SkyWalking Linux服务端集群部署

文件状态：

[ ] 草稿

[√] 正在修改

当前版本

1.0

历史修订版本

1.0;

作    者

杜有龙

完成日期

2019-02-19

一、版本要求

  • SkyWalking5.0.0-GA
  • ElