received and Client Sent annotations, they are presented as a single span. -
    +

    Zipkin reduces time in triage by contextualizing errors and delays.

    -

    Why is there a difference between the seven and four spans in this case?

    -
    -
    -
      -
    • -

      One span comes from the http:/start span. It has the Server Received (sr) and Server Sent (ss) annotations.

      -
      • -
    • -

      Two spans come from the RPC call from service1 to service2 to the http:/foo endpoint. -The Client Sent (cs) and Client Received (cr) events took place on the service1 side. -Server Received (sr) and Server Sent (ss) events took place on the service2 side. -These two spans form one logical span related to an RPC call.

      -
      • -
    • -

      Two spans come from the RPC call from service2 to service3 to the http:/bar endpoint. -The Client Sent (cs) and Client Received (cr) events took place on the service2 side. -The Server Received (sr) and Server Sent (ss) events took place on the service3 side. -These two spans form one logical span related to an RPC call.

      -
      • -
    • -

      Two spans come from the RPC call from service2 to service4 to the http:/baz endpoint. -The Client Sent (cs) and Client Received (cr) events took place on the service2 side. -Server Received (sr) and Server Sent (ss) events took place on the service4 side. -These two spans form one logical span related to an RPC call.

      -
      • -
    -
    -
    -

    So, if we count the physical spans, we have one from http:/start, two from service1 calling service2, two from service2 -calling service3, and two from service2 calling service4. In sum, we have a total of seven spans.

    -
    -
    -

    Logically, we see the information of four total Spans because we have one span related to the incoming request -to service1 and three spans related to RPC calls.

    -
    -
    -
    -

    Visualizing errors

    -
    -

    Zipkin lets you visualize errors in your trace. -When an exception was thrown and was not caught, we set proper tags on the span, which Zipkin can then properly colorize. -You could see in the list of traces one trace that is red. That appears because an exception was thrown.

    -
    -
    -

    If you click that trace, you see a similar picture, as follows:

    +

    Requests colored red in the search screen failed:

    @@ -414,7 +307,8 @@ You could see in the list of traces one trace that is red. That appears because
    -

    If you then click on one of the spans, you see the following

    +

    If you then click on one of the traces, you can understand if the failure +happened before the request hit another service or not:

    @@ -422,65 +316,34 @@ You could see in the list of traces one trace that is red. That appears because
    -

    The span shows the reason for the error and the whole stack trace related to it.

    +

    For example, the above error happened in the "backend" service, and caused the +"frontend" service to fail.

    -

    Distributed Tracing with Brave

    +

    .1.2. Log correlation

    -

    Starting with version 2.0.0, Spring Cloud Sleuth uses Brave as the tracing library. -Consequently, Sleuth no longer takes care of storing the context but delegates that work to Brave.

    +

    Sleuth configures the logging context with variables including the service name +(%{spring.zipkin.service.name}) and the trace ID (%{traceId}). These help +you connect logs with distributed traces and allow you choice in what tools you +use to troubleshoot your services.

    -

    Due to the fact that Sleuth had different naming and tagging conventions than Brave, we decided to follow Brave’s conventions from now on.

    -
    -
    -
    -

    Live examples

    -
    -
    -Zipkin deployed on Pivotal Web Services -
    -
    Click the Pivotal Web Services icon to see it live!Click the Pivotal Web Services icon to see it live!
    -
    -
    -

    Click here to see it live!

    -
    -
    -

    The dependency graph in Zipkin should resemble the following image:

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

    Click here to see it live!

    -
    -
    -
    -

    Log correlation

    -
    -

    When using grep to read the logs of those four applications by scanning for a trace ID equal to (for example) 2485ec27856c56f4, you get output resembling the following:

    +

    Once you find any log with an error, you can look for the trace ID in the +message. Paste that into Zipkin to visualize the entire trace, regardless of +how many services the first request ended up hitting.

    -
    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]]
    +
    backend.log:  2020-04-09 17:45:40.516 ERROR [backend,5e8eeec48b08e26882aba313eb08f0a4,dcc1df555b5777b3,true] 97203 --- [nio-9000-exec-1] o.s.c.s.i.web.ExceptionLoggingFilter     : Uncaught exception thrown
+frontend.log:2020-04-09 17:45:40.574 ERROR [frontend,5e8eeec48b08e26882aba313eb08f0a4,82aba313eb08f0a4,true] 97192 --- [nio-8081-exec-2] o.s.c.s.i.web.ExceptionLoggingFilter     : Uncaught exception thrown
    +

    Above, you’ll notice the trace ID is 5e8eeec48b08e26882aba313eb08f0a4, for +example. This log configuration was automatically setup by Sleuth.

    +
    +

    If you use a log aggregating tool (such as Kibana, Splunk, and others), you can order the events that took place. An example from Kibana would resemble the following image:

    @@ -537,7 +400,7 @@ If you want to use Grok together with the logs from Cloud Foundry, you have to u
    -
    JSON Logback with Logstash
    +
    JSON Logback with Logstash

    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 so, you have to do the following (for readability, we pass the dependencies in the groupId:artifactId:version notation).

    @@ -565,80 +428,80 @@ To do so, you have to do the following (for readability, we pass the dependencie 
    <?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}"/>​
+    <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}"/>​
 
-	<!-- You can override this to have a custom pattern -->
-	<property name="CONSOLE_LOG_PATTERN"
-			  value="%clr(%d{yyyy-MM-dd HH:mm:ss.SSS}){faint} %clr(${LOG_LEVEL_PATTERN:-%5p}) %clr(${PID:- }){magenta} %clr(---){faint} %clr([%15.15t]){faint} %clr(%-40.40logger{39}){cyan} %clr(:){faint} %m%n${LOG_EXCEPTION_CONVERSION_WORD:-%wEx}"/>
+    <!-- You can override this to have a custom pattern -->
+    <property name="CONSOLE_LOG_PATTERN"
+              value="%clr(%d{yyyy-MM-dd HH:mm:ss.SSS}){faint} %clr(${LOG_LEVEL_PATTERN:-%5p}) %clr(${PID:- }){magenta} %clr(---){faint} %clr([%15.15t]){faint} %clr(%-40.40logger{39}){cyan} %clr(:){faint} %m%n${LOG_EXCEPTION_CONVERSION_WORD:-%wEx}"/>
 
-	<!-- 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>DEBUG</level>
-		</filter>
-		<encoder>
-			<pattern>${CONSOLE_LOG_PATTERN}</pattern>
-			<charset>utf8</charset>
-		</encoder>
-	</appender>
+    <!-- Appender to log to console -->
+    <appender name="console" class="ch.qos.logback.core.ConsoleAppender">
+        <filter class="ch.qos.logback.classic.filter.ThresholdFilter">
+            <!-- Minimum logging level to be presented in the console logs-->
+            <level>DEBUG</level>
+        </filter>
+        <encoder>
+            <pattern>${CONSOLE_LOG_PATTERN}</pattern>
+            <charset>utf8</charset>
+        </encoder>
+    </appender>
 
-	<!-- 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:-}",
-						"parent": "%X{X-B3-ParentSpanId:-}",
-						"exportable": "%X{X-Span-Export:-}",
-						"baggage": "%X{key:-}",
-						"pid": "${PID:-}",
-						"thread": "%thread",
-						"class": "%logger{40}",
-						"rest": "%message"
-						}
-					</pattern>
-				</pattern>
-			</providers>
-		</encoder>
-	</appender>
-	​
-	<root level="INFO">
-		<appender-ref ref="console"/>
-		<!-- uncomment this to have also JSON logs -->
-		<!--<appender-ref ref="logstash"/>-->
-		<!--<appender-ref ref="flatfile"/>-->
-	</root>
+    <!-- Appender to log to file -->​
+    <appender name="flatfile" class="ch.qos.logback.core.rolling.RollingFileAppender">
+        <file>${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": "${springAppName:-}",
+                        "trace": "%X{X-B3-TraceId:-}",
+                        "span": "%X{X-B3-SpanId:-}",
+                        "parent": "%X{X-B3-ParentSpanId:-}",
+                        "exportable": "%X{X-Span-Export:-}",
+                        "baggage": "%X{key:-}",
+                        "pid": "${PID:-}",
+                        "thread": "%thread",
+                        "class": "%logger{40}",
+                        "rest": "%message"
+                        }
+                    </pattern>
+                </pattern>
+            </providers>
+        </encoder>
+    </appender>
+    ​
+    <root level="INFO">
+        <appender-ref ref="console"/>
+        <!-- uncomment this to have also JSON logs -->
+        <!--<appender-ref ref="logstash"/>-->
+        <!--<appender-ref ref="flatfile"/>-->
+    </root>
 </configuration>
    @@ -674,33 +537,41 @@ Otherwise, your custom logback file does not properly read the property.
    -

    Propagating Span Context

    +

    .1.3. Service Dependency Graph

    -

    The span context is the state that must get propagated to any child spans across process boundaries. -Part of the Span Context is the Baggage. The trace and span IDs are a required part of the span context. -Baggage is an optional part.

    +

    When you consider distributed tracing tracks requests, it makes sense that +trace data can paint a picture of your architecture.

    -

    Baggage is a set of key:value pairs stored in the span context. -Baggage travels together with the trace and is attached to every span. -Spring Cloud Sleuth understands that a header is baggage-related if the HTTP header is prefixed with baggage- and, for messaging, it starts with baggage_.

    -
    -
    - - - - - -
    - - -There is currently no limitation of the count or size of baggage items. -However, keep in mind that too many can decrease system throughput or increase RPC latency. -In extreme cases, too much baggage can crash the application, due to exceeding transport-level message or header capacity. -
    +

    Zipkin includes a tool to build service dependency diagrams from traces, +including the count of calls and how many errors exist.

    -

    The following example shows setting baggage on a span:

    +

    The example application will make a simple diagram like this, but your real +environment diagram may be more complex. +image::https://raw.githubusercontent.com/spring-cloud/spring-cloud-sleuth/master/docs/src/main/asciidoc/images/zipkin-depedendencies.png[Zipkin Dependencies]

    +
    +
    +

    Note: Production environments will generate a lot of data. You will likely +need to run a separate service to aggregate the dependency graph. You can learn +more here.

    +
    +
    +
    +

    .1.4. Request scoped properties (Baggage)

    +
    +

    Distributed tracing works by propagating fields inside and across services that +connect the trace together: traceId and spanId notably. The context that holds +these fields can optionally push other fields that need to be consistent +regardless of many services are touched. The simple name for these extra fields +is "Baggage".

    +
    +
    +

    Sleuth allows you to define which baggage are permitted to exist in the trace +context, including what header names are used.

    +
    +
    +

    The following example shows setting baggage values:

    @@ -709,49 +580,34 @@ BUSINESS_PROCESS.updateValue(initialSpan.context(), "ALM"); COUNTRY_CODE.updateValue(initialSpan.context(), "FO");
    +
    + + + + + +
    + + +There is currently no limitation of the count or size of baggage +items. Keep in mind that too many can decrease system throughput or increase +RPC latency. In extreme cases, too much baggage can crash the application, due +to exceeding transport-level message or header capacity. +
    +
    -
    Baggage versus Span Tags
    +
    Baggage versus Tags
    -

    Baggage travels with the trace (every child span contains the baggage of its parent). -Zipkin has no knowledge of baggage and does not receive that information.

    -
    -
    - - - - - -
    - - -Starting from Sleuth 2.0.0 you have to pass the baggage key names explicitly -in your project configuration. Read more about that setup here -
    +

    Like trace IDs, Baggage is attached to messages or requests, usually as +headers. Tags are key value pairs sent in a Span to Zipkin. Baggage values are +not added spans by default, which means you can’t search based on Baggage +unless you opt-in.

    -

    Tags are attached to a specific span. In other words, they are presented only for that particular span. -However, you can search by tag to find the trace, assuming a span having the searched tag value exists.

    -
    -
    -

    If you want to be able to lookup a span based on baggage, you should add a corresponding entry as a tag in the root span.

    -
    -
    - - - - - -
    - - -The span must be in scope. -
    -
    -
    -

    The following listing shows integration tests that use baggage:

    +

    To make baggage also tags, use the property spring.sleuth.baggage.tag-fields +like so:

    -
    The setup
    spring:
   sleuth:
@@ -763,17 +619,11 @@ The span must be in scope.
         - country-code
    -
    -
    The code
    -
    -
    Tags.BAGGAGE_FIELD.tag(BUSINESS_PROCESS, initialSpan);
    -
    -
    -

    Adding Sleuth to the Project

    +

    .2. Adding Sleuth to the Project

    This section addresses how to add Sleuth to your project with either Maven or Gradle.

    @@ -790,78 +640,7 @@ To ensure that your application name is properly displayed in Zipkin, set the
    -

    Only Sleuth (log correlation)

    -
    -

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

    -
    -
    -

    The following example shows how to add Sleuth with Maven:

    -
    -
    -
    Maven
    -
    -
    <dependencyManagement> (1)
-      <dependencies>
-          <dependency>
-              <groupId>org.springframework.cloud</groupId>
-              <artifactId>spring-cloud-dependencies</artifactId>
-              <version>${release.train.version}</version>
-              <type>pom</type>
-              <scope>import</scope>
-          </dependency>
-      </dependencies>
-</dependencyManagement>
-
-<dependency> (2)
-    <groupId>org.springframework.cloud</groupId>
-    <artifactId>spring-cloud-starter-sleuth</artifactId>
-</dependency>
    -
    -
    -
    - - - - - - - - - -
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    -
    -
    -

    The following example shows how to add Sleuth with Gradle:

    -
    -
    -
    Gradle
    -
    -
    dependencyManagement { (1)
-    imports {
-        mavenBom "org.springframework.cloud:spring-cloud-dependencies:${releaseTrainVersion}"
-    }
-}
-
-dependencies { (2)
-    compile "org.springframework.cloud:spring-cloud-starter-sleuth"
-}
    -
    -
    -
    - - - - - - - - - -
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    -
    -
    -
    -

    Sleuth with Zipkin via HTTP

    +

    .2.1. Sleuth with Zipkin via HTTP

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

    @@ -932,7 +711,7 @@ dependencies { (2)
    -

    Sleuth with Zipkin over RabbitMQ or Kafka

    +

    .2.2. Sleuth with Zipkin over RabbitMQ or Kafka

    If you want to use RabbitMQ or Kafka instead of HTTP, add the spring-rabbit or spring-kafka dependency. The default destination name is zipkin.

    @@ -1037,9 +816,8 @@ dependencies {
    - -
    -

    Overriding the auto-configuration of Zipkin

    +
    +

    .2.3. Overriding the auto-configuration of Zipkin

    Spring Cloud Sleuth supports sending traces to multiple tracing systems as of version 2.1.0. In order to get this to work, every tracing system needs to have a Reporter<Span> and Sender. @@ -1051,212 +829,130 @@ To do this you can use respectively ZipkinAutoConfiguration.REPORTER_BEAN_ 

    @Configuration
 protected static class MyConfig {
 
-	@Bean(ZipkinAutoConfiguration.REPORTER_BEAN_NAME)
-	Reporter<zipkin2.Span> myReporter() {
-		return AsyncReporter.create(mySender());
-	}
+    @Bean(ZipkinAutoConfiguration.REPORTER_BEAN_NAME)
+    Reporter<zipkin2.Span> myReporter() {
+        return AsyncReporter.create(mySender());
+    }
 
-	@Bean(ZipkinAutoConfiguration.SENDER_BEAN_NAME)
-	MySender mySender() {
-		return new MySender();
-	}
+    @Bean(ZipkinAutoConfiguration.SENDER_BEAN_NAME)
+    MySender mySender() {
+        return new MySender();
+    }
 
-	static class MySender extends Sender {
+    static class MySender extends Sender {
 
-		private boolean spanSent = false;
+        private boolean spanSent = false;
 
-		boolean isSpanSent() {
-			return this.spanSent;
-		}
+        boolean isSpanSent() {
+            return this.spanSent;
+        }
 
-		@Override
-		public Encoding encoding() {
-			return Encoding.JSON;
-		}
+        @Override
+        public Encoding encoding() {
+            return Encoding.JSON;
+        }
 
-		@Override
-		public int messageMaxBytes() {
-			return Integer.MAX_VALUE;
-		}
+        @Override
+        public int messageMaxBytes() {
+            return Integer.MAX_VALUE;
+        }
 
-		@Override
-		public int messageSizeInBytes(List<byte[]> encodedSpans) {
-			return encoding().listSizeInBytes(encodedSpans);
-		}
+        @Override
+        public int messageSizeInBytes(List<byte[]> encodedSpans) {
+            return encoding().listSizeInBytes(encodedSpans);
+        }
 
-		@Override
-		public Call<Void> sendSpans(List<byte[]> encodedSpans) {
-			this.spanSent = true;
-			return Call.create(null);
-		}
+        @Override
+        public Call<Void> sendSpans(List<byte[]> encodedSpans) {
+            this.spanSent = true;
+            return Call.create(null);
+        }
 
-	}
+    }
 
 }
    - - -
    -

    Additional Resources

    -
    +
    +

    .2.4. Only Sleuth (log correlation)

    -

    You can watch a video of Reshmi Krishna and Marcin Grzejszczak talking about Spring Cloud -Sleuth and Zipkin by clicking here.

    +

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

    -

    You can check different setups of Sleuth and Brave in the openzipkin/sleuth-webmvc-example repository.

    +

    The following example shows how to add Sleuth with Maven:

    -
    -
    -
    -

    1. 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, as shown in the following example logs:

      -
      +
      +
      Maven
      -
      2016-02-02 15:30:57.902  INFO [bar,6bfd228dc00d216b,6bfd228dc00d216b] 23030 --- [nio-8081-exec-3] ...
-2016-02-02 15:30:58.372 ERROR [bar,6bfd228dc00d216b,6bfd228dc00d216b] 23030 --- [nio-8081-exec-3] ...
-2016-02-02 15:31:01.936  INFO [bar,46ab0d418373cbc9,46ab0d418373cbc9] 23030 --- [nio-8081-exec-4] ...
      +
      <dependencyManagement> (1)
+      <dependencies>
+          <dependency>
+              <groupId>org.springframework.cloud</groupId>
+              <artifactId>spring-cloud-dependencies</artifactId>
+              <version>${release.train.version}</version>
+              <type>pom</type>
+              <scope>import</scope>
+          </dependency>
+      </dependencies>
+</dependencyManagement>
+
+<dependency> (2)
+    <groupId>org.springframework.cloud</groupId>
+    <artifactId>spring-cloud-starter-sleuth</artifactId>
+</dependency>
      +
      + + + + + + + + + +
      1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
      2Add the dependency to spring-cloud-starter-sleuth.
      +
      -

      Notice the [appname,traceId,spanId] entries from the MDC:

      +

      The following example shows how to add Sleuth with Gradle:

      -
      -
        -
      • -

        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.

        -
        • -
      +
      +
      Gradle
      +
      +
      dependencyManagement { (1)
+    imports {
+        mavenBom "org.springframework.cloud:spring-cloud-dependencies:${releaseTrainVersion}"
+    }
+}
+
+dependencies { (2)
+    compile "org.springframework.cloud:spring-cloud-starter-sleuth"
+}
      -
      • -
    • -

      Provides an abstraction over common distributed tracing data models: traces, spans (forming a DAG), annotations, and key-value annotations. -Spring Cloud Sleuth is loosely based on HTrace but is compatible with Zipkin (Dapper).

      -
      • -
    • -

      Sleuth records timing information to aid in latency analysis. -By 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. -To that end, Sleuth:

      -
      -
        -
      • -

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

        -
        • -
      • -

        Includes opinionated instrumentation of layers such as HTTP.

        -
        • -
      • -

        Includes a 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, and Feign client).

      -
      • -
    • -

      Sleuth includes default logic to join a trace across HTTP or messaging boundaries. -For example, HTTP propagation works over Zipkin-compatible request headers.

      -
      • -
    • -

      Sleuth can propagate context (also known as baggage) between processes. -Consequently, if you set a baggage element on a Span, it is sent downstream to other processes over either HTTP or messaging.

      -
      • -
    • -

      Provides a way to create or continue spans and add tags and logs through annotations.

      -
      • -
    • -

      If spring-cloud-sleuth-zipkin is on the classpath, the app generates and collects Zipkin-compatible traces. -By default, it sends them over HTTP to a Zipkin server on localhost (port 9411). -You can configure the location of the service by setting spring.zipkin.baseUrl.

      -
      -
        -
      • -

        If you depend on spring-rabbit, your app sends traces to a RabbitMQ broker instead of HTTP.

        -
        • -
      • -

        If you depend on spring-kafka, and set spring.zipkin.sender.type: kafka, your app sends traces to a Kafka broker instead of HTTP.

        -
        • -
      -
      -
      • -
    -
    -
    +
    - - + + + + + +
    - - -spring-cloud-sleuth-stream is deprecated and should no longer be used. -1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    -
    -
    -
    - - - - - -
    - - -The SLF4J MDC is always set and logback users immediately see the trace and span IDs in logs per the example -shown earlier. -Other logging systems have to configure their own formatter to get the same result. -The default is as follows: -logging.pattern.level set to %5p [${spring.zipkin.service.name:${spring.application.name:-}},%X{traceId:-},%X{spanId:-}] -(this is a Spring Boot feature for logback users). -If you do not use SLF4J, this pattern is NOT automatically applied. -
    -
    -
    - - - - - -
    - - -Starting with version 3.0.0, the logging pattern has changed. -We’ve converted the MDC entries from B3 to non B3 keys (e.g. X-B3-TraceId to traceId). -
    -

    2. Building

    +

    1. Building

    -

    2.1. Basic Compile and Test

    +

    1.1. Basic Compile and Test

    To build the source you will need to install JDK 1.7.

    @@ -1334,7 +1030,7 @@ If all else fails, build with the command from .travis.yml (usually
    -

    2.2. Documentation

    +

    1.2. Documentation

    The spring-cloud-build module has a "docs" profile, and if you switch that on it will try to build asciidoc sources from @@ -1347,7 +1043,7 @@ a modified file in the correct place. Just commit it and push the change.

    -

    2.3. Working with the code

    +

    1.3. Working with the code

    If you don’t have an IDE preference we would recommend that you use Spring Tools Suite or @@ -1356,7 +1052,7 @@ a modified file in the correct place. Just commit it and push the change.

    should also work without issue as long as they use Maven 3.3.3 or better.

    -

    2.3.1. Importing into eclipse with m2eclipse

    +

    1.3.1. Importing into eclipse with m2eclipse

    We recommend the m2eclipse eclipse plugin when working with eclipse. If you don’t already have m2eclipse installed it is available from the "eclipse @@ -1383,7 +1079,7 @@ pom into your settings.xml.

    -

    2.3.2. Importing into eclipse without m2eclipse

    +

    1.3.2. Importing into eclipse without m2eclipse

    If you prefer not to use m2eclipse you can generate eclipse project metadata using the following command:

    @@ -1417,7 +1113,7 @@ so, your app breaks during the Maven build.
    -

    3. Contributing

    +

    2. Contributing

    Spring Cloud is released under the non-restrictive Apache 2.0 license, @@ -1427,7 +1123,7 @@ to contribute even something trivial please do not hesitate, but follow the guidelines below.

    -

    3.1. Sign the Contributor License Agreement

    +

    2.1. Sign the Contributor License Agreement

    Before we accept a non-trivial patch or pull request we will need you to sign the Contributor License Agreement. @@ -1438,7 +1134,7 @@ given the ability to merge pull requests.

    -

    3.2. Code of Conduct

    +

    2.2. Code of Conduct

    This project adheres to the Contributor Covenant code of conduct. By participating, you are expected to uphold this code. Please report @@ -1446,7 +1142,7 @@ unacceptable behavior to spri

    -

    3.3. Code Conventions and Housekeeping

    +

    2.3. Code Conventions and Housekeeping

    None of these is essential for a pull request, but they will all help. They can also be added after the original pull request but before a merge.

    @@ -1494,7 +1190,7 @@ message (where XXXX is the issue number).

    -

    3.4. Checkstyle

    +

    2.4. Checkstyle

    Spring Cloud Build comes with a set of checkstyle rules. You can find them in the spring-cloud-build-tools module. The most notable files under the module are:

    @@ -1527,7 +1223,7 @@ message (where XXXX is the issue number).

    -

    3.4.1. Checkstyle configuration

    +

    2.4.1. Checkstyle configuration

    Checkstyle rules are disabled by default. To add checkstyle to your project just define the following properties and plugins.

    @@ -1617,9 +1313,9 @@ $ touch .springformat
    -

    3.5. IDE setup

    +

    2.5. IDE setup

    -

    3.5.1. Intellij IDEA

    +

    2.5.1. Intellij IDEA

    In order to setup Intellij you should import our coding conventions, inspection profiles and set up the checkstyle plugin. The following files can be found in the Spring Cloud Build project.

    diff --git a/reference/html/features.html b/reference/html/features.html index 71c0fc161..e621ca9c5 100644 --- a/reference/html/features.html +++ b/reference/html/features.html @@ -113,118 +113,271 @@ $(globalSwitch);
    -
    -

    1. 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, as shown in the following example logs:

      -
      +
      +

      1. Features

      +
      +

      Sleuth sets up instrumentation not only to track timing, but also to catch +errors so that they can be analyzed or correlated with logs. This works the +same way regardless of if the error came from a common instrumented library, +such as RestTemplate, or your own code annotated with @NewSpan or similar.

      +
      +
      +

      Below, we’ll use the word Zipkin to describe the tracing system, and include +Zipkin screenshots. However, most services accepting Zipkin’s format[zipkin.io/zipkin-api/#/default/post_spans], +have similar base features. Sleuth can also be configured to send data in other +formats, something detailed later.

      +
      +
      +

      1.1. Contextualizing errors

      +
      +

      Without distributed tracing, it can be difficult to understand the impact of a +an exception. For example, it can be hard to know if a specific request caused +the caller to fail or not.

      +
      +
      +

      Zipkin reduces time in triage by contextualizing errors and delays.

      +
      +
      +

      Requests colored red in the search screen failed:

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

      Notice the [appname,traceId,spanId] entries from the MDC:

      +

      If you then click on one of the traces, you can understand if the failure +happened before the request hit another service or not:

      -
      -
        -
      • -

        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.

        -
        • -
      +
      +
      +Error Traces Info propagation
      -
      • -
    • -

      Provides an abstraction over common distributed tracing data models: traces, spans (forming a DAG), annotations, and key-value annotations. -Spring Cloud Sleuth is loosely based on HTrace but is compatible with Zipkin (Dapper).

      -
      • -
    • -

      Sleuth records timing information to aid in latency analysis. -By 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. -To that end, Sleuth:

      -
      -
        -
      • -

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

        -
        • -
      • -

        Includes opinionated instrumentation of layers such as HTTP.

        -
        • -
      • -

        Includes a 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, and Feign client).

      -
      • -
    • -

      Sleuth includes default logic to join a trace across HTTP or messaging boundaries. -For example, HTTP propagation works over Zipkin-compatible request headers.

      -
      • -
    • -

      Sleuth can propagate context (also known as baggage) between processes. -Consequently, if you set a baggage element on a Span, it is sent downstream to other processes over either HTTP or messaging.

      -
      • -
    • -

      Provides a way to create or continue spans and add tags and logs through annotations.

      -
      • -
    • -

      If spring-cloud-sleuth-zipkin is on the classpath, the app generates and collects Zipkin-compatible traces. -By default, it sends them over HTTP to a Zipkin server on localhost (port 9411). -You can configure the location of the service by setting spring.zipkin.baseUrl.

      -
      -
        -
      • -

        If you depend on spring-rabbit, your app sends traces to a RabbitMQ broker instead of HTTP.

        -
        • -
      • -

        If you depend on spring-kafka, and set spring.zipkin.sender.type: kafka, your app sends traces to a Kafka broker instead of HTTP.

        -
        • -
      +
      +

      For example, the above error happened in the "backend" service, and caused the +"frontend" service to fail.

      -
      • -
    -
    +
    +

    1.2. Log correlation

    +
    +

    Sleuth configures the logging context with variables including the service name +(%{spring.zipkin.service.name}) and the trace ID (%{traceId}). These help +you connect logs with distributed traces and allow you choice in what tools you +use to troubleshoot your services.

    +
    +
    +

    Once you find any log with an error, you can look for the trace ID in the +message. Paste that into Zipkin to visualize the entire trace, regardless of +how many services the first request ended up hitting.

    +
    +
    +
    +
    backend.log:  2020-04-09 17:45:40.516 ERROR [backend,5e8eeec48b08e26882aba313eb08f0a4,dcc1df555b5777b3,true] 97203 --- [nio-9000-exec-1] o.s.c.s.i.web.ExceptionLoggingFilter     : Uncaught exception thrown
+frontend.log:2020-04-09 17:45:40.574 ERROR [frontend,5e8eeec48b08e26882aba313eb08f0a4,82aba313eb08f0a4,true] 97192 --- [nio-8081-exec-2] o.s.c.s.i.web.ExceptionLoggingFilter     : Uncaught exception thrown
    +
    +
    +
    +

    Above, you’ll notice the trace ID is 5e8eeec48b08e26882aba313eb08f0a4, for +example. This log configuration was automatically setup by Sleuth.

    +
    +
    +

    If you use a log aggregating tool (such as Kibana, Splunk, and others), you can order the events that took place. +An example from Kibana would resemble the following image:

    +
    +
    +
    +Log correlation with Kibana +
    +
    +
    +

    If you want to use Logstash, the following listing shows the Grok pattern for Logstash:

    +
    +
    +
    +
    filter {
+  # pattern matching logback pattern
+  grok {
+    match => { "message" => "%{TIMESTAMP_ISO8601:timestamp}\s+%{LOGLEVEL:severity}\s+\[%{DATA:service},%{DATA:trace},%{DATA:span}\]\s+%{DATA:pid}\s+---\s+\[%{DATA:thread}\]\s+%{DATA:class}\s+:\s+%{GREEDYDATA:rest}" }
+  }
+  date {
+    match => ["timestamp", "ISO8601"]
+  }
+  mutate {
+    remove_field => ["timestamp"]
+  }
+}
    +
    +
    +
    - + -spring-cloud-sleuth-stream is deprecated and should no longer be used. +If you want to use Grok together with the logs from Cloud Foundry, you have to use the following pattern:
    +
    +
    +
    filter {
+  # pattern matching logback pattern
+  grok {
+    match => { "message" => "(?m)OUT\s+%{TIMESTAMP_ISO8601:timestamp}\s+%{LOGLEVEL:severity}\s+\[%{DATA:service},%{DATA:trace},%{DATA:span}\]\s+%{DATA:pid}\s+---\s+\[%{DATA:thread}\]\s+%{DATA:class}\s+:\s+%{GREEDYDATA:rest}" }
+  }
+  date {
+    match => ["timestamp", "ISO8601"]
+  }
+  mutate {
+    remove_field => ["timestamp"]
+  }
+}
    +
    +
    +
    +
    JSON Logback with Logstash
    +
    +

    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 so, you have to do the following (for readability, we pass the dependencies in the groupId:artifactId:version notation).

    +
    +
    +

    Dependencies Setup

    +
    +
    +
      +
    1. +

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

      +
      2. +
    2. +

      Add Logstash Logback encode. For example, to use version 4.6, add net.logstash.logback:logstash-logback-encoder:4.6.

      +
      3. +
    +
    +
    +

    Logback Setup

    +
    +
    +

    Consider the following example of a Logback configuration file (named logback-spring.xml).

    +
    +
    +
    +
    <?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}"/>​
+
+    <!-- You can override this to have a custom pattern -->
+    <property name="CONSOLE_LOG_PATTERN"
+              value="%clr(%d{yyyy-MM-dd HH:mm:ss.SSS}){faint} %clr(${LOG_LEVEL_PATTERN:-%5p}) %clr(${PID:- }){magenta} %clr(---){faint} %clr([%15.15t]){faint} %clr(%-40.40logger{39}){cyan} %clr(:){faint} %m%n${LOG_EXCEPTION_CONVERSION_WORD:-%wEx}"/>
+
+    <!-- Appender to log to console -->
+    <appender name="console" class="ch.qos.logback.core.ConsoleAppender">
+        <filter class="ch.qos.logback.classic.filter.ThresholdFilter">
+            <!-- Minimum logging level to be presented in the console logs-->
+            <level>DEBUG</level>
+        </filter>
+        <encoder>
+            <pattern>${CONSOLE_LOG_PATTERN}</pattern>
+            <charset>utf8</charset>
+        </encoder>
+    </appender>
+
+    <!-- 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:-}",
+                        "parent": "%X{X-B3-ParentSpanId:-}",
+                        "exportable": "%X{X-Span-Export:-}",
+                        "baggage": "%X{key:-}",
+                        "pid": "${PID:-}",
+                        "thread": "%thread",
+                        "class": "%logger{40}",
+                        "rest": "%message"
+                        }
+                    </pattern>
+                </pattern>
+            </providers>
+        </encoder>
+    </appender>
+    ​
+    <root level="INFO">
+        <appender-ref ref="console"/>
+        <!-- uncomment this to have also JSON logs -->
+        <!--<appender-ref ref="logstash"/>-->
+        <!--<appender-ref ref="flatfile"/>-->
+    </root>
+</configuration>
    +
    +
    +
    +

    That Logback configuration file:

    +
    • -

      Spring Cloud Sleuth is OpenTracing compatible.

      +

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

      +
      • +
    • +

      Has commented out two additional appenders: console and standard log file.

      +
      • +
    • +

      Has the same logging pattern as the one presented in the previous section.

    @@ -235,17 +388,58 @@ You can configure the location of the service by setting spring.zipkin.bas -The SLF4J MDC is always set and logback users immediately see the trace and span IDs in logs per the example -shown earlier. -Other logging systems have to configure their own formatter to get the same result. -The default is as follows: -logging.pattern.level set to %5p [${spring.zipkin.service.name:${spring.application.name:-}},%X{traceId:-},%X{spanId:-}] -(this is a Spring Boot feature for logback users). -If you do not use SLF4J, this pattern is NOT automatically applied. +If you use a custom logback-spring.xml, you must pass the spring.application.name in the bootstrap rather than the application property file. +Otherwise, your custom logback file does not properly read the property.
    +
    +
    +
    +

    1.3. Service Dependency Graph

    +
    +

    When you consider distributed tracing tracks requests, it makes sense that +trace data can paint a picture of your architecture.

    +
    +
    +

    Zipkin includes a tool to build service dependency diagrams from traces, +including the count of calls and how many errors exist.

    +
    +
    +

    The example application will make a simple diagram like this, but your real +environment diagram may be more complex. +image::https://raw.githubusercontent.com/spring-cloud/spring-cloud-sleuth/master/docs/src/main/asciidoc/images/zipkin-depedendencies.png[Zipkin Dependencies]

    +
    +
    +

    Note: Production environments will generate a lot of data. You will likely +need to run a separate service to aggregate the dependency graph. You can learn +more here.

    +
    +
    +
    +

    1.4. Request scoped properties (Baggage)

    +
    +

    Distributed tracing works by propagating fields inside and across services that +connect the trace together: traceId and spanId notably. The context that holds +these fields can optionally push other fields that need to be consistent +regardless of many services are touched. The simple name for these extra fields +is "Baggage".

    +
    +
    +

    Sleuth allows you to define which baggage are permitted to exist in the trace +context, including what header names are used.

    +
    +
    +

    The following example shows setting baggage values:

    +
    +
    +
    +
    Span initialSpan = this.tracer.nextSpan().name("span").start();
+BUSINESS_PROCESS.updateValue(initialSpan.context(), "ALM");
+COUNTRY_CODE.updateValue(initialSpan.context(), "FO");
    +
    +
    @@ -253,12 +447,39 @@ If you do not use SLF4J, this pattern is NOT automatically applied.
    -Starting with version 3.0.0, the logging pattern has changed. -We’ve converted the MDC entries from B3 to non B3 keys (e.g. X-B3-TraceId to traceId). +There is currently no limitation of the count or size of baggage +items. Keep in mind that too many can decrease system throughput or increase +RPC latency. In extreme cases, too much baggage can crash the application, due +to exceeding transport-level message or header capacity.
    +
    +
    Baggage versus Tags
    +
    +

    Like trace IDs, Baggage is attached to messages or requests, usually as +headers. Tags are key value pairs sent in a Span to Zipkin. Baggage values are +not added spans by default, which means you can’t search based on Baggage +unless you opt-in.

    +
    +
    +

    To make baggage also tags, use the property spring.sleuth.baggage.tag-fields +like so:

    +
    +
    +
    +
    spring:
+  sleuth:
+    baggage:
+      remoteFields:
+        - country-code
+        - x-vcap-request-id
+      tagFields:
+        - country-code
    +
    +
    +
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zZe9JIL1)-T?3ZPluc{vHxYJmWeBP&$-+KmTa6Cg6mm!>>q{E8jc-g~11f0b`|9{s%+918b`y zrX`Kz)suTh-OVO?w6XE@YQEV2t=64L_~^Ky4B1p1ZtO=B-x`Z|$lH&O?q?|uS2Fhg8%p$L$N&HU diff --git a/reference/html/index.html b/reference/html/index.html index 3e0de2a5b..ab3562ddf 100644 --- a/reference/html/index.html +++ b/reference/html/index.html @@ -119,81 +119,77 @@ $(globalSwitch);

    Table of Contents
    @@ -206,185 +202,70 @@ $(globalSwitch);
    -

    1. Introduction

    +

    1. Overview

    -

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

    +

    Spring Cloud Sleuth provides Spring Boot auto-configuration for distributed +tracing. Underneath, Spring Cloud Sleuth is a layer over a Tracer library named +Brave.

    +
    +
    +

    Sleuth configures everything you need to get started. This includes where trace +data (spans) are reported to, how many traces to keep (sampling), if remote +fields (baggage) are sent, and which libraries are traced.

    +
    +
    +

    We maintain an example app where two Spring Boot services collaborate on an +HTTP request. Sleuth configures these apps, so that timing of these requests are +recorded into Zipkin, a distributed tracing system. Tracing +UIs visualize latency, such as time in one service vs waiting for other +services.

    +
    +
    +

    Here’s an example of what it looks like:

    +
    +
    +
    +Zipkin Traces +
    +
    +
    +

    The source repository of this +example includes demonstrations ofmany things, including WebFlux and messaging. +Most features require only a property or dependency change to work. These +snippets showcase the value of Spring Cloud Sleuth: Through auto-configuration, +Sleuth make getting started with distributed tracing easy!

    +
    +
    +

    To keep things simple, the same example is used throughout documentation using +basic HTTP communication.

    -

    1.1. Terminology

    +

    1.1. Features

    -

    Spring Cloud Sleuth borrows Dapper’s terminology.

    +

    Sleuth sets up instrumentation not only to track timing, but also to catch +errors so that they can be analyzed or correlated with logs. This works the +same way regardless of if the error came from a common instrumented library, +such as RestTemplate, or your own code annotated with @NewSpan or similar.

    -

    Span: The basic unit of work. For example, sending an RPC is a new span, as is sending a response to an RPC. -Spans 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 IDs (normally IP addresses).

    -
    -
    -

    Spans can be 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.

    -
    -
    - - - - - -
    - - -The initial span that starts a trace is called a root span. The value of the ID -of that span is equal to the trace ID. -
    -
    -
    -

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

    -
    -
    -

    Annotation: Used to record the existence of an event in time. With -Brave instrumentation, we no longer need to set special events -for Zipkin to understand who the client and server are, where -the request started, and where it ended. For learning purposes, -however, we mark these events to highlight what kind -of an action took place.

    -
    -
    -
      -
    • -

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

      -
      • -
    • -

      sr: Server Received: The server side got the request and started processing it. -Subtracting the cs timestamp from this timestamp reveals the network latency.

      -
      • -
    • -

      ss: Server Sent. Annotated upon completion of request processing (when the response got sent back to the client). -Subtracting the sr timestamp from this timestamp reveals the time needed by the server side to process the request.

      -
      • -
    • -

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

      -
      • -
    -
    -
    -

    The following image shows how Span and Trace look in a system, together with the Zipkin annotations:

    -
    -
    -
    -Trace Info propagation -
    -
    -
    -

    Each color of a note signifies a span (there are seven spans - from A to G). -Consider the following note:

    -
    -
    -
    -
    Trace Id = X
-Span Id = D
-Client Sent
    -
    -
    -
    -

    This note indicates that the current span has Trace Id set to X and Span Id set to D. -Also, the Client Sent event took place.

    -
    -
    -

    The following image shows how parent-child relationships of spans look:

    -
    -
    -
    -Parent child relationship -
    -
    -
    -
    -

    1.2. Purpose

    -
    -

    The following sections refer to the example shown in the preceding image.

    +

    Below, we’ll use the word Zipkin to describe the tracing system, and include +Zipkin screenshots. However, most services accepting Zipkin’s format[zipkin.io/zipkin-api/#/default/post_spans], +have similar base features. Sleuth can also be configured to send data in other +formats, something detailed later.

    -

    1.2.1. Distributed Tracing with Zipkin

    +

    1.1.1. Contextualizing errors

    -

    This example has seven spans. -If you go to traces in Zipkin, you can see this number in the second trace, as shown in the following image:

    -
    -
    -
    -Traces -
    +

    Without distributed tracing, it can be difficult to understand the impact of a +an exception. For example, it can be hard to know if a specific request caused +the caller to fail or not.

    -

    However, if you pick a particular trace, you can see four spans, as shown in the following image:

    -
    -
    -
    -Traces Info propagation -
    -
    -
    - - - - - -
    - - -When you pick a particular trace, you see merged spans. -That means that, if there were two spans sent to Zipkin with Server Received and Server Sent or Client Received and Client Sent annotations, they are presented as a single span. -
    +

    Zipkin reduces time in triage by contextualizing errors and delays.

    -

    Why is there a difference between the seven and four spans in this case?

    -
    -
    -
      -
    • -

      One span comes from the http:/start span. It has the Server Received (sr) and Server Sent (ss) annotations.

      -
      • -
    • -

      Two spans come from the RPC call from service1 to service2 to the http:/foo endpoint. -The Client Sent (cs) and Client Received (cr) events took place on the service1 side. -Server Received (sr) and Server Sent (ss) events took place on the service2 side. -These two spans form one logical span related to an RPC call.

      -
      • -
    • -

      Two spans come from the RPC call from service2 to service3 to the http:/bar endpoint. -The Client Sent (cs) and Client Received (cr) events took place on the service2 side. -The Server Received (sr) and Server Sent (ss) events took place on the service3 side. -These two spans form one logical span related to an RPC call.

      -
      • -
    • -

      Two spans come from the RPC call from service2 to service4 to the http:/baz endpoint. -The Client Sent (cs) and Client Received (cr) events took place on the service2 side. -Server Received (sr) and Server Sent (ss) events took place on the service4 side. -These two spans form one logical span related to an RPC call.

      -
      • -
    -
    -
    -

    So, if we count the physical spans, we have one from http:/start, two from service1 calling service2, two from service2 -calling service3, and two from service2 calling service4. In sum, we have a total of seven spans.

    -
    -
    -

    Logically, we see the information of four total Spans because we have one span related to the incoming request -to service1 and three spans related to RPC calls.

    -
    -
    -
    -

    1.2.2. Visualizing errors

    -
    -

    Zipkin lets you visualize errors in your trace. -When an exception was thrown and was not caught, we set proper tags on the span, which Zipkin can then properly colorize. -You could see in the list of traces one trace that is red. That appears because an exception was thrown.

    -
    -
    -

    If you click that trace, you see a similar picture, as follows:

    +

    Requests colored red in the search screen failed:

    @@ -392,7 +273,8 @@ You could see in the list of traces one trace that is red. That appears because
    -

    If you then click on one of the spans, you see the following

    +

    If you then click on one of the traces, you can understand if the failure +happened before the request hit another service or not:

    @@ -400,65 +282,34 @@ You could see in the list of traces one trace that is red. That appears because
    -

    The span shows the reason for the error and the whole stack trace related to it.

    +

    For example, the above error happened in the "backend" service, and caused the +"frontend" service to fail.

    -

    1.2.3. Distributed Tracing with Brave

    +

    1.1.2. Log correlation

    -

    Starting with version 2.0.0, Spring Cloud Sleuth uses Brave as the tracing library. -Consequently, Sleuth no longer takes care of storing the context but delegates that work to Brave.

    +

    Sleuth configures the logging context with variables including the service name +(%{spring.zipkin.service.name}) and the trace ID (%{traceId}). These help +you connect logs with distributed traces and allow you choice in what tools you +use to troubleshoot your services.

    -

    Due to the fact that Sleuth had different naming and tagging conventions than Brave, we decided to follow Brave’s conventions from now on.

    -
    -
    -
    -

    1.2.4. Live examples

    -
    -
    -Zipkin deployed on Pivotal Web Services -
    -
    Click the Pivotal Web Services icon to see it live!Click the Pivotal Web Services icon to see it live!
    -
    -
    -

    Click here to see it live!

    -
    -
    -

    The dependency graph in Zipkin should resemble the following image:

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

    Click here to see it live!

    -
    -
    -
    -

    1.2.5. Log correlation

    -
    -

    When using grep to read the logs of those four applications by scanning for a trace ID equal to (for example) 2485ec27856c56f4, you get output resembling the following:

    +

    Once you find any log with an error, you can look for the trace ID in the +message. Paste that into Zipkin to visualize the entire trace, regardless of +how many services the first request ended up hitting.

    -
    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]]
    +
    backend.log:  2020-04-09 17:45:40.516 ERROR [backend,5e8eeec48b08e26882aba313eb08f0a4,dcc1df555b5777b3,true] 97203 --- [nio-9000-exec-1] o.s.c.s.i.web.ExceptionLoggingFilter     : Uncaught exception thrown
+frontend.log:2020-04-09 17:45:40.574 ERROR [frontend,5e8eeec48b08e26882aba313eb08f0a4,82aba313eb08f0a4,true] 97192 --- [nio-8081-exec-2] o.s.c.s.i.web.ExceptionLoggingFilter     : Uncaught exception thrown
    +

    Above, you’ll notice the trace ID is 5e8eeec48b08e26882aba313eb08f0a4, for +example. This log configuration was automatically setup by Sleuth.

    +
    +

    If you use a log aggregating tool (such as Kibana, Splunk, and others), you can order the events that took place. An example from Kibana would resemble the following image:

    @@ -652,33 +503,41 @@ Otherwise, your custom logback file does not properly read the property.
    -

    1.2.6. Propagating Span Context

    +

    1.1.3. Service Dependency Graph

    -

    The span context is the state that must get propagated to any child spans across process boundaries. -Part of the Span Context is the Baggage. The trace and span IDs are a required part of the span context. -Baggage is an optional part.

    +

    When you consider distributed tracing tracks requests, it makes sense that +trace data can paint a picture of your architecture.

    -

    Baggage is a set of key:value pairs stored in the span context. -Baggage travels together with the trace and is attached to every span. -Spring Cloud Sleuth understands that a header is baggage-related if the HTTP header is prefixed with baggage- and, for messaging, it starts with baggage_.

