spring cloud sleuth 分佈式跟蹤的解決方案,
span 跨度,基本工作單元。
包含:
-
64位的唯一標識(id),
-
描述
-
時間戳事件
-
鍵值對註解
-
spanId
-
span父Id
初始化的時候被稱爲root span, id 和 trace Id 相同。
trace跟蹤
共享root span ,span組成的樹狀結構
64位的唯一標識(id),該trace中所有的span都共享該trace的Id
annotation(標註)
用來記錄事件的存在,定義請求的開始和結束
- cs client sent 客戶端發送(一個請求),該標註描述了span的開始
- sr server received 服務端接收 ,服務端獲得請求並處理。sr-cs=網絡延遲
- ss server sent 服務端發送。表明完成請求處理(當響應發回客戶端時),ss-sr=服務器端處理請求所需的時間
- cr client received 客戶端接收,span結束的標識。客戶端成功接收到服務器端的響應。cr - cs= 客戶端發送請求到服務器響應的所需時間。
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-starter-sleuth</artifactId>
</dependency>
logging:
level:
root: INFO
org.springframework.cloud.sleuth: DEBUG
# org.springframework.web.servlet.DispatcherServlet: DEBUG
sleuth與elk配合
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-starter-sleuth</artifactId>
</dependency>
<dependency>
<groupId>net.logstash.logback</groupId>
<artifactId>logstash-logback-encoder</artifactId>
<version>4.6</version>
</dependency>
resources目錄創建 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}" />
<property name="CONSOLE_LOG_PATTERN"
value="%clr(%d{yyyy-MM-dd HH:mm:ss.SSS}){faint} %clr(${LOG_LEVEL_PATTERN:-%5p}) %clr([${springAppName:-},%X{X-B3-TraceId:-},%X{X-B3-SpanId:-},%X{X-B3-ParentSpanId:-},%X{X-Span-Export:-}]){yellow} %clr(${PID:- }){magenta} %clr(---){faint} %clr([%15.15t]){faint} %clr(%-40.40logger{39}){cyan} %clr(:){faint} %m%n${LOG_EXCEPTION_CONVERSION_WORD:-%wEx}" />
<!-- 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": "${springAppName:-}",
"trace": "%X{X-B3-TraceId:-}",
"span": "%X{X-B3-SpanId:-}",
"parent": "%X{X-B3-ParentSpanId:-}",
"exportable": "%X{X-Span-Export:-}",
"pid": "${PID:-}",
"thread": "%thread",
"class": "%logger{40}",
"rest": "%message"
}
</pattern>
</pattern>
</providers>
</encoder>
</appender>
<root level="INFO">
<appender-ref ref="console" />
<appender-ref ref="logstash" />
<!--<appender-ref ref="flatfile"/> -->
</root>
</configuration>
編寫bootstrap.yml
spring:
application:
name: microservice-provider-user
# 注意:本例中的spring.application.name只能放在bootstrap.*文件中,不能放在application.*文件中,因爲我們使用了自定義的logback-spring.xml。
# 如果放在application.*文件中,自定義的logback文件將無法正確讀取屬性。
sleuth 與 zipkin
zipkin是 twitter開源的分佈式跟蹤系統,基於Dapper的論文設計而來。
收集系統的 時序數據,追蹤微服務架構的 系統延時
<dependency>
<groupId>io.zipkin.java</groupId>
<artifactId>zipkin-autoconfigure-ui</artifactId>
</dependency>
<dependency>
<groupId>io.zipkin.java</groupId>
<artifactId>zipkin-server</artifactId>
</dependency>
main方法
@SpringBootApplication
@EnableZipkinServer
public class ZipkinServerApplication {
public static void main(String[] args) {
SpringApplication.run(ZipkinServerApplication.class, args);
}
}
http://localhost:9411/zipkin/
service name 就是 spring: application: name: microservice-provider-user
start time 和 end time 起始時間和結束時間
Duration 持續 時間, 從 span創建到關閉所經歷的時間
annotations query 自定義查詢
微服務整合 Zipkin
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-starter-sleuth</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-sleuth-zipkin</artifactId>
</dependency>
spring:
zipkin:
base-url: http://localhost:9411
sleuth:
sampler:
percentage: 1.0
- percentage 採樣的請求的百分比,默認是0.1 ,即 10%
多種採集器
public Sampler defaultSampler(){
/*return new NeverSampler();
return new PercentageBasedSampler();*/
return new AlwaysSampler();
}
默認採集是10%,會忽略大量span