分布式链路追踪之Skywalking从入门到CRUD
文章目录
- Skywalking介绍
-
- Skywalking和Spring Cloud Sleuth + ZipKin对比
- Skywalking架构
- SpringCloud引入Skywalking
-
- Skywalking下载
-
- 配置
- 启动
- 客户端整合
- Skywalking数据持久化（es）
- 定义日志配置
- 验收
Skywalking介绍
- Skywalking为国产开源软件，由国内开源爱好者吴晟开源并提交到Apache孵化器的产品；
- SkyWalking增长势头强劲，社区活跃，中文文档齐全，没有语言障碍；
- SkyWalking支持多语言，切引入到项目中非常方便，无代码侵入性；
Skywalking和Spring Cloud Sleuth + ZipKin对比
- SkyWalking采用字节码增强的技术实现代码无侵入，zipKin代码侵入性比较高；
- SkyWalking功能比较丰富，报表统计，UI界面更加人性化；
- 如果是新架构，建议优先选择SkyWalking；
Skywalking架构
官网架构图：
上述架构图中主要分为四个部分，如下：
- 上面的Agent：负责收集日志数据，并且传递给中间的OAP服务器；
- 中间的OAP：负责接收 Agent 发送的 Tracing 和Metric的数据信息，然后进行分析(AnalysisCore) ，存储到外部存储器( Storage )，最终提供查询( Query )功能；
- 左面的UI：负责提供web控制台，查看链路，查看各种指标，性能等等；
- 右面Storage：负责数据的存储，支持多种存储类型；
SpringCloud引入Skywalking
Skywalking下载
下载地址：https://archive.apache.org/dist/skywalking/，下载对应的版本（本篇文章使用8.7.0），目录大致如下：
配置
修改配置文件，这里配合nacos与es一起使用，配置文件为config目录application.yml文件（oap服务的配置文件）；
对接nacos：
cluster:
# 这里修改为 nacos
selector: ${SW_CLUSTER:nacos}
standalone:
zookeeper:
nameSpace: ${SW_NAMESPACE:""}
hostPort: ${SW_CLUSTER_ZK_HOST_PORT:localhost:2181}
# Retry Policy
baseSleepTimeMs: ${SW_CLUSTER_ZK_SLEEP_TIME:1000}
maxRetries: ${SW_CLUSTER_ZK_MAX_RETRIES:3}
# Enable ACL
enableACL: ${SW_ZK_ENABLE_ACL:false}
schema: ${SW_ZK_SCHEMA:digest}
expression: ${SW_ZK_EXPRESSION:skywalking:skywalking}
kubernetes:
namespace: ${SW_CLUSTER_K8S_NAMESPACE:default}
labelSelector: ${SW_CLUSTER_K8S_LABEL:app=collector,release=skywalking}
uidEnvName: ${SW_CLUSTER_K8S_UID:SKYWALKING_COLLECTOR_UID}
consul:
serviceName: ${SW_SERVICE_NAME:"SkyWalking_OAP_Cluster"}
hostPort: ${SW_CLUSTER_CONSUL_HOST_PORT:localhost:8500}
aclToken: ${SW_CLUSTER_CONSUL_ACLTOKEN:""}
etcd:
endpoints: ${SW_CLUSTER_ETCD_ENDPOINTS:localhost:2379}
namespace: ${SW_CLUSTER_ETCD_NAMESPACE:/skywalking}
serviceName: ${SW_SCLUSTER_ETCD_ERVICE_NAME:"SkyWalking_OAP_Cluster"}
authentication: ${SW_CLUSTER_ETCD_AUTHENTICATION:false}
user: ${SW_SCLUSTER_ETCD_USER:}
password: ${SW_SCLUSTER_ETCD_PASSWORD:}
nacos:
# 这里为在nacos中展示的服务名称，在这里默认就好
serviceName: ${SW_SERVICE_NAME:"SkyWalking_OAP_Cluster"}
# 这里填写nacos注册中心地址
hostPort: ${SW_CLUSTER_NACOS_HOST_PORT:127.0.0.1:8848}
# 如果有配置命名空间的话，填写命名空间ID
namespace: ${SW_CLUSTER_NACOS_NAMESPACE:"729f3090-638e-4b45-bfde-b91312ffe3d0"}
# Nacos auth username
username: ${SW_CLUSTER_NACOS_USERNAME:"nacos"}
password: ${SW_CLUSTER_NACOS_PASSWORD:"nacos"}
# Nacos auth accessKey
accessKey: ${SW_CLUSTER_NACOS_ACCESSKEY:""}
secretKey: ${SW_CLUSTER_NACOS_SECRETKEY:""}
启动
其中bin目录下，oapService.bat与webappService.bat分别对应启动服务端与客户端，对应.sh后缀同理，startup.bat为前后端同时启动；
这里执行startup.bat进行启动，下面为启动成功样式：
注意点：
- 启动命令目录下不可以有中文、空格，否则会出现闪退；
- 端口冲突也会造成闪退，修改端口可在
webapp/webapp.yml中进行修改，默认为8080；
这时访问localhost:8080即可访问成功，但因为没有做任何配置，所以只是个空页面：
（这里不管页面展示与否，都不用担心，只要保证startup.bat启动之后没有闪退就可以）
客户端整合
- 客户端整合无需修改代码，只需要在启动时，指定配置即可；
-Dfile.encoding=utf-8
// 指定jar
-javaagent:D:\skywalking-es7-8.7.0\apache-skywalking-apm-bin-es7\agent\skywalking-agent.jar
// 自定义服务名称
-Dskywalking.agent.service_name=blog-article
// 这个端口是默认的，除非自己修改了配置
-Dskywalking.collector.backend_service=127.0.0.1:11800
-Xms400m
-Xmx400m
- idea启动项目时，在VM处配置即可；
- 之后在启动日志中即可查看到配置已生效：
Skywalking数据持久化（es）
- Skywalking数据持久化可以对接H2以及es，这里以es为例，首先搭建es，访问localhost:9200，展示es相关信息，代表搭建完成，搭建es相关步骤就不在这里展开讲解了；
{
"name": "28f784356f66",
"cluster_name": "docker-cluster",
"cluster_uuid": "pD1a-jZYQ1iiHlQ7KezQHA",
"version": {
"number": "7.8.1",
"build_flavor": "oss",
"build_type": "docker",
"build_hash": "b5ca9c58fb664ca8bf9e4057fc229b3396bf3a89",
"build_date": "2020-07-21T16:40:44.668009Z",
"build_snapshot": false,
"lucene_version": "8.5.1",
"minimum_wire_compatibility_version": "6.8.0",
"minimum_index_compatibility_version": "6.0.0-beta1"
},
"tagline": "You Know, for Search"
}
- 因为这里Skywalking使用的是8.7.0版本，所以es最好使用7.0版本以上，本篇使用的es版本为
7.8.1； - 修改
config/application.yml配置文件，storage节点下指定elasticsearch7，elasticsearch7节点下配置es的访问地址； - 注意配置文件中有
elasticsearch以及elasticsearch7节点，不要混淆；
storage:
selector: elasticsearch7
elasticsearch7:
nameSpace: ${SW_NAMESPACE:"docker-cluster"}
# 指定地址
clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:127.0.0.1:9200}
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: ${SW_STORAGE_ES_ADVANCED:""}
- 修改完配置文件，再次启动Skywalking时，会发现控制台已经有了数据，刷新项目之后也会在日志栏中展示日志；
定义日志配置
logback-spring.xml
<configuration scan="true" scanPeriod=" 5 seconds">
<property name="logPath" value="logs"/>
<appender name="console_log" class="ch.qos.logback.core.ConsoleAppender">
<encoder class="ch.qos.logback.core.encoder.LayoutWrappingEncoder">
<layout class="org.apache.skywalking.apm.toolkit.log.logback.v1.x.TraceIdPatternLogbackLayout">
<Pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%tid] [%thread] %-5level %logger{36} -%msg%nPattern>
layout>
encoder>
appender>
<appender name="ASYNC" class="ch.qos.logback.classic.AsyncAppender">
<discardingThreshold>0discardingThreshold>
<queueSize>1024queueSize>
<neverBlock>trueneverBlock>
<appender-ref ref="console_log"/>
appender>
<appender name="grpc-log" class="org.apache.skywalking.apm.toolkit.log.logback.v1.x.log.GRPCLogClientAppender">
<encoder class="ch.qos.logback.core.encoder.LayoutWrappingEncoder">
<layout class="org.apache.skywalking.apm.toolkit.log.logback.v1.x.mdc.TraceIdMDCPatternLogbackLayout">
<Pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%X{tid}] [%thread] %-5level %logger{36} -%msg%nPattern>
layout>
encoder>
appender>
<appender name="fileDEBUGLog"
class="ch.qos.logback.core.rolling.RollingFileAppender">
<filter class="ch.qos.logback.classic.filter.LevelFilter">
<level>Errorlevel>
<onMatch>DENYonMatch>
<onMismatch>ACCEPTonMismatch>
filter>
<File>${logPath}/blog-gateway.logFile>
<rollingPolicy
class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy">
<FileNamePattern>${logPath}/blog-gateway_%d{yyyy-MM-dd}.logFileNamePattern>
<maxHistory>90maxHistory>
<totalSizeCap>1GBtotalSizeCap>
rollingPolicy>
<encoder>
<charset>UTF-8charset>
<pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%X{tid}] [%thread] %-5level %logger{36} -%msg%npattern>
encoder>
appender>
<appender name="fileErrorLog"
class="ch.qos.logback.core.rolling.RollingFileAppender">
<filter class="ch.qos.logback.classic.filter.ThresholdFilter">
<level>Errorlevel>
filter>
<File>${logPath}/blog-gateway_error.logFile>
<rollingPolicy
class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy">
<FileNamePattern>${logPath}/blog-gateway_error_%d{yyyy-MM-dd}.logFileNamePattern>
<maxHistory>90maxHistory>
<totalSizeCap>1GBtotalSizeCap>
rollingPolicy>
<encoder>
<charset>UTF-8charset>
<pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%X{tid}] [%thread] %-5level %logger{36} -%msg%npattern>
encoder>
appender>
<root level="INFO">
<appender-ref ref="ASYNC"/>
<appender-ref ref="grpc-log"/>
<appender-ref ref="fileDEBUGLog"/>
<appender-ref ref="fileErrorLog"/>
root>
configuration>
验收
- 自此，Skywalking安装配置以及数据持久化已经全部完成，重新启动项目时，可以看到控制台监控的项目信息；
- 扑朔图以及链路追踪
- Skywalking还有很多细节方面的知识点，本篇主要围绕搭建方面，后面会单独记录其他知识点；