    -
    -
    - - - - - -
    - - -There is currently no limitation of the count or size of baggage items. -However, keep in mind that too many can decrease system throughput or increase RPC latency. -In extreme cases, too much baggage can crash the application, due to exceeding transport-level message or header capacity. -
    +

    Zipkin includes a tool to build service dependency diagrams from traces, +including the count of calls and how many errors exist.

    -

    The following example shows setting baggage on a span:

    +

    The example application will make a simple diagram like this, but your real +environment diagram may be more complex. +image::https://raw.githubusercontent.com/spring-cloud/spring-cloud-sleuth/master/docs/src/main/asciidoc/images/zipkin-depedendencies.png[Zipkin Dependencies]

    +
    +
    +

    Note: Production environments will generate a lot of data. You will likely +need to run a separate service to aggregate the dependency graph. You can learn +more here.

    +
    +
    +
    +

    1.1.4. Request scoped properties (Baggage)

    +
    +

    Distributed tracing works by propagating fields inside and across services that +connect the trace together: traceId and spanId notably. The context that holds +these fields can optionally push other fields that need to be consistent +regardless of many services are touched. The simple name for these extra fields +is "Baggage".

    +
    +
    +

    Sleuth allows you to define which baggage are permitted to exist in the trace +context, including what header names are used.

    +
    +
    +

    The following example shows setting baggage values:

    @@ -687,49 +546,34 @@ BUSINESS_PROCESS.updateValue(initialSpan.context(), "ALM"); COUNTRY_CODE.updateValue(initialSpan.context(), "FO");
    +
    + + + + + +
    + + +There is currently no limitation of the count or size of baggage +items. Keep in mind that too many can decrease system throughput or increase +RPC latency. In extreme cases, too much baggage can crash the application, due +to exceeding transport-level message or header capacity. +
    +
    -
    Baggage versus Span Tags
    +
    Baggage versus Tags
    -

    Baggage travels with the trace (every child span contains the baggage of its parent). -Zipkin has no knowledge of baggage and does not receive that information.

    -
    -
    - - - - - -
    - - -Starting from Sleuth 2.0.0 you have to pass the baggage key names explicitly -in your project configuration. Read more about that setup here -
    +

    Like trace IDs, Baggage is attached to messages or requests, usually as +headers. Tags are key value pairs sent in a Span to Zipkin. Baggage values are +not added spans by default, which means you can’t search based on Baggage +unless you opt-in.

    -

    Tags are attached to a specific span. In other words, they are presented only for that particular span. -However, you can search by tag to find the trace, assuming a span having the searched tag value exists.

    -
    -
    -

    If you want to be able to lookup a span based on baggage, you should add a corresponding entry as a tag in the root span.

    -
    -
    - - - - - -
    - - -The span must be in scope. -
    -
    -
    -

    The following listing shows integration tests that use baggage:

    +

    To make baggage also tags, use the property spring.sleuth.baggage.tag-fields +like so:

    -
    The setup
    spring:
   sleuth:
@@ -741,17 +585,11 @@ The span must be in scope.
         - country-code
    -
    -
    The code
    -
    -
    Tags.BAGGAGE_FIELD.tag(BUSINESS_PROCESS, initialSpan);
    -
    -
    -

    1.3. Adding Sleuth to the Project

    +

    1.2. Adding Sleuth to the Project

    This section addresses how to add Sleuth to your project with either Maven or Gradle.

    @@ -768,78 +606,7 @@ To ensure that your application name is properly displayed in Zipkin, set the
    -

    1.3.1. Only Sleuth (log correlation)

    -
    -

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

    -
    -
    -

    The following example shows how to add Sleuth with Maven:

    -
    -
    -
    Maven
    -
    -
    <dependencyManagement> (1)
-      <dependencies>
-          <dependency>
-              <groupId>org.springframework.cloud</groupId>
-              <artifactId>spring-cloud-dependencies</artifactId>
-              <version>${release.train.version}</version>
-              <type>pom</type>
-              <scope>import</scope>
-          </dependency>
-      </dependencies>
-</dependencyManagement>
-
-<dependency> (2)
-    <groupId>org.springframework.cloud</groupId>
-    <artifactId>spring-cloud-starter-sleuth</artifactId>
-</dependency>
    -
    -
    -
    - - - - - - - - - -
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    -
    -
    -

    The following example shows how to add Sleuth with Gradle:

    -
    -
    -
    Gradle
    -
    -
    dependencyManagement { (1)
-    imports {
-        mavenBom "org.springframework.cloud:spring-cloud-dependencies:${releaseTrainVersion}"
-    }
-}
-
-dependencies { (2)
-    compile "org.springframework.cloud:spring-cloud-starter-sleuth"
-}
    -
    -
    -
    - - - - - - - - - -
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    -
    -
    -
    -

    1.3.2. Sleuth with Zipkin via HTTP

    +

    1.2.1. Sleuth with Zipkin via HTTP

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

    @@ -910,7 +677,7 @@ dependencies { (2)
    -

    1.3.3. Sleuth with Zipkin over RabbitMQ or Kafka

    +

    1.2.2. Sleuth with Zipkin over RabbitMQ or Kafka

    If you want to use RabbitMQ or Kafka instead of HTTP, add the spring-rabbit or spring-kafka dependency. The default destination name is zipkin.

    @@ -1015,9 +782,8 @@ dependencies {
    -
    -
    -

    1.4. Overriding the auto-configuration of Zipkin

    +
    +

    1.2.3. Overriding the auto-configuration of Zipkin

    Spring Cloud Sleuth supports sending traces to multiple tracing systems as of version 2.1.0. In order to get this to work, every tracing system needs to have a Reporter<Span> and Sender. @@ -1074,164 +840,82 @@ protected static class MyConfig {

    -
    -
    -
    -

    2. Additional Resources

    -
    +
    +

    1.2.4. Only Sleuth (log correlation)

    -

    You can watch a video of Reshmi Krishna and Marcin Grzejszczak talking about Spring Cloud -Sleuth and Zipkin by clicking here.

    +

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

    -

    You can check different setups of Sleuth and Brave in the openzipkin/sleuth-webmvc-example repository.

    +

    The following example shows how to add Sleuth with Maven:

    -
    -
    -
    -

    3. 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, as shown in the following example logs:

      -
      +
      +
      Maven
      -
      2016-02-02 15:30:57.902  INFO [bar,6bfd228dc00d216b,6bfd228dc00d216b] 23030 --- [nio-8081-exec-3] ...
-2016-02-02 15:30:58.372 ERROR [bar,6bfd228dc00d216b,6bfd228dc00d216b] 23030 --- [nio-8081-exec-3] ...
-2016-02-02 15:31:01.936  INFO [bar,46ab0d418373cbc9,46ab0d418373cbc9] 23030 --- [nio-8081-exec-4] ...
      +
      <dependencyManagement> (1)
+      <dependencies>
+          <dependency>
+              <groupId>org.springframework.cloud</groupId>
+              <artifactId>spring-cloud-dependencies</artifactId>
+              <version>${release.train.version}</version>
+              <type>pom</type>
+              <scope>import</scope>
+          </dependency>
+      </dependencies>
+</dependencyManagement>
+
+<dependency> (2)
+    <groupId>org.springframework.cloud</groupId>
+    <artifactId>spring-cloud-starter-sleuth</artifactId>
+</dependency>
      +
      + + + + + + + + + +
      1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
      2Add the dependency to spring-cloud-starter-sleuth.
      +
      -

      Notice the [appname,traceId,spanId] entries from the MDC:

      +

      The following example shows how to add Sleuth with Gradle:

      -
      -
        -
      • -

        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.

        -
        • -
      +
      +
      Gradle
      +
      +
      dependencyManagement { (1)
+    imports {
+        mavenBom "org.springframework.cloud:spring-cloud-dependencies:${releaseTrainVersion}"
+    }
+}
+
+dependencies { (2)
+    compile "org.springframework.cloud:spring-cloud-starter-sleuth"
+}
      -
      • -
    • -

      Provides an abstraction over common distributed tracing data models: traces, spans (forming a DAG), annotations, and key-value annotations. -Spring Cloud Sleuth is loosely based on HTrace but is compatible with Zipkin (Dapper).

      -
      • -
    • -

      Sleuth records timing information to aid in latency analysis. -By 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. -To that end, Sleuth:

      -
      -
        -
      • -

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

        -
        • -
      • -

        Includes opinionated instrumentation of layers such as HTTP.

        -
        • -
      • -

        Includes a 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, and Feign client).

      -
      • -
    • -

      Sleuth includes default logic to join a trace across HTTP or messaging boundaries. -For example, HTTP propagation works over Zipkin-compatible request headers.

      -
      • -
    • -

      Sleuth can propagate context (also known as baggage) between processes. -Consequently, if you set a baggage element on a Span, it is sent downstream to other processes over either HTTP or messaging.

      -
      • -
    • -

      Provides a way to create or continue spans and add tags and logs through annotations.

      -
      • -
    • -

      If spring-cloud-sleuth-zipkin is on the classpath, the app generates and collects Zipkin-compatible traces. -By default, it sends them over HTTP to a Zipkin server on localhost (port 9411). -You can configure the location of the service by setting spring.zipkin.baseUrl.

      -
      -
        -
      • -

        If you depend on spring-rabbit, your app sends traces to a RabbitMQ broker instead of HTTP.

        -
        • -
      • -

        If you depend on spring-kafka, and set spring.zipkin.sender.type: kafka, your app sends traces to a Kafka broker instead of HTTP.

        -
        • -
      -
      -
      • -
    -
    -
    +
    - - + + + + + +
    - - -spring-cloud-sleuth-stream is deprecated and should no longer be used. -1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    -
    -
    -
    - - - - - -
    - - -The SLF4J MDC is always set and logback users immediately see the trace and span IDs in logs per the example -shown earlier. -Other logging systems have to configure their own formatter to get the same result. -The default is as follows: -logging.pattern.level set to %5p [${spring.zipkin.service.name:${spring.application.name:-}},%X{traceId:-},%X{spanId:-}] -(this is a Spring Boot feature for logback users). -If you do not use SLF4J, this pattern is NOT automatically applied. -
    -
    -
    - - - - - -
    - - -Starting with version 3.0.0, the logging pattern has changed. -We’ve converted the MDC entries from B3 to non B3 keys (e.g. X-B3-TraceId to traceId). -
    -

    4. Introduction

    +

    2. How Sleuth works

    Spring Cloud Sleuth is a layer over Brave.

    @@ -1265,14 +949,14 @@ predefined, but is flexible otherwise.

    Sleuth configures everything you need to get started with tracing. Sleuth configures where trace data (spans) are reported to, how many traces to keep -(sampling), if remote fields (baggage) and which libraries are traced. +(sampling), if remote fields (baggage) are sent, and which libraries are traced. Sleuth also adds annotation based tracing features and some instrumentation not available otherwise, such as Reactor. If cannot find the configuration you are looking for in the documentation, ask Gitter before assuming something cannot be done.

    -

    4.1. Brave Basics

    +

    2.1. Brave Basics

    Most instrumentation work is done for you by default. Sleuth provides beans to allow you to change what’s traced, and it even provides annotations to avoid @@ -1297,7 +981,7 @@ are some pointers.

    -

    5. Sampling

    +

    3. Sampling

    By default Spring Cloud Sleuth doesn’t sample spans. @@ -1348,7 +1032,7 @@ Doing so forces the current request to be sampled regardless of configuration.

    -

    6. Baggage

    +

    4. Baggage

    Baggage are fields that are propagated with the trace, optionally out of process. You can use @@ -1393,7 +1077,7 @@ Remember that adding entries to MDC can drastically decrease the performance of spring.sleuth.baggage.tag-fields with a list of whitelisted baggage keys. To disable the feature you have to pass the spring.sleuth.propagation.tag.enabled=false property.

    -

    6.1. Java configuration

    +

    4.1. Java configuration

    If you need to do anything more advanced than above, do not define properties and instead use a @Bean config for the baggage fields you use. @@ -1406,7 +1090,7 @@ Remember that adding entries to MDC can drastically decrease the performance of

    -

    7. Instrumentation

    +

    5. Instrumentation

    Spring Cloud Sleuth automatically instruments all your Spring applications, so you should not have to do anything to activate it. @@ -1432,7 +1116,7 @@ Tags are collected and exported only if there is a Sampler that all

    -

    8. Span lifecycle

    +

    6. Span lifecycle

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

    @@ -1471,7 +1155,7 @@ Spring Cloud Sleuth creates an instance of Tracer for you. In order
    -

    8.1. Creating and finishing spans

    +

    6.1. Creating and finishing spans

    You can manually create spans by using the Tracer, as shown in the following example:

    @@ -1526,7 +1210,7 @@ Your names have to be explicit and concrete. Big names lead to latency issues an
    -

    8.2. Continuing Spans

    +

    6.2. Continuing Spans

    Sometimes, you do not want to create a new span but you want to continue one. An example of such a situation might be as follows:

    @@ -1563,7 +1247,7 @@ finally {
    -

    8.3. Creating a Span with an explicit Parent

    +

    6.3. Creating a Span with an explicit Parent

    You might want to start a new span and provide an explicit parent of that span. Assume that the parent of a span is in one thread and you want to start a new span in another thread. @@ -1611,7 +1295,7 @@ After creating such a span, you must finish it. Otherwise it is not reported (fo

    -

    9. Naming spans

    +

    7. Naming spans

    Picking a span name is not a trivial task. A span name should depict an operation name. @@ -1637,7 +1321,7 @@ The name should be low cardinality, so it should not include identifiers.

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

    -

    9.1. @SpanName Annotation

    +

    7.1. @SpanName Annotation

    You can name the span explicitly by using the @SpanName annotation, as shown in the following example:

    @@ -1668,7 +1352,7 @@ future.get();
    -

    9.2. toString() method

    +

    7.2. toString() method

    It is pretty rare to create separate classes for Runnable or Callable. Typically, one creates an anonymous instance of those classes. @@ -1700,13 +1384,13 @@ future.get();

    -

    10. Managing Spans with Annotations

    +

    8. Managing Spans with Annotations

    You can manage spans with a variety of annotations.

    -

    10.1. Rationale

    +

    8.1. Rationale

    There are a number of good reasons to manage spans with annotations, including:

    @@ -1729,7 +1413,7 @@ Now you can provide annotations over interfaces and the arguments of those inter
    -

    10.2. Creating New Spans

    +

    8.2. Creating New Spans

    If you do not want to create local spans manually, you can use the @NewSpan annotation. Also, we provide the @SpanTag annotation to add tags in an automated fashion.

    @@ -1785,7 +1469,7 @@ concrete one wins (in this case customNameOnTestMethod3 is set).

    -

    10.3. Continuing Spans

    +

    8.3. Continuing Spans

    If you want to add tags and annotations to an existing span, you can use the @ContinueSpan annotation, as shown in the following example:

    @@ -1821,7 +1505,7 @@ this.testBean.testMethod13();
    -

    10.4. Advanced Tag Setting

    +

    8.4. Advanced Tag Setting

    There are 3 different ways to add tags to a span. All of them are controlled by the SpanTag annotation. The precedence is as follows:

    @@ -1843,7 +1527,7 @@ The default implementation uses SPEL expression resolution.
    -

    10.4.1. Custom extractor

    +

    8.4.1. Custom extractor

    The value of the tag for the following method is computed by an implementation of TagValueResolver interface. Its class name has to be passed as the value of the resolver attribute.

    @@ -1875,7 +1559,7 @@ public TagValueResolver tagValueResolver() {
    -

    10.4.2. Resolving Expressions for a Value

    +

    8.4.2. Resolving Expressions for a Value

    Consider the following annotated method:

    @@ -1893,7 +1577,7 @@ If you want to use some other expression resolution mechanism, you can create yo
    -

    10.4.3. Using the toString() method

    +

    8.4.3. Using the toString() method

    Consider the following annotated method:

    @@ -1912,7 +1596,7 @@ public void getAnnotationForArgumentToString(@SpanTag("test") Long param) {
    -

    11. Customizations

    +

    9. Customizations

    The Tracer object is fully managed by sleuth, so you rarely need to affect it. That said, @@ -1946,9 +1630,9 @@ customize behaviour:

    -

    11.1. HTTP

    +

    9.1. HTTP

    -

    11.1.1. Data Policy

    +

    9.1.1. Data Policy

    The default span data policy for HTTP requests is described in Brave: github.com/openzipkin/brave/tree/master/instrumentation/http#span-data-policy

    @@ -1990,7 +1674,7 @@ class Config {
    -

    11.1.2. Sampling

    +

    9.1.2. Sampling

    If client /server sampling is required, just register a bean of type brave.sampler.SamplerFunction<HttpRequest> and name the bean @@ -2033,7 +1717,7 @@ class Config {

    -

    11.2. TracingFilter

    +

    9.2. TracingFilter

    You can also modify the behavior of the TracingFilter, which is the component that is responsible for processing the input HTTP request and adding tags basing on the HTTP response. You can customize the tags or modify the response headers by registering your own instance of the TracingFilter bean.

    @@ -2074,7 +1758,7 @@ class MyFilter extends GenericFilterBean {
    -

    11.3. Messaging

    +

    9.3. Messaging

    Sleuth automatically configures the MessagingTracing bean which serves as a foundation for Messaging instrumentation such as Kafka or JMS.

    @@ -2107,7 +1791,7 @@ class Config {
    -

    11.4. RPC

    +

    9.4. RPC

    Sleuth automatically configures the RpcTracing bean which serves as a foundation for RPC instrumentation such as gRPC or Dubbo.

    @@ -2148,7 +1832,7 @@ class Config {
    -

    11.5. Custom service name

    +

    9.5. Custom service name

    By default, Sleuth assumes that, when you send a span to Zipkin, you want the span’s service name to be equal to the value of the spring.application.name property. That is not always the case, though. @@ -2162,7 +1846,7 @@ To achieve that, you can pass the following property to your application to over

    -

    11.6. Customization of Reported Spans

    +

    9.6. Customization of Reported Spans

    Before reporting spans (for example, to Zipkin) you may want to modify that span in some way. You can do so by using the FinishedSpanHandler interface.

    @@ -2205,7 +1889,7 @@ FinishedSpanHandler handlerTwo() {
    -

    11.7. Host Locator

    +

    9.7. Host Locator

    @@ -2236,7 +1920,7 @@ If those are not set, we try to retrieve the host name from the network interfac
    -

    12. Sending Spans to Zipkin

    +

    10. Sending Spans to Zipkin

    By default, if you add spring-cloud-starter-zipkin as a dependency to your project, when the span is closed, it is sent to Zipkin over HTTP. @@ -2317,7 +2001,7 @@ object, you will have to create a bean of zipkin2.reporter.Sender t

    -

    13. Zipkin Stream Span Consumer

    +

    11. Zipkin Stream Span Consumer

    @@ -2339,10 +2023,10 @@ In the Finchley release, it got removed.
    -

    14. Integrations

    +

    12. Integrations

    -

    14.1. OpenTracing

    +

    12.1. OpenTracing

    Spring Cloud Sleuth is compatible with OpenTracing. If you have OpenTracing on the classpath, we automatically register the OpenTracing Tracer bean. @@ -2350,7 +2034,7 @@ If you wish to disable this, set spring.sleuth.opentracing.enabled

    -

    14.2. Runnable and Callable

    +

    12.2. Runnable and Callable

    If you wrap your logic in Runnable or Callable, you can wrap those classes in their Sleuth representative, as shown in the following example for Runnable:

    @@ -2406,13 +2090,13 @@ Callable<String> traceCallableFromTracer = this.tracing.currentTraceContex
    -

    14.3. Spring Cloud CircuitBreaker

    +

    12.3. Spring Cloud CircuitBreaker

    If you have Spring Cloud CircuitBreaker on the classpath, we will wrap the passed command Supplier and the fallback Function in its trace representations. In order to disable this instrumentation set spring.sleuth.circuitbreaker.enabled to false.

    -

    14.4. RxJava

    +

    12.4. RxJava

    We registering a custom RxJavaSchedulersHook that wraps all Action0 instances in their Sleuth representative, which is called TraceAction. The hook either starts or continues a span, depending on whether tracing was already going on before the Action was scheduled. @@ -2437,12 +2121,12 @@ the Reactor support.

    -

    14.5. HTTP integration

    +

    12.5. HTTP integration

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

    -

    14.5.1. HTTP Filter

    +

    12.5.1. HTTP Filter

    Through the TracingFilter, all sampled incoming requests result in creation of a Span. That Span’s name is http: + the path to which the request was sent. @@ -2466,7 +2150,7 @@ to true.

    -

    14.5.2. HandlerInterceptor

    +

    12.5.2. HandlerInterceptor

    Since we want the span names to be precise, we use 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. @@ -2476,13 +2160,13 @@ In that case, please file an issue in Spring Cloud Sleuth.

    -

    14.5.3. Async Servlet support

    +

    12.5.3. Async Servlet support

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

    -

    14.5.4. WebFlux support

    +

    12.5.4. WebFlux support

    Through TraceWebFilter, all sampled incoming requests result in creation of a Span. That Span’s name is http: + the path to which the request was sent. @@ -2497,7 +2181,7 @@ If you want to reuse Sleuth’s default skip patterns and append your own, p

    -

    14.5.5. Dubbo RPC support

    +

    12.5.5. Dubbo RPC support

    Via the integration with Brave, Spring Cloud Sleuth supports Dubbo. It’s enough to add the brave-instrumentation-dubbo dependency:

    @@ -2526,9 +2210,9 @@ An example of Spring Cloud Sleuth and Dubbo can be found -

    14.6. HTTP Client Integration

    +

    12.6. HTTP Client Integration

    -

    14.6.1. Synchronous Rest Template

    +

    12.6.1. Synchronous Rest Template

    We inject a RestTemplate interceptor to ensure that all the tracing information is passed to the requests. Each time a call is made, a new Span is created. @@ -2550,7 +2234,7 @@ If you create a RestTemplate instance with a new keywo

    -

    14.6.2. Asynchronous Rest Template

    +

    12.6.2. Asynchronous Rest Template

    @@ -2607,7 +2291,7 @@ static class Config {
    -

    14.6.3. WebClient

    +

    12.6.3. WebClient

    We inject a ExchangeFilterFunction implementation that creates a span and, through on-success and on-error callbacks, takes care of closing client-side spans.

    @@ -2629,7 +2313,7 @@ If you create a WebClient instance with a new keyword,
    -

    14.6.4. Traverson

    +

    12.6.4. Traverson

    If you use the Traverson library, you can inject a RestTemplate as a bean into your Traverson object. Since RestTemplate is already intercepted, you get full support for tracing in your client. The following pseudo code @@ -2646,7 +2330,7 @@ Traverson traverson = new Traverson(URI.create("https://some/address"),

    -

    14.6.5. Apache HttpClientBuilder and HttpAsyncClientBuilder

    +

    12.6.5. Apache HttpClientBuilder and HttpAsyncClientBuilder

    We instrument the HttpClientBuilder and HttpAsyncClientBuilder so that tracing context gets injected to the sent requests.

    @@ -2656,7 +2340,7 @@ tracing context gets injected to the sent requests.

    -

    14.6.6. Netty HttpClient

    +

    12.6.6. Netty HttpClient

    We instrument the Netty’s HttpClient.

    @@ -2678,7 +2362,7 @@ If you create a HttpClient instance with a new keyword
    -

    14.6.7. UserInfoRestTemplateCustomizer

    +

    12.6.7. UserInfoRestTemplateCustomizer

    We instrument the Spring Security’s UserInfoRestTemplateCustomizer.

    @@ -2688,7 +2372,7 @@ If you create a HttpClient instance with a new keyword
    -

    14.7. Feign

    +

    12.7. Feign

    By default, Spring Cloud Sleuth provides integration with Feign through TraceFeignClientAutoConfiguration. You can disable it entirely by setting spring.sleuth.feign.enabled to false. @@ -2702,12 +2386,12 @@ However, all the default instrumentation is still there.

    -

    14.8. gRPC

    +

    12.8. gRPC

    Spring Cloud Sleuth provides instrumentation for gRPC through TraceGrpcAutoConfiguration. You can disable it entirely by setting spring.sleuth.grpc.enabled to false.

    -

    14.8.1. Variant 1

    +

    12.8.1. Variant 1

    Dependencies
    @@ -2776,16 +2460,16 @@ Spring Cloud Sleuth provides a SpringAwareManagedChannelBuilder tha
    -

    14.8.2. Variant 2

    +

    12.8.2. Variant 2

    Grpc Spring Boot Starter automatically detects the presence of Spring Cloud Sleuth and brave’s instrumentation for gRPC and registers the necessary client and/or server tooling.

    -

    14.9. Asynchronous Communication

    +

    12.9. Asynchronous Communication

    -

    14.9.1. @Async Annotated methods

    +

    12.9.1. @Async Annotated methods

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

    @@ -2808,7 +2492,7 @@ You can disable this behavior by setting the value of spring.sleuth.async.
    -

    14.9.2. @Scheduled Annotated Methods

    +

    12.9.2. @Scheduled Annotated Methods

    In Spring Cloud Sleuth, we instrument scheduled method execution so that the tracing information is passed between threads. You can disable this behavior by setting the value of spring.sleuth.scheduled.enabled to false.

    @@ -2831,7 +2515,7 @@ You can disable this behavior by setting the value of spring.sleuth.schedu
    -

    14.9.3. Executor, ExecutorService, and ScheduledExecutorService

    +

    12.9.3. Executor, ExecutorService, and ScheduledExecutorService

    We provide LazyTraceExecutor, TraceableExecutorService, and TraceableScheduledExecutorService. Those implementations create spans each time a new task is submitted, invoked, or scheduled.

    @@ -2918,12 +2602,12 @@ to add the @Role(BeanDefinition.ROLE_INFRASTRUCTURE) on your
    -

    14.10. Messaging

    +

    12.10. Messaging

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

    -

    14.10.1. Spring Integration and Spring Cloud Stream

    +

    12.10.1. Spring Integration and Spring Cloud Stream

    Spring Cloud Sleuth integrates with Spring Integration. It creates spans for publish and subscribe events. @@ -2962,7 +2646,7 @@ it’s enough for you to register beans of types:

    -

    14.10.2. Spring RabbitMq

    +

    12.10.2. Spring RabbitMq

    We instrument the RabbitTemplate so that tracing headers get injected into the message.

    @@ -2972,7 +2656,7 @@ into the message.

    -

    14.10.3. Spring Kafka

    +

    12.10.3. Spring Kafka

    We instrument the Spring Kafka’s ProducerFactory and ConsumerFactory so that tracing headers get injected into the created Spring Kafka’s @@ -2983,7 +2667,7 @@ so that tracing headers get injected into the created Spring Kafka’s

    -

    14.10.4. Spring Kafka Streams

    +

    12.10.4. Spring Kafka Streams

    We instrument the KafkaStreams KafkaClientSupplier so that tracing headers get injected into the Producer and Consumer`s. A `KafkaStreamsTracing bean @@ -2995,7 +2679,7 @@ allows for further instrumentation through additional TransformerSupplier<

    -

    14.10.5. Spring JMS

    +

    12.10.5. Spring JMS

    We instrument the JmsTemplate so that tracing headers get injected into the message. We also support @JmsListener annotated methods on the consumer side.

    @@ -3017,7 +2701,7 @@ We don’t support baggage propagation for JMS
    -

    14.10.6. Spring Cloud AWS Messaging SQS

    +

    12.10.6. Spring Cloud AWS Messaging SQS

    We instrument @SqsListener which is provided by org.springframework.cloud:spring-cloud-aws-messaging so that tracing headers get extracted from the message and a trace gets put into the context.

    @@ -3028,14 +2712,14 @@ so that tracing headers get extracted from the message and a trace gets put into
    -

    14.11. Redis

    +

    12.11. Redis

    We set tracing property to Lettcue ClientResources instance to enable Brave tracing built in Lettuce . To disable Redis support, set the spring.sleuth.redis.enabled property to false.

    -

    14.12. Quartz

    +

    12.12. Quartz

    We instrument quartz jobs by adding Job/Trigger listeners to the Quartz Scheduler.

    @@ -3044,7 +2728,7 @@ To disable Redis support, set the spring.sleuth.redis.enabled prope
    -

    14.13. Project Reactor

    +

    12.13. Project Reactor

    For projects depending on Project Reactor such as Spring Cloud Gateway, we suggest turning the spring.sleuth.reactor.decorate-on-each option to false. That way an increased performance gain should be observed in comparison to the standard instrumentation mechanism. What this option does is it will wrap decorate onLast operator instead of onEach which will result in creation of far fewer objects. The downside of this is that when Project Reactor will change threads, the trace propagation will continue without issues, however anything relying on the ThreadLocal such as e.g. MDC entries can be buggy.

    @@ -3052,7 +2736,7 @@ To disable Redis support, set the spring.sleuth.redis.enabled prope
    -

    15. Configuration properties

    +

    13. Configuration properties

    To see the list of all Sleuth related configuration properties please check the Appendix page.

    @@ -3060,7 +2744,7 @@ To disable Redis support, set the spring.sleuth.redis.enabled prope
    -

    16. Running examples

    +

    14. Running examples

    You can see the running examples deployed in the Pivotal Web Services. diff --git a/reference/html/overview.html b/reference/html/overview.html new file mode 100644 index 000000000..d85405547 --- /dev/null +++ b/reference/html/overview.html @@ -0,0 +1,170 @@ + + + + + + + +Overview + + + + + + + + + +

    +
    +
    +

    Overview

    +
    +
    +

    Spring Cloud Sleuth provides Spring Boot auto-configuration for distributed +tracing. Underneath, Spring Cloud Sleuth is a layer over a Tracer library named +Brave.

    +
    +
    +

    Sleuth configures everything you need to get started. This includes where trace +data (spans) are reported to, how many traces to keep (sampling), if remote +fields (baggage) are sent, and which libraries are traced.

    +
    +
    +

    We maintain an example app where two Spring Boot services collaborate on an +HTTP request. Sleuth configures these apps, so that timing of these requests are +recorded into Zipkin, a distributed tracing system. Tracing +UIs visualize latency, such as time in one service vs waiting for other +services.

    +
    +
    +

    Here’s an example of what it looks like:

    +
    +
    +
    +Zipkin Traces +
    +
    +
    +

    The source repository of this +example includes demonstrations ofmany things, including WebFlux and messaging. +Most features require only a property or dependency change to work. These +snippets showcase the value of Spring Cloud Sleuth: Through auto-configuration, +Sleuth make getting started with distributed tracing easy!

    +
    +
    +

    To keep things simple, the same example is used throughout documentation using +basic HTTP communication.

    +
    +
    +
    +
    + + + + + + + \ No newline at end of file diff --git a/reference/html/setup.html b/reference/html/setup.html new file mode 100644 index 000000000..c3d6989ea --- /dev/null +++ b/reference/html/setup.html @@ -0,0 +1,453 @@ + + + + + + + +Adding Sleuth to the Project + + + + + + + + + + +
    +
    +

    Adding Sleuth to the Project

    +
    +

    This section addresses how to add Sleuth to your project with either Maven or Gradle.

