搭建Skywalking分布式链路追踪与监控，并接入Java项目的教程

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程序员云帆哥 发表于 2022/05/16 10:56:32 2022/05/16
【摘要】 一、简介   Skywalking是一个国产的开源框架，2015年有吴晟个人开源，2017年加入Apache孵化器，国人开源的产品，主要开发人员来自于华为，2019年4月17日Apache董事会批准SkyWalking成为顶级项目，支持Java、.Net、NodeJs等探针，数据存储支持Mysql、Elasticsearch等，跟Pinpoint一样采用字节码注入的方式实现代码的无侵入，探...

一、简介

   Skywalking是一个国产的开源框架，2015年有吴晟个人开源，2017年加入Apache孵化器，国人开源的产品，主要开发人员来自于华为，2019年4月17日Apache董事会批准SkyWalking成为顶级项目，支持Java、.Net、NodeJs等探针，数据存储支持Mysql、Elasticsearch等，跟Pinpoint一样采用字节码注入的方式实现代码的无侵入，探针采集数据粒度粗，但性能表现优秀，且对云原生支持，目前增长势头强劲，社区活跃。
   Skywalking是分布式系统的应用程序性能监视工具，专为微服务，云原生架构和基于容器（Docker，K8S,Mesos）架构而设计，它是一款优秀的APM（Application Performance Management）工具，包括了分布式追踪，性能指标分析和服务依赖分析等。
在这里插入图片描述

二、搭建教程

这边先采用windows的方式，在本地搭建。

1、官网下载包

官网地址：https://skywalking.apache.org/
在这里插入图片描述
主要有两种：一种是只支持Elasticsearch数据存储的，另一种支持多种数据存储的（如 H2、MySQL、TiDB、InfluxDB、ElasticSearch）。
我选用的是：v8.7.0 for H2/MySQL/TiDB/InfluxDB/ElasticSearch 7

2、压缩包解压

在这里插入图片描述

3、修改数据存储方式

配置文件位置在config/application.yml，如下图所示。
默认是H2，重启会丢失。我们可以根据需要，修改数据存储方式，大家熟悉MySQL多也可以用它，当然最为推荐的还是ElasticSearch，时序数据库性能要高很多。

storage:
  selector: ${SW_STORAGE:h2}
  elasticsearch:
    nameSpace: ${SW_NAMESPACE:""}
    clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200}
    protocol: ${SW_STORAGE_ES_HTTP_PROTOCOL:"http"}
    connectTimeout: ${SW_STORAGE_ES_CONNECT_TIMEOUT:500}
    socketTimeout: ${SW_STORAGE_ES_SOCKET_TIMEOUT:30000}
    user: ${SW_ES_USER:""}
    password: ${SW_ES_PASSWORD:""}
    trustStorePath: ${SW_STORAGE_ES_SSL_JKS_PATH:""}
    trustStorePass: ${SW_STORAGE_ES_SSL_JKS_PASS:""}
    secretsManagementFile: ${SW_ES_SECRETS_MANAGEMENT_FILE:""} # Secrets management file in the properties format includes the username, password, which are managed by 3rd party tool.
    dayStep: ${SW_STORAGE_DAY_STEP:1} # Represent the number of days in the one minute/hour/day index.
    indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:1} # Shard number of new indexes
    indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:1} # Replicas number of new indexes
    # Super data set has been defined in the codes, such as trace segments.The following 3 config would be improve es performance when storage super size data in es.
    superDatasetDayStep: ${SW_SUPERDATASET_STORAGE_DAY_STEP:-1} # Represent the number of days in the super size dataset record index, the default value is the same as dayStep when the value is less than 0
    superDatasetIndexShardsFactor: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_SHARDS_FACTOR:5} #  This factor provides more shards for the super data set, shards number = indexShardsNumber * superDatasetIndexShardsFactor. Also, this factor effects Zipkin and Jaeger traces.
    superDatasetIndexReplicasNumber: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_REPLICAS_NUMBER:0} # Represent the replicas number in the super size dataset record index, the default value is 0.
    indexTemplateOrder: ${SW_STORAGE_ES_INDEX_TEMPLATE_ORDER:0} # the order of index template
    bulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:5000} # Execute the async bulk record data every ${SW_STORAGE_ES_BULK_ACTIONS} requests
    # flush the bulk every 10 seconds whatever the number of requests
    # INT(flushInterval * 2/3) would be used for index refresh period.
    flushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:15}
    concurrentRequests: ${SW_STORAGE_ES_CONCURRENT_REQUESTS:2} # the number of concurrent requests
    resultWindowMaxSize: ${SW_STORAGE_ES_QUERY_MAX_WINDOW_SIZE:10000}
    metadataQueryMaxSize: ${SW_STORAGE_ES_QUERY_MAX_SIZE:5000}
    segmentQueryMaxSize: ${SW_STORAGE_ES_QUERY_SEGMENT_SIZE:200}
    profileTaskQueryMaxSize: ${SW_STORAGE_ES_QUERY_PROFILE_TASK_SIZE:200}
    oapAnalyzer: ${SW_STORAGE_ES_OAP_ANALYZER:"{\"analyzer\":{\"oap_analyzer\":{\"type\":\"stop\"}}}"} # the oap analyzer.
    oapLogAnalyzer: ${SW_STORAGE_ES_OAP_LOG_ANALYZER:"{\"analyzer\":{\"oap_log_analyzer\":{\"type\":\"standard\"}}}"} # the oap log analyzer. It could be customized by the ES analyzer configuration to support more language log formats, such as Chinese log, Japanese log and etc.
    advanced: ${SW_STORAGE_ES_ADVANCED:""}
  elasticsearch7:
    nameSpace: ${SW_NAMESPACE:""}
    clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200}
    protocol: ${SW_STORAGE_ES_HTTP_PROTOCOL:"http"}
    connectTimeout: ${SW_STORAGE_ES_CONNECT_TIMEOUT:500}
    socketTimeout: ${SW_STORAGE_ES_SOCKET_TIMEOUT:30000}
    trustStorePath: ${SW_STORAGE_ES_SSL_JKS_PATH:""}
    trustStorePass: ${SW_STORAGE_ES_SSL_JKS_PASS:""}
    dayStep: ${SW_STORAGE_DAY_STEP:1} # Represent the number of days in the one minute/hour/day index.
    indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:1} # Shard number of new indexes
    indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:1} # Replicas number of new indexes
    # Super data set has been defined in the codes, such as trace segments.The following 3 config would be improve es performance when storage super size data in es.
    superDatasetDayStep: ${SW_SUPERDATASET_STORAGE_DAY_STEP:-1} # Represent the number of days in the super size dataset record index, the default value is the same as dayStep when the value is less than 0
    superDatasetIndexShardsFactor: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_SHARDS_FACTOR:5} #  This factor provides more shards for the super data set, shards number = indexShardsNumber * superDatasetIndexShardsFactor. Also, this factor effects Zipkin and Jaeger traces.
    superDatasetIndexReplicasNumber: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_REPLICAS_NUMBER:0} # Represent the replicas number in the super size dataset record index, the default value is 0.
    indexTemplateOrder: ${SW_STORAGE_ES_INDEX_TEMPLATE_ORDER:0} # the order of index template
    user: ${SW_ES_USER:""}
    password: ${SW_ES_PASSWORD:""}
    secretsManagementFile: ${SW_ES_SECRETS_MANAGEMENT_FILE:""} # Secrets management file in the properties format includes the username, password, which are managed by 3rd party tool.
    bulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:5000} # Execute the async bulk record data every ${SW_STORAGE_ES_BULK_ACTIONS} requests
    # flush the bulk every 10 seconds whatever the number of requests
    # INT(flushInterval * 2/3) would be used for index refresh period.
    flushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:15}
    concurrentRequests: ${SW_STORAGE_ES_CONCURRENT_REQUESTS:2} # the number of concurrent requests
    resultWindowMaxSize: ${SW_STORAGE_ES_QUERY_MAX_WINDOW_SIZE:10000}
    metadataQueryMaxSize: ${SW_STORAGE_ES_QUERY_MAX_SIZE:5000}
    segmentQueryMaxSize: ${SW_STORAGE_ES_QUERY_SEGMENT_SIZE:200}
    profileTaskQueryMaxSize: ${SW_STORAGE_ES_QUERY_PROFILE_TASK_SIZE:200}
    oapAnalyzer: ${SW_STORAGE_ES_OAP_ANALYZER:"{\"analyzer\":{\"oap_analyzer\":{\"type\":\"stop\"}}}"} # the oap analyzer.
    oapLogAnalyzer: ${SW_STORAGE_ES_OAP_LOG_ANALYZER:"{\"analyzer\":{\"oap_log_analyzer\":{\"type\":\"standard\"}}}"} # the oap log analyzer. It could be customized by the ES analyzer configuration to support more language log formats, such as Chinese log, Japanese log and etc.
    advanced: ${SW_STORAGE_ES_ADVANCED:""}