    +
    +
    +
    + + + + +
    + + +To ensure that your application name is properly displayed in Zipkin, set the spring.application.name property in bootstrap.yml. +
    +
    +
    +

    Sleuth with Zipkin via HTTP

    +
    +

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

    +
    +
    +

    The following example shows how to do so for Maven:

    +
    +
    +
    Maven
    +
    +
    <dependencyManagement> (1)
+      <dependencies>
+          <dependency>
+              <groupId>org.springframework.cloud</groupId>
+              <artifactId>spring-cloud-dependencies</artifactId>
+              <version>${release.train.version}</version>
+              <type>pom</type>
+              <scope>import</scope>
+          </dependency>
+      </dependencies>
+</dependencyManagement>
+
+<dependency> (2)
+    <groupId>org.springframework.cloud</groupId>
+    <artifactId>spring-cloud-starter-zipkin</artifactId>
+</dependency>
    +
    +
    +
    + + + + + + + + + +
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-zipkin.
    +
    +
    +

    The following example shows how to do so for Gradle:

    +
    +
    +
    Gradle
    +
    +
    dependencyManagement { (1)
+    imports {
+        mavenBom "org.springframework.cloud:spring-cloud-dependencies:${releaseTrainVersion}"
+    }
+}
+
+dependencies { (2)
+    compile "org.springframework.cloud:spring-cloud-starter-zipkin"
+}
    +
    +
    +
    + + + + + + + + + +
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-zipkin.
    +
    +
    +
    +

    Sleuth with Zipkin over RabbitMQ or Kafka

    +
    +

    If you want to use RabbitMQ or Kafka instead of HTTP, add the spring-rabbit or spring-kafka dependency. +The default destination name is zipkin.

    +
    +
    +

    If using Kafka, you must set the property spring.zipkin.sender.type property accordingly:

    +
    +
    +
    +
    spring.zipkin.sender.type: kafka
    +
    +
    +
    + + + + + +
    + + +spring-cloud-sleuth-stream is deprecated and incompatible with these destinations. +
    +
    +
    +

    If you want Sleuth over RabbitMQ, add the spring-cloud-starter-zipkin and spring-rabbit +dependencies.

    +
    +
    +

    The following example shows how to do so for Gradle:

    +
    +
    +
    Maven
    +
    +
    <dependencyManagement> (1)
+      <dependencies>
+          <dependency>
+              <groupId>org.springframework.cloud</groupId>
+              <artifactId>spring-cloud-dependencies</artifactId>
+              <version>${release.train.version}</version>
+              <type>pom</type>
+              <scope>import</scope>
+          </dependency>
+      </dependencies>
+</dependencyManagement>
+
+<dependency> (2)
+    <groupId>org.springframework.cloud</groupId>
+    <artifactId>spring-cloud-starter-zipkin</artifactId>
+</dependency>
+<dependency> (3)
+    <groupId>org.springframework.amqp</groupId>
+    <artifactId>spring-rabbit</artifactId>
+</dependency>
    +
    +
    +
    + + + + + + + + + + + + + +
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-zipkin. That way, all nested dependencies get downloaded.
    3To automatically configure RabbitMQ, add the spring-rabbit dependency.
    +
    +
    +
    Gradle
    +
    +
    dependencyManagement { (1)
+    imports {
+        mavenBom "org.springframework.cloud:spring-cloud-dependencies:${releaseTrainVersion}"
+    }
+}
+
+dependencies {
+    compile "org.springframework.cloud:spring-cloud-starter-zipkin" (2)
+    compile "org.springframework.amqp:spring-rabbit" (3)
+}
    +
    +
    +
    + + + + + + + + + + + + + +
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-zipkin. That way, all nested dependencies get downloaded.
    3To automatically configure RabbitMQ, add the spring-rabbit dependency.
    +
    +
    +
    +

    Overriding the auto-configuration of Zipkin

    +
    +

    Spring Cloud Sleuth supports sending traces to multiple tracing systems as of version 2.1.0. +In order to get this to work, every tracing system needs to have a Reporter<Span> and Sender. +If you want to override the provided beans you need to give them a specific name. +To do this you can use respectively ZipkinAutoConfiguration.REPORTER_BEAN_NAME and ZipkinAutoConfiguration.SENDER_BEAN_NAME.

    +
    +
    +
    +
    @Configuration
+protected static class MyConfig {
+
+	@Bean(ZipkinAutoConfiguration.REPORTER_BEAN_NAME)
+	Reporter<zipkin2.Span> myReporter() {
+		return AsyncReporter.create(mySender());
+	}
+
+	@Bean(ZipkinAutoConfiguration.SENDER_BEAN_NAME)
+	MySender mySender() {
+		return new MySender();
+	}
+
+	static class MySender extends Sender {
+
+		private boolean spanSent = false;
+
+		boolean isSpanSent() {
+			return this.spanSent;
+		}
+
+		@Override
+		public Encoding encoding() {
+			return Encoding.JSON;
+		}
+
+		@Override
+		public int messageMaxBytes() {
+			return Integer.MAX_VALUE;
+		}
+
+		@Override
+		public int messageSizeInBytes(List<byte[]> encodedSpans) {
+			return encoding().listSizeInBytes(encodedSpans);
+		}
+
+		@Override
+		public Call<Void> sendSpans(List<byte[]> encodedSpans) {
+			this.spanSent = true;
+			return Call.create(null);
+		}
+
+	}
+
+}
    +
    +
    +
    +
    +

    Only Sleuth (log correlation)

    +
    +

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

    +
    +
    +

    The following example shows how to add Sleuth with Maven:

    +
    +
    +
    Maven
    +
    +
    <dependencyManagement> (1)
+      <dependencies>
+          <dependency>
+              <groupId>org.springframework.cloud</groupId>
+              <artifactId>spring-cloud-dependencies</artifactId>
+              <version>${release.train.version}</version>
+              <type>pom</type>
+              <scope>import</scope>
+          </dependency>
+      </dependencies>
+</dependencyManagement>
+
+<dependency> (2)
+    <groupId>org.springframework.cloud</groupId>
+    <artifactId>spring-cloud-starter-sleuth</artifactId>
+</dependency>
    +
    +
    +
    + + + + + + + + + +
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    +
    +
    +

    The following example shows how to add Sleuth with Gradle:

    +
    +
    +
    Gradle
    +
    +
    dependencyManagement { (1)
+    imports {
+        mavenBom "org.springframework.cloud:spring-cloud-dependencies:${releaseTrainVersion}"
+    }
+}
+
+dependencies { (2)
+    compile "org.springframework.cloud:spring-cloud-starter-sleuth"
+}
    +
    +
    +
    + + + + + + + + + +
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    +
    +
    +
    +
    + + + + + + + \ No newline at end of file diff --git a/reference/html/spring-cloud-sleuth.html b/reference/html/spring-cloud-sleuth.html index 3e0de2a5b..ab3562ddf 100644 --- a/reference/html/spring-cloud-sleuth.html +++ b/reference/html/spring-cloud-sleuth.html @@ -119,81 +119,77 @@ $(globalSwitch);
    Table of Contents
    @@ -206,185 +202,70 @@ $(globalSwitch);
    -

    1. Introduction

    +

    1. Overview

    -

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

    +

    Spring Cloud Sleuth provides Spring Boot auto-configuration for distributed +tracing. Underneath, Spring Cloud Sleuth is a layer over a Tracer library named +Brave.

    +
    +
    +

    Sleuth configures everything you need to get started. This includes where trace +data (spans) are reported to, how many traces to keep (sampling), if remote +fields (baggage) are sent, and which libraries are traced.

    +
    +
    +

    We maintain an example app where two Spring Boot services collaborate on an +HTTP request. Sleuth configures these apps, so that timing of these requests are +recorded into Zipkin, a distributed tracing system. Tracing +UIs visualize latency, such as time in one service vs waiting for other +services.

    +
    +
    +

    Here’s an example of what it looks like:

    +
    +
    +
    +Zipkin Traces +
    +
    +
    +

    The source repository of this +example includes demonstrations ofmany things, including WebFlux and messaging. +Most features require only a property or dependency change to work. These +snippets showcase the value of Spring Cloud Sleuth: Through auto-configuration, +Sleuth make getting started with distributed tracing easy!

    +
    +
    +

    To keep things simple, the same example is used throughout documentation using +basic HTTP communication.

    -

    1.1. Terminology

    +

    1.1. Features

    -

    Spring Cloud Sleuth borrows Dapper’s terminology.

    +

    Sleuth sets up instrumentation not only to track timing, but also to catch +errors so that they can be analyzed or correlated with logs. This works the +same way regardless of if the error came from a common instrumented library, +such as RestTemplate, or your own code annotated with @NewSpan or similar.

    -

    Span: The basic unit of work. For example, sending an RPC is a new span, as is sending a response to an RPC. -Spans 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 IDs (normally IP addresses).

    -
    -
    -

    Spans can be 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.

    -
    -
    - - - - - -
    - - -The initial span that starts a trace is called a root span. The value of the ID -of that span is equal to the trace ID. -
    -
    -
    -

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

    -
    -
    -

    Annotation: Used to record the existence of an event in time. With -Brave instrumentation, we no longer need to set special events -for Zipkin to understand who the client and server are, where -the request started, and where it ended. For learning purposes, -however, we mark these events to highlight what kind -of an action took place.

    -
    -
    -
      -
    • -

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

      -
      • -
    • -

      sr: Server Received: The server side got the request and started processing it. -Subtracting the cs timestamp from this timestamp reveals the network latency.

      -
      • -
    • -

      ss: Server Sent. Annotated upon completion of request processing (when the response got sent back to the client). -Subtracting the sr timestamp from this timestamp reveals the time needed by the server side to process the request.

      -
      • -
    • -

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

      -
      • -
    -
    -
    -

    The following image shows how Span and Trace look in a system, together with the Zipkin annotations:

    -
    -
    -
    -Trace Info propagation -
    -
    -
    -

    Each color of a note signifies a span (there are seven spans - from A to G). -Consider the following note:

    -
    -
    -
    -
    Trace Id = X
-Span Id = D
-Client Sent
    -
    -
    -
    -

    This note indicates that the current span has Trace Id set to X and Span Id set to D. -Also, the Client Sent event took place.

    -
    -
    -

    The following image shows how parent-child relationships of spans look:

    -
    -
    -
    -Parent child relationship -
    -
    -
    -
    -

    1.2. Purpose

    -
    -

    The following sections refer to the example shown in the preceding image.

    +

    Below, we’ll use the word Zipkin to describe the tracing system, and include +Zipkin screenshots. However, most services accepting Zipkin’s format[zipkin.io/zipkin-api/#/default/post_spans], +have similar base features. Sleuth can also be configured to send data in other +formats, something detailed later.

    -

    1.2.1. Distributed Tracing with Zipkin

    +

    1.1.1. Contextualizing errors

    -

    This example has seven spans. -If you go to traces in Zipkin, you can see this number in the second trace, as shown in the following image:

    -
    -
    -
    -Traces -
    +

    Without distributed tracing, it can be difficult to understand the impact of a +an exception. For example, it can be hard to know if a specific request caused +the caller to fail or not.

    -

    However, if you pick a particular trace, you can see four spans, as shown in the following image:

    -
    -
    -
    -Traces Info propagation -
    -
    -
    - - - - - -
    - - -When you pick a particular trace, you see merged spans. -That means that, if there were two spans sent to Zipkin with Server Received and Server Sent or Client Received and Client Sent annotations, they are presented as a single span. -
    +

    Zipkin reduces time in triage by contextualizing errors and delays.

    -

    Why is there a difference between the seven and four spans in this case?

    -
    -
    -
      -
    • -

      One span comes from the http:/start span. It has the Server Received (sr) and Server Sent (ss) annotations.

      -
      • -
    • -

      Two spans come from the RPC call from service1 to service2 to the http:/foo endpoint. -The Client Sent (cs) and Client Received (cr) events took place on the service1 side. -Server Received (sr) and Server Sent (ss) events took place on the service2 side. -These two spans form one logical span related to an RPC call.

      -
      • -
    • -

      Two spans come from the RPC call from service2 to service3 to the http:/bar endpoint. -The Client Sent (cs) and Client Received (cr) events took place on the service2 side. -The Server Received (sr) and Server Sent (ss) events took place on the service3 side. -These two spans form one logical span related to an RPC call.

      -
      • -
    • -

      Two spans come from the RPC call from service2 to service4 to the http:/baz endpoint. -The Client Sent (cs) and Client Received (cr) events took place on the service2 side. -Server Received (sr) and Server Sent (ss) events took place on the service4 side. -These two spans form one logical span related to an RPC call.

      -
      • -
    -
    -
    -

    So, if we count the physical spans, we have one from http:/start, two from service1 calling service2, two from service2 -calling service3, and two from service2 calling service4. In sum, we have a total of seven spans.

    -
    -
    -

    Logically, we see the information of four total Spans because we have one span related to the incoming request -to service1 and three spans related to RPC calls.

    -
    -
    -
    -

    1.2.2. Visualizing errors

    -
    -

    Zipkin lets you visualize errors in your trace. -When an exception was thrown and was not caught, we set proper tags on the span, which Zipkin can then properly colorize. -You could see in the list of traces one trace that is red. That appears because an exception was thrown.

    -
    -
    -

    If you click that trace, you see a similar picture, as follows:

    +

    Requests colored red in the search screen failed:

    @@ -392,7 +273,8 @@ You could see in the list of traces one trace that is red. That appears because
    -

    If you then click on one of the spans, you see the following

    +

    If you then click on one of the traces, you can understand if the failure +happened before the request hit another service or not:

    @@ -400,65 +282,34 @@ You could see in the list of traces one trace that is red. That appears because
    -

    The span shows the reason for the error and the whole stack trace related to it.

    +

    For example, the above error happened in the "backend" service, and caused the +"frontend" service to fail.

    -

    1.2.3. Distributed Tracing with Brave

    +

    1.1.2. Log correlation

    -

    Starting with version 2.0.0, Spring Cloud Sleuth uses Brave as the tracing library. -Consequently, Sleuth no longer takes care of storing the context but delegates that work to Brave.

    +

    Sleuth configures the logging context with variables including the service name +(%{spring.zipkin.service.name}) and the trace ID (%{traceId}). These help +you connect logs with distributed traces and allow you choice in what tools you +use to troubleshoot your services.

    -

    Due to the fact that Sleuth had different naming and tagging conventions than Brave, we decided to follow Brave’s conventions from now on.

    -
    -
    -
    -

    1.2.4. Live examples

    -
    -
    -Zipkin deployed on Pivotal Web Services -
    -
    Click the Pivotal Web Services icon to see it live!Click the Pivotal Web Services icon to see it live!
    -
    -
    -

    Click here to see it live!

    -
    -
    -

    The dependency graph in Zipkin should resemble the following image:

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

    Click here to see it live!

    -
    -
    -
    -

    1.2.5. Log correlation

    -
    -

    When using grep to read the logs of those four applications by scanning for a trace ID equal to (for example) 2485ec27856c56f4, you get output resembling the following:

    +

    Once you find any log with an error, you can look for the trace ID in the +message. Paste that into Zipkin to visualize the entire trace, regardless of +how many services the first request ended up hitting.

    -
    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]]
    +
    backend.log:  2020-04-09 17:45:40.516 ERROR [backend,5e8eeec48b08e26882aba313eb08f0a4,dcc1df555b5777b3,true] 97203 --- [nio-9000-exec-1] o.s.c.s.i.web.ExceptionLoggingFilter     : Uncaught exception thrown
+frontend.log:2020-04-09 17:45:40.574 ERROR [frontend,5e8eeec48b08e26882aba313eb08f0a4,82aba313eb08f0a4,true] 97192 --- [nio-8081-exec-2] o.s.c.s.i.web.ExceptionLoggingFilter     : Uncaught exception thrown
    +

    Above, you’ll notice the trace ID is 5e8eeec48b08e26882aba313eb08f0a4, for +example. This log configuration was automatically setup by Sleuth.

    +
    +

    If you use a log aggregating tool (such as Kibana, Splunk, and others), you can order the events that took place. An example from Kibana would resemble the following image:

    @@ -652,33 +503,41 @@ Otherwise, your custom logback file does not properly read the property.
    -

    1.2.6. Propagating Span Context

    +

    1.1.3. Service Dependency Graph

    -

    The span context is the state that must get propagated to any child spans across process boundaries. -Part of the Span Context is the Baggage. The trace and span IDs are a required part of the span context. -Baggage is an optional part.

    +

    When you consider distributed tracing tracks requests, it makes sense that +trace data can paint a picture of your architecture.

    -

    Baggage is a set of key:value pairs stored in the span context. -Baggage travels together with the trace and is attached to every span. -Spring Cloud Sleuth understands that a header is baggage-related if the HTTP header is prefixed with baggage- and, for messaging, it starts with baggage_.

    -
    -
    - - - - - -
    - - -There is currently no limitation of the count or size of baggage items. -However, keep in mind that too many can decrease system throughput or increase RPC latency. -In extreme cases, too much baggage can crash the application, due to exceeding transport-level message or header capacity. -
    +

    Zipkin includes a tool to build service dependency diagrams from traces, +including the count of calls and how many errors exist.

    -

    The following example shows setting baggage on a span:

    +

    The example application will make a simple diagram like this, but your real +environment diagram may be more complex. +image::https://raw.githubusercontent.com/spring-cloud/spring-cloud-sleuth/master/docs/src/main/asciidoc/images/zipkin-depedendencies.png[Zipkin Dependencies]

    +
    +
    +

    Note: Production environments will generate a lot of data. You will likely +need to run a separate service to aggregate the dependency graph. You can learn +more here.

    +
    +
    +
    +

    1.1.4. Request scoped properties (Baggage)

    +
    +

    Distributed tracing works by propagating fields inside and across services that +connect the trace together: traceId and spanId notably. The context that holds +these fields can optionally push other fields that need to be consistent +regardless of many services are touched. The simple name for these extra fields +is "Baggage".

    +
    +
    +

    Sleuth allows you to define which baggage are permitted to exist in the trace +context, including what header names are used.

    +
    +
    +

    The following example shows setting baggage values:

    @@ -687,49 +546,34 @@ BUSINESS_PROCESS.updateValue(initialSpan.context(), "ALM"); COUNTRY_CODE.updateValue(initialSpan.context(), "FO");
    +
    + + + + + +
    + + +There is currently no limitation of the count or size of baggage +items. Keep in mind that too many can decrease system throughput or increase +RPC latency. In extreme cases, too much baggage can crash the application, due +to exceeding transport-level message or header capacity. +
    +
    -
    Baggage versus Span Tags
    +
    Baggage versus Tags
    -

    Baggage travels with the trace (every child span contains the baggage of its parent). -Zipkin has no knowledge of baggage and does not receive that information.

    -
    -
    - - - - - -
    - - -Starting from Sleuth 2.0.0 you have to pass the baggage key names explicitly -in your project configuration. Read more about that setup here -
    +

    Like trace IDs, Baggage is attached to messages or requests, usually as +headers. Tags are key value pairs sent in a Span to Zipkin. Baggage values are +not added spans by default, which means you can’t search based on Baggage +unless you opt-in.

    -

    Tags are attached to a specific span. In other words, they are presented only for that particular span. -However, you can search by tag to find the trace, assuming a span having the searched tag value exists.

    -
    -
    -

    If you want to be able to lookup a span based on baggage, you should add a corresponding entry as a tag in the root span.

    -
    -
    - - - - - -
    - - -The span must be in scope. -
    -
    -
    -

    The following listing shows integration tests that use baggage:

    +

    To make baggage also tags, use the property spring.sleuth.baggage.tag-fields +like so:

    -
    The setup
    spring:
   sleuth:
@@ -741,17 +585,11 @@ The span must be in scope.
         - country-code
    -
    -
    The code
    -
    -
    Tags.BAGGAGE_FIELD.tag(BUSINESS_PROCESS, initialSpan);
    -
    -
    -

    1.3. Adding Sleuth to the Project

    +

    1.2. Adding Sleuth to the Project

    This section addresses how to add Sleuth to your project with either Maven or Gradle.

    @@ -768,78 +606,7 @@ To ensure that your application name is properly displayed in Zipkin, set the
    -

    1.3.1. Only Sleuth (log correlation)

    -
    -

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

    -
    -
    -

    The following example shows how to add Sleuth with Maven:

    -
    -
    -
    Maven
    -
    -
    <dependencyManagement> (1)
-      <dependencies>
-          <dependency>
-              <groupId>org.springframework.cloud</groupId>
-              <artifactId>spring-cloud-dependencies</artifactId>
-              <version>${release.train.version}</version>
-              <type>pom</type>
-              <scope>import</scope>
-          </dependency>
-      </dependencies>
-</dependencyManagement>
-
-<dependency> (2)
-    <groupId>org.springframework.cloud</groupId>
-    <artifactId>spring-cloud-starter-sleuth</artifactId>
-</dependency>
    -
    -
    -
    - - - - - - - - - -
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    -
    -
    -

    The following example shows how to add Sleuth with Gradle:

    -
    -
    -
    Gradle
    -
    -
    dependencyManagement { (1)
-    imports {
-        mavenBom "org.springframework.cloud:spring-cloud-dependencies:${releaseTrainVersion}"
-    }
-}
-
-dependencies { (2)
-    compile "org.springframework.cloud:spring-cloud-starter-sleuth"
-}
    -
    -
    -
    - - - - - - - - - -
    1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    -
    -
    -
    -

    1.3.2. Sleuth with Zipkin via HTTP

    +

    1.2.1. Sleuth with Zipkin via HTTP

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

    @@ -910,7 +677,7 @@ dependencies { (2)
    -

    1.3.3. Sleuth with Zipkin over RabbitMQ or Kafka

    +

    1.2.2. Sleuth with Zipkin over RabbitMQ or Kafka

    If you want to use RabbitMQ or Kafka instead of HTTP, add the spring-rabbit or spring-kafka dependency. The default destination name is zipkin.

    @@ -1015,9 +782,8 @@ dependencies {
    -
    -
    -

    1.4. Overriding the auto-configuration of Zipkin

    +
    +

    1.2.3. Overriding the auto-configuration of Zipkin

    Spring Cloud Sleuth supports sending traces to multiple tracing systems as of version 2.1.0. In order to get this to work, every tracing system needs to have a Reporter<Span> and Sender. @@ -1074,164 +840,82 @@ protected static class MyConfig {

    -
    -
    -
    -

    2. Additional Resources

    -
    +
    +

    1.2.4. Only Sleuth (log correlation)

    -

    You can watch a video of Reshmi Krishna and Marcin Grzejszczak talking about Spring Cloud -Sleuth and Zipkin by clicking here.

    +

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

    -

    You can check different setups of Sleuth and Brave in the openzipkin/sleuth-webmvc-example repository.

    +

    The following example shows how to add Sleuth with Maven:

    -
    -
    -
    -

    3. 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, as shown in the following example logs:

      -
      +
      +
      Maven
      -
      2016-02-02 15:30:57.902  INFO [bar,6bfd228dc00d216b,6bfd228dc00d216b] 23030 --- [nio-8081-exec-3] ...
-2016-02-02 15:30:58.372 ERROR [bar,6bfd228dc00d216b,6bfd228dc00d216b] 23030 --- [nio-8081-exec-3] ...
-2016-02-02 15:31:01.936  INFO [bar,46ab0d418373cbc9,46ab0d418373cbc9] 23030 --- [nio-8081-exec-4] ...
      +
      <dependencyManagement> (1)
+      <dependencies>
+          <dependency>
+              <groupId>org.springframework.cloud</groupId>
+              <artifactId>spring-cloud-dependencies</artifactId>
+              <version>${release.train.version}</version>
+              <type>pom</type>
+              <scope>import</scope>
+          </dependency>
+      </dependencies>
+</dependencyManagement>
+
+<dependency> (2)
+    <groupId>org.springframework.cloud</groupId>
+    <artifactId>spring-cloud-starter-sleuth</artifactId>
+</dependency>
      +
      + + + + + + + + + +
      1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
      2Add the dependency to spring-cloud-starter-sleuth.
      +
      -

      Notice the [appname,traceId,spanId] entries from the MDC:

      +

      The following example shows how to add Sleuth with Gradle:

      -
      -
        -
      • -

        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.

        -
        • -
      +
      +
      Gradle
      +
      +
      dependencyManagement { (1)
+    imports {
+        mavenBom "org.springframework.cloud:spring-cloud-dependencies:${releaseTrainVersion}"
+    }
+}
+
+dependencies { (2)
+    compile "org.springframework.cloud:spring-cloud-starter-sleuth"
+}
      -
      • -
    • -

      Provides an abstraction over common distributed tracing data models: traces, spans (forming a DAG), annotations, and key-value annotations. -Spring Cloud Sleuth is loosely based on HTrace but is compatible with Zipkin (Dapper).

      -
      • -
    • -

      Sleuth records timing information to aid in latency analysis. -By 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. -To that end, Sleuth:

      -
      -
        -
      • -

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

        -
        • -
      • -

        Includes opinionated instrumentation of layers such as HTTP.

        -
        • -
      • -

        Includes a 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, and Feign client).

      -
      • -
    • -

      Sleuth includes default logic to join a trace across HTTP or messaging boundaries. -For example, HTTP propagation works over Zipkin-compatible request headers.

      -
      • -
    • -

      Sleuth can propagate context (also known as baggage) between processes. -Consequently, if you set a baggage element on a Span, it is sent downstream to other processes over either HTTP or messaging.

      -
      • -
    • -

      Provides a way to create or continue spans and add tags and logs through annotations.

      -
      • -
    • -

      If spring-cloud-sleuth-zipkin is on the classpath, the app generates and collects Zipkin-compatible traces. -By default, it sends them over HTTP to a Zipkin server on localhost (port 9411). -You can configure the location of the service by setting spring.zipkin.baseUrl.

      -
      -
        -
      • -

        If you depend on spring-rabbit, your app sends traces to a RabbitMQ broker instead of HTTP.

        -
        • -
      • -

        If you depend on spring-kafka, and set spring.zipkin.sender.type: kafka, your app sends traces to a Kafka broker instead of HTTP.

        -
        • -
      -
      -
      • -
    -
    -
    +
    - - + + + + + +
    - - -spring-cloud-sleuth-stream is deprecated and should no longer be used. -1We recommend that you add the dependency management through the Spring BOM so that you need not manage versions yourself.
    2Add the dependency to spring-cloud-starter-sleuth.
    -
    -
    -
    - - - - - -
    - - -The SLF4J MDC is always set and logback users immediately see the trace and span IDs in logs per the example -shown earlier. -Other logging systems have to configure their own formatter to get the same result. -The default is as follows: -logging.pattern.level set to %5p [${spring.zipkin.service.name:${spring.application.name:-}},%X{traceId:-},%X{spanId:-}] -(this is a Spring Boot feature for logback users). -If you do not use SLF4J, this pattern is NOT automatically applied. -
    -
    -
    - - - - - -
    - - -Starting with version 3.0.0, the logging pattern has changed. -We’ve converted the MDC entries from B3 to non B3 keys (e.g. X-B3-TraceId to traceId). -
    -

    4. Introduction

    +

    2. How Sleuth works

    Spring Cloud Sleuth is a layer over Brave.

    @@ -1265,14 +949,14 @@ predefined, but is flexible otherwise.

    Sleuth configures everything you need to get started with tracing. Sleuth configures where trace data (spans) are reported to, how many traces to keep -(sampling), if remote fields (baggage) and which libraries are traced. +(sampling), if remote fields (baggage) are sent, and which libraries are traced. Sleuth also adds annotation based tracing features and some instrumentation not available otherwise, such as Reactor. If cannot find the configuration you are looking for in the documentation, ask Gitter before assuming something cannot be done.

    -

    4.1. Brave Basics

    +

    2.1. Brave Basics

    Most instrumentation work is done for you by default. Sleuth provides beans to allow you to change what’s traced, and it even provides annotations to avoid @@ -1297,7 +981,7 @@ are some pointers.

    -

    5. Sampling

    +

    3. Sampling

    By default Spring Cloud Sleuth doesn’t sample spans. @@ -1348,7 +1032,7 @@ Doing so forces the current request to be sampled regardless of configuration.

    -

    6. Baggage

    +

    4. Baggage

    Baggage are fields that are propagated with the trace, optionally out of process. You can use @@ -1393,7 +1077,7 @@ Remember that adding entries to MDC can drastically decrease the performance of spring.sleuth.baggage.tag-fields with a list of whitelisted baggage keys. To disable the feature you have to pass the spring.sleuth.propagation.tag.enabled=false property.

    -

    6.1. Java configuration

    +

    4.1. Java configuration

    If you need to do anything more advanced than above, do not define properties and instead use a @Bean config for the baggage fields you use. @@ -1406,7 +1090,7 @@ Remember that adding entries to MDC can drastically decrease the performance of

    -

    7. Instrumentation

    +

    5. Instrumentation

    Spring Cloud Sleuth automatically instruments all your Spring applications, so you should not have to do anything to activate it. @@ -1432,7 +1116,7 @@ Tags are collected and exported only if there is a Sampler that all

    -

    8. Span lifecycle

    +

    6. Span lifecycle

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

    @@ -1471,7 +1155,7 @@ Spring Cloud Sleuth creates an instance of Tracer for you. In order
    -

    8.1. Creating and finishing spans

    +

    6.1. Creating and finishing spans

    You can manually create spans by using the Tracer, as shown in the following example:

    @@ -1526,7 +1210,7 @@ Your names have to be explicit and concrete. Big names lead to latency issues an
    -

    8.2. Continuing Spans

    +

    6.2. Continuing Spans

    Sometimes, you do not want to create a new span but you want to continue one. An example of such a situation might be as follows:

    @@ -1563,7 +1247,7 @@ finally {
    -

    8.3. Creating a Span with an explicit Parent

    +

    6.3. Creating a Span with an explicit Parent

    You might want to start a new span and provide an explicit parent of that span. Assume that the parent of a span is in one thread and you want to start a new span in another thread. @@ -1611,7 +1295,7 @@ After creating such a span, you must finish it. Otherwise it is not reported (fo

    -

    9. Naming spans

    +

    7. Naming spans

    Picking a span name is not a trivial task. A span name should depict an operation name. @@ -1637,7 +1321,7 @@ The name should be low cardinality, so it should not include identifiers.

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

    -

    9.1. @SpanName Annotation

    +

    7.1. @SpanName Annotation

    You can name the span explicitly by using the @SpanName annotation, as shown in the following example:

    @@ -1668,7 +1352,7 @@ future.get();
    -

    9.2. toString() method

    +

    7.2. toString() method

    It is pretty rare to create separate classes for Runnable or Callable. Typically, one creates an anonymous instance of those classes. @@ -1700,13 +1384,13 @@ future.get();

    -

    10. Managing Spans with Annotations

    +

    8. Managing Spans with Annotations

    You can manage spans with a variety of annotations.

    -

    10.1. Rationale

    +

    8.1. Rationale

    There are a number of good reasons to manage spans with annotations, including:

    @@ -1729,7 +1413,7 @@ Now you can provide annotations over interfaces and the arguments of those inter
    -

    10.2. Creating New Spans

    +

    8.2. Creating New Spans

    If you do not want to create local spans manually, you can use the @NewSpan annotation. Also, we provide the @SpanTag annotation to add tags in an automated fashion.

    @@ -1785,7 +1469,7 @@ concrete one wins (in this case customNameOnTestMethod3 is set).

    -

    10.3. Continuing Spans

    +

    8.3. Continuing Spans

    If you want to add tags and annotations to an existing span, you can use the @ContinueSpan annotation, as shown in the following example:

    @@ -1821,7 +1505,7 @@ this.testBean.testMethod13();
    -

    10.4. Advanced Tag Setting

    +

    8.4. Advanced Tag Setting

    There are 3 different ways to add tags to a span. All of them are controlled by the SpanTag annotation. The precedence is as follows:

    @@ -1843,7 +1527,7 @@ The default implementation uses SPEL expression resolution.
    -

    10.4.1. Custom extractor

    +

    8.4.1. Custom extractor

    The value of the tag for the following method is computed by an implementation of TagValueResolver interface. Its class name has to be passed as the value of the resolver attribute.

    @@ -1875,7 +1559,7 @@ public TagValueResolver tagValueResolver() {
    -

    10.4.2. Resolving Expressions for a Value

    +

    8.4.2. Resolving Expressions for a Value

    Consider the following annotated method:

    @@ -1893,7 +1577,7 @@ If you want to use some other expression resolution mechanism, you can create yo
    -

    10.4.3. Using the toString() method

    +

    8.4.3. Using the toString() method

    Consider the following annotated method:

    @@ -1912,7 +1596,7 @@ public void getAnnotationForArgumentToString(@SpanTag("test") Long param) {
    -

    11. Customizations

    +

    9. Customizations

    The Tracer object is fully managed by sleuth, so you rarely need to affect it. That said, @@ -1946,9 +1630,9 @@ customize behaviour:

    -

    11.1. HTTP

    +

    9.1. HTTP

    -

    11.1.1. Data Policy

    +

    9.1.1. Data Policy

    The default span data policy for HTTP requests is described in Brave: github.com/openzipkin/brave/tree/master/instrumentation/http#span-data-policy

    @@ -1990,7 +1674,7 @@ class Config {
    -

    11.1.2. Sampling

    +

    9.1.2. Sampling

    If client /server sampling is required, just register a bean of type brave.sampler.SamplerFunction<HttpRequest> and name the bean @@ -2033,7 +1717,7 @@ class Config {

    -

    11.2. TracingFilter

    +

    9.2. TracingFilter

    You can also modify the behavior of the TracingFilter, which is the component that is responsible for processing the input HTTP request and adding tags basing on the HTTP response. You can customize the tags or modify the response headers by registering your own instance of the TracingFilter bean.

    @@ -2074,7 +1758,7 @@ class MyFilter extends GenericFilterBean {
    -

    11.3. Messaging

    +

    9.3. Messaging

    Sleuth automatically configures the MessagingTracing bean which serves as a foundation for Messaging instrumentation such as Kafka or JMS.

    @@ -2107,7 +1791,7 @@ class Config {
    -

    11.4. RPC

    +

    9.4. RPC

    Sleuth automatically configures the RpcTracing bean which serves as a foundation for RPC instrumentation such as gRPC or Dubbo.

    @@ -2148,7 +1832,7 @@ class Config {
    -

    11.5. Custom service name

    +

    9.5. Custom service name

    By default, Sleuth assumes that, when you send a span to Zipkin, you want the span’s service name to be equal to the value of the spring.application.name property. That is not always the case, though. @@ -2162,7 +1846,7 @@ To achieve that, you can pass the following property to your application to over

    -

    11.6. Customization of Reported Spans

    +

    9.6. Customization of Reported Spans

    Before reporting spans (for example, to Zipkin) you may want to modify that span in some way. You can do so by using the FinishedSpanHandler interface.

    @@ -2205,7 +1889,7 @@ FinishedSpanHandler handlerTwo() {
    -

    11.7. Host Locator

    +

    9.7. Host Locator

    @@ -2236,7 +1920,7 @@ If those are not set, we try to retrieve the host name from the network interfac
    -

    12. Sending Spans to Zipkin

    +

    10. Sending Spans to Zipkin

    By default, if you add spring-cloud-starter-zipkin as a dependency to your project, when the span is closed, it is sent to Zipkin over HTTP. @@ -2317,7 +2001,7 @@ object, you will have to create a bean of zipkin2.reporter.Sender t

    -

    13. Zipkin Stream Span Consumer

    +

    11. Zipkin Stream Span Consumer

    @@ -2339,10 +2023,10 @@ In the Finchley release, it got removed.
    -

    14. Integrations

    +

    12. Integrations

    -

    14.1. OpenTracing

    +

    12.1. OpenTracing

    Spring Cloud Sleuth is compatible with OpenTracing. If you have OpenTracing on the classpath, we automatically register the OpenTracing Tracer bean. @@ -2350,7 +2034,7 @@ If you wish to disable this, set spring.sleuth.opentracing.enabled

    -

    14.2. Runnable and Callable

    +

    12.2. Runnable and Callable

    If you wrap your logic in Runnable or Callable, you can wrap those classes in their Sleuth representative, as shown in the following example for Runnable:

    @@ -2406,13 +2090,13 @@ Callable<String> traceCallableFromTracer = this.tracing.currentTraceContex
    -

    14.3. Spring Cloud CircuitBreaker

    +

    12.3. Spring Cloud CircuitBreaker

    If you have Spring Cloud CircuitBreaker on the classpath, we will wrap the passed command Supplier and the fallback Function in its trace representations. In order to disable this instrumentation set spring.sleuth.circuitbreaker.enabled to false.

    -

    14.4. RxJava

    +

    12.4. RxJava

    We registering a custom RxJavaSchedulersHook that wraps all Action0 instances in their Sleuth representative, which is called TraceAction. The hook either starts or continues a span, depending on whether tracing was already going on before the Action was scheduled. @@ -2437,12 +2121,12 @@ the Reactor support.

    -

    14.5. HTTP integration

    +

    12.5. HTTP integration

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

    -

    14.5.1. HTTP Filter

    +

    12.5.1. HTTP Filter

    Through the TracingFilter, all sampled incoming requests result in creation of a Span. That Span’s name is http: + the path to which the request was sent. @@ -2466,7 +2150,7 @@ to true.

    -

    14.5.2. HandlerInterceptor

    +

    12.5.2. HandlerInterceptor

    Since we want the span names to be precise, we use 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. @@ -2476,13 +2160,13 @@ In that case, please file an issue in Spring Cloud Sleuth.

    -

    14.5.3. Async Servlet support

    +

    12.5.3. Async Servlet support

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

    -

    14.5.4. WebFlux support

    +

    12.5.4. WebFlux support

    Through TraceWebFilter, all sampled incoming requests result in creation of a Span. That Span’s name is http: + the path to which the request was sent. @@ -2497,7 +2181,7 @@ If you want to reuse Sleuth’s default skip patterns and append your own, p

    -

    14.5.5. Dubbo RPC support

    +

    12.5.5. Dubbo RPC support

    Via the integration with Brave, Spring Cloud Sleuth supports Dubbo. It’s enough to add the brave-instrumentation-dubbo dependency:

    @@ -2526,9 +2210,9 @@ An example of Spring Cloud Sleuth and Dubbo can be found -

    14.6. HTTP Client Integration

    +

    12.6. HTTP Client Integration

    -

    14.6.1. Synchronous Rest Template

    +

    12.6.1. Synchronous Rest Template

    We inject a RestTemplate interceptor to ensure that all the tracing information is passed to the requests. Each time a call is made, a new Span is created. @@ -2550,7 +2234,7 @@ If you create a RestTemplate instance with a new keywo

    -

    14.6.2. Asynchronous Rest Template

    +

    12.6.2. Asynchronous Rest Template

    @@ -2607,7 +2291,7 @@ static class Config {
    -

    14.6.3. WebClient

    +

    12.6.3. WebClient

    We inject a ExchangeFilterFunction implementation that creates a span and, through on-success and on-error callbacks, takes care of closing client-side spans.

    @@ -2629,7 +2313,7 @@ If you create a WebClient instance with a new keyword,
    -

    14.6.4. Traverson

    +

    12.6.4. Traverson

    If you use the Traverson library, you can inject a RestTemplate as a bean into your Traverson object. Since RestTemplate is already intercepted, you get full support for tracing in your client. The following pseudo code @@ -2646,7 +2330,7 @@ Traverson traverson = new Traverson(URI.create("https://some/address"),

    -

    14.6.5. Apache HttpClientBuilder and HttpAsyncClientBuilder

    +

    12.6.5. Apache HttpClientBuilder and HttpAsyncClientBuilder

    We instrument the HttpClientBuilder and HttpAsyncClientBuilder so that tracing context gets injected to the sent requests.

    @@ -2656,7 +2340,7 @@ tracing context gets injected to the sent requests.

    -

    14.6.6. Netty HttpClient

    +

    12.6.6. Netty HttpClient

    We instrument the Netty’s HttpClient.

    @@ -2678,7 +2362,7 @@ If you create a HttpClient instance with a new keyword
    -

    14.6.7. UserInfoRestTemplateCustomizer

    +

    12.6.7. UserInfoRestTemplateCustomizer

    We instrument the Spring Security’s UserInfoRestTemplateCustomizer.

    @@ -2688,7 +2372,7 @@ If you create a HttpClient instance with a new keyword
    -

    14.7. Feign

    +

    12.7. Feign

    By default, Spring Cloud Sleuth provides integration with Feign through TraceFeignClientAutoConfiguration. You can disable it entirely by setting spring.sleuth.feign.enabled to false. @@ -2702,12 +2386,12 @@ However, all the default instrumentation is still there.

    -

    14.8. gRPC

    +

    12.8. gRPC

    Spring Cloud Sleuth provides instrumentation for gRPC through TraceGrpcAutoConfiguration. You can disable it entirely by setting spring.sleuth.grpc.enabled to false.

    -

    14.8.1. Variant 1

    +

    12.8.1. Variant 1

    Dependencies
    @@ -2776,16 +2460,16 @@ Spring Cloud Sleuth provides a SpringAwareManagedChannelBuilder tha
    -

    14.8.2. Variant 2

    +

    12.8.2. Variant 2

    Grpc Spring Boot Starter automatically detects the presence of Spring Cloud Sleuth and brave’s instrumentation for gRPC and registers the necessary client and/or server tooling.

    -

    14.9. Asynchronous Communication

    +

    12.9. Asynchronous Communication

    -

    14.9.1. @Async Annotated methods

    +

    12.9.1. @Async Annotated methods

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

    @@ -2808,7 +2492,7 @@ You can disable this behavior by setting the value of spring.sleuth.async.
    -

    14.9.2. @Scheduled Annotated Methods

    +

    12.9.2. @Scheduled Annotated Methods

    In Spring Cloud Sleuth, we instrument scheduled method execution so that the tracing information is passed between threads. You can disable this behavior by setting the value of spring.sleuth.scheduled.enabled to false.

    @@ -2831,7 +2515,7 @@ You can disable this behavior by setting the value of spring.sleuth.schedu
    -

    14.9.3. Executor, ExecutorService, and ScheduledExecutorService

    +

    12.9.3. Executor, ExecutorService, and ScheduledExecutorService

    We provide LazyTraceExecutor, TraceableExecutorService, and TraceableScheduledExecutorService. Those implementations create spans each time a new task is submitted, invoked, or scheduled.

    @@ -2918,12 +2602,12 @@ to add the @Role(BeanDefinition.ROLE_INFRASTRUCTURE) on your
    -

    14.10. Messaging

    +

    12.10. Messaging

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

    -

    14.10.1. Spring Integration and Spring Cloud Stream

    +

    12.10.1. Spring Integration and Spring Cloud Stream

    Spring Cloud Sleuth integrates with Spring Integration. It creates spans for publish and subscribe events. @@ -2962,7 +2646,7 @@ it’s enough for you to register beans of types:

    -

    14.10.2. Spring RabbitMq

    +

    12.10.2. Spring RabbitMq

    We instrument the RabbitTemplate so that tracing headers get injected into the message.

    @@ -2972,7 +2656,7 @@ into the message.

    -

    14.10.3. Spring Kafka

    +

    12.10.3. Spring Kafka

    We instrument the Spring Kafka’s ProducerFactory and ConsumerFactory so that tracing headers get injected into the created Spring Kafka’s @@ -2983,7 +2667,7 @@ so that tracing headers get injected into the created Spring Kafka’s

    -

    14.10.4. Spring Kafka Streams

    +

    12.10.4. Spring Kafka Streams

    We instrument the KafkaStreams KafkaClientSupplier so that tracing headers get injected into the Producer and Consumer`s. A `KafkaStreamsTracing bean @@ -2995,7 +2679,7 @@ allows for further instrumentation through additional TransformerSupplier<

    -

    14.10.5. Spring JMS

    +

    12.10.5. Spring JMS

    We instrument the JmsTemplate so that tracing headers get injected into the message. We also support @JmsListener annotated methods on the consumer side.

    @@ -3017,7 +2701,7 @@ We don’t support baggage propagation for JMS
    -

    14.10.6. Spring Cloud AWS Messaging SQS

    +

    12.10.6. Spring Cloud AWS Messaging SQS

    We instrument @SqsListener which is provided by org.springframework.cloud:spring-cloud-aws-messaging so that tracing headers get extracted from the message and a trace gets put into the context.

    @@ -3028,14 +2712,14 @@ so that tracing headers get extracted from the message and a trace gets put into
    -

    14.11. Redis

    +

    12.11. Redis

    We set tracing property to Lettcue ClientResources instance to enable Brave tracing built in Lettuce . To disable Redis support, set the spring.sleuth.redis.enabled property to false.

    -

    14.12. Quartz

    +

    12.12. Quartz

    We instrument quartz jobs by adding Job/Trigger listeners to the Quartz Scheduler.

    @@ -3044,7 +2728,7 @@ To disable Redis support, set the spring.sleuth.redis.enabled prope
    -

    14.13. Project Reactor

    +

    12.13. Project Reactor

    For projects depending on Project Reactor such as Spring Cloud Gateway, we suggest turning the spring.sleuth.reactor.decorate-on-each option to false. That way an increased performance gain should be observed in comparison to the standard instrumentation mechanism. What this option does is it will wrap decorate onLast operator instead of onEach which will result in creation of far fewer objects. The downside of this is that when Project Reactor will change threads, the trace propagation will continue without issues, however anything relying on the ThreadLocal such as e.g. MDC entries can be buggy.

    @@ -3052,7 +2736,7 @@ To disable Redis support, set the spring.sleuth.redis.enabled prope
    -

    15. Configuration properties

    +

    13. Configuration properties

    To see the list of all Sleuth related configuration properties please check the Appendix page.

    @@ -3060,7 +2744,7 @@ To disable Redis support, set the spring.sleuth.redis.enabled prope
    -

    16. Running examples

    +

    14. Running examples

    You can see the running examples deployed in the Pivotal Web Services. diff --git a/reference/htmlsingle/images/zipkin-dependencies.png b/reference/htmlsingle/images/zipkin-dependencies.png new file mode 100644 index 0000000000000000000000000000000000000000..ae09dafe005c1ea7f9b60665ebf68e93b72ba93f GIT binary patch literal 46703 zcmagGby!r}`#uaqml%|UAWC;jBM2xh-5@aZ(2cZ!f{3(qNq580Dj?lCl!U;*5E4W4 z+Z^?L&i5SO>-7&Vm_2*%wbx$jdG6=F@5eVPO0opFyEhl_JH6%mjBA9*O8IIo+z(P=_*7KB_GexKsgSrC}g`JJ7e@Gcl*A0$h*6f z`hQ8^6gRaZlCaqnJ>)C7I=}G4w71lzy@T?V>V*(bTI#Fa$FG{zqL(H;C|~&Uj}U#r zv!SdQ;Pi@+;@7tHiLA@x`(%x>*o}`V3__u$Dv+n+d2o{|OZ<~=@em`)C!16AzNa#b zp9F4c;zh20q&>HTDC^JO_^1>urOmWrpLFYLi10){z5VrZ__B#$pLm)Lgm#59K9aOD zjD`vGQvl{`49fSoA0RRN?y@PeS`>^uA*Jcm>KZW(1i$res8$AzXbNtiq&@GcL6tm5^aG#Ab=@g{>&* zJVden;B8OtQ<&QVzUPnEmk?Oyd-Eri)_2IEAMd& zL**e60bPWu?C|pmMgesiX37p3gv@GI*mI41dUdQqLRUh*fFxNT3DaTqY9d`KNT8d< zSw`YI`hlH`7?j8$)J__iv6IO#jJM7~hAV@g9mdu9$mE>s)(0X5{#-J(AglHR6B*9Y 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