  h2:
    driver: ${SW_STORAGE_H2_DRIVER:org.h2.jdbcx.JdbcDataSource}
    url: ${SW_STORAGE_H2_URL:jdbc:h2:mem:skywalking-oap-db;DB_CLOSE_DELAY=-1}
    user: ${SW_STORAGE_H2_USER:sa}
    metadataQueryMaxSize: ${SW_STORAGE_H2_QUERY_MAX_SIZE:5000}
    maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
    numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
  mysql:
    properties:
      jdbcUrl: ${SW_JDBC_URL:"jdbc:mysql://localhost:3306/swtest"}
      dataSource.user: ${SW_DATA_SOURCE_USER:root}
      dataSource.password: ${SW_DATA_SOURCE_PASSWORD:root}
      dataSource.cachePrepStmts: ${SW_DATA_SOURCE_CACHE_PREP_STMTS:true}
      dataSource.prepStmtCacheSize: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_SIZE:250}
      dataSource.prepStmtCacheSqlLimit: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_LIMIT:2048}
      dataSource.useServerPrepStmts: ${SW_DATA_SOURCE_USE_SERVER_PREP_STMTS:true}
    metadataQueryMaxSize: ${SW_STORAGE_MYSQL_QUERY_MAX_SIZE:5000}
    maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
    numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
  tidb:
    properties:
      jdbcUrl: ${SW_JDBC_URL:"jdbc:mysql://localhost:4000/tidbswtest"}
      dataSource.user: ${SW_DATA_SOURCE_USER:root}
      dataSource.password: ${SW_DATA_SOURCE_PASSWORD:""}
      dataSource.cachePrepStmts: ${SW_DATA_SOURCE_CACHE_PREP_STMTS:true}
      dataSource.prepStmtCacheSize: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_SIZE:250}
      dataSource.prepStmtCacheSqlLimit: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_LIMIT:2048}
      dataSource.useServerPrepStmts: ${SW_DATA_SOURCE_USE_SERVER_PREP_STMTS:true}
      dataSource.useAffectedRows: ${SW_DATA_SOURCE_USE_AFFECTED_ROWS:true}
    metadataQueryMaxSize: ${SW_STORAGE_MYSQL_QUERY_MAX_SIZE:5000}
    maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
    numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
  influxdb:
    # InfluxDB configuration
    url: ${SW_STORAGE_INFLUXDB_URL:http://localhost:8086}
    user: ${SW_STORAGE_INFLUXDB_USER:root}
    password: ${SW_STORAGE_INFLUXDB_PASSWORD:}
    database: ${SW_STORAGE_INFLUXDB_DATABASE:skywalking}
    actions: ${SW_STORAGE_INFLUXDB_ACTIONS:1000} # the number of actions to collect
    duration: ${SW_STORAGE_INFLUXDB_DURATION:1000} # the time to wait at most (milliseconds)
    batchEnabled: ${SW_STORAGE_INFLUXDB_BATCH_ENABLED:true}
    fetchTaskLogMaxSize: ${SW_STORAGE_INFLUXDB_FETCH_TASK_LOG_MAX_SIZE:5000} # the max number of fetch task log in a request
    connectionResponseFormat: ${SW_STORAGE_INFLUXDB_CONNECTION_RESPONSE_FORMAT:MSGPACK} # the response format of connection to influxDB, cannot be anything but MSGPACK or JSON.
  postgresql:
    properties:
      jdbcUrl: ${SW_JDBC_URL:"jdbc:postgresql://localhost:5432/skywalking"}
      dataSource.user: ${SW_DATA_SOURCE_USER:postgres}
      dataSource.password: ${SW_DATA_SOURCE_PASSWORD:123456}
      dataSource.cachePrepStmts: ${SW_DATA_SOURCE_CACHE_PREP_STMTS:true}
      dataSource.prepStmtCacheSize: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_SIZE:250}
      dataSource.prepStmtCacheSqlLimit: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_LIMIT:2048}
      dataSource.useServerPrepStmts: ${SW_DATA_SOURCE_USE_SERVER_PREP_STMTS:true}
    metadataQueryMaxSize: ${SW_STORAGE_MYSQL_QUERY_MAX_SIZE:5000}
    maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
    numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
  zipkin-elasticsearch7:
    nameSpace: ${SW_NAMESPACE:""}
    clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200}
    protocol: ${SW_STORAGE_ES_HTTP_PROTOCOL:"http"}
    trustStorePath: ${SW_STORAGE_ES_SSL_JKS_PATH:""}
    trustStorePass: ${SW_STORAGE_ES_SSL_JKS_PASS:""}
    dayStep: ${SW_STORAGE_DAY_STEP:1} # Represent the number of days in the one minute/hour/day index.
    indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:1} # Shard number of new indexes
    indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:1} # Replicas number of new indexes
    # Super data set has been defined in the codes, such as trace segments.The following 3 config would be improve es performance when storage super size data in es.
    superDatasetDayStep: ${SW_SUPERDATASET_STORAGE_DAY_STEP:-1} # Represent the number of days in the super size dataset record index, the default value is the same as dayStep when the value is less than 0
    superDatasetIndexShardsFactor: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_SHARDS_FACTOR:5} #  This factor provides more shards for the super data set, shards number = indexShardsNumber * superDatasetIndexShardsFactor. Also, this factor effects Zipkin and Jaeger traces.
    superDatasetIndexReplicasNumber: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_REPLICAS_NUMBER:0} # Represent the replicas number in the super size dataset record index, the default value is 0.
    user: ${SW_ES_USER:""}
    password: ${SW_ES_PASSWORD:""}
    secretsManagementFile: ${SW_ES_SECRETS_MANAGEMENT_FILE:""} # Secrets management file in the properties format includes the username, password, which are managed by 3rd party tool.
    bulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:5000} # Execute the async bulk record data every ${SW_STORAGE_ES_BULK_ACTIONS} requests
    # flush the bulk every 10 seconds whatever the number of requests
    # INT(flushInterval * 2/3) would be used for index refresh period.
    flushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:15}
    concurrentRequests: ${SW_STORAGE_ES_CONCURRENT_REQUESTS:2} # the number of concurrent requests
    resultWindowMaxSize: ${SW_STORAGE_ES_QUERY_MAX_WINDOW_SIZE:10000}
    metadataQueryMaxSize: ${SW_STORAGE_ES_QUERY_MAX_SIZE:5000}
    segmentQueryMaxSize: ${SW_STORAGE_ES_QUERY_SEGMENT_SIZE:200}
    profileTaskQueryMaxSize: ${SW_STORAGE_ES_QUERY_PROFILE_TASK_SIZE:200}
    oapAnalyzer: ${SW_STORAGE_ES_OAP_ANALYZER:"{\"analyzer\":{\"oap_analyzer\":{\"type\":\"stop\"}}}"} # the oap analyzer.
    oapLogAnalyzer: ${SW_STORAGE_ES_OAP_LOG_ANALYZER:"{\"analyzer\":{\"oap_log_analyzer\":{\"type\":\"standard\"}}}"} # the oap log analyzer. It could be customized by the ES analyzer configuration to support more language log formats, such as Chinese log, Japanese log and etc.
    advanced: ${SW_STORAGE_ES_ADVANCED:""}

3、启动服务

启动位置在 bin/startup.bat。
在这里插入图片描述
查看Skywalking界面
http://localhost:8080/
在这里插入图片描述

三、Java项目接入Skywalking

1、启动参数配置

在这里插入图片描述

-javaagent:D:\tools\skywalking-8.7.0\agent\skywalking-agent.jar
-DSW_AGENT_NAME=yun-tool-app
-DSW_AGENT_COLLECTOR_BACKEND_SERVICES=localhost:11800

配置完，启动Java项目。

2、查看仪表盘

在这里插入图片描述

3、查看拓扑图

在这里插入图片描述

4、查看追踪面板

在这里插入图片描述

5、分布式日志管理

引入依赖

<dependency>
    <groupId>org.apache.skywalking</groupId>
    <artifactId>apm-toolkit-logback-1.x</artifactId>
    <version>8.7.0</version>
</dependency>

修改logback配置文件

<appender name="CONSOLE" class="ch.qos.logback.core.ConsoleAppender">
    <encoder class="ch.qos.logback.core.encoder.LayoutWrappingEncoder">
        <layout class="org.apache.skywalking.apm.toolkit.log.logback.v1.x.TraceIdPatternLogbackLayout">
            <Pattern>${CONSOLE_LOG_PATTERN}</Pattern>
        </layout>
    </encoder>
</appender>

<appender name="grpc-log" class="org.apache.skywalking.apm.toolkit.log.logback.v1.x.log.GRPCLogClientAppender">
    <encoder class="ch.qos.logback.core.encoder.LayoutWrappingEncoder">
        <layout class="org.apache.skywalking.apm.toolkit.log.logback.v1.x.mdc.TraceIdMDCPatternLogbackLayout">
            <Pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%X{tid}] [%thread] %-5level %logger{36} -%msg%n</Pattern>
        </layout>
    </encoder>
</appender>

6、查看日志面板

调用接口时，控制台输出看到分布式链路id了
在这里插入图片描述
查看日志面板
在这里插入图片描述
点击日志中的分布式链路id，可以看到：
在这里插入图片描述

后续还将使用Skywalking的性能剖析功能和告警功能。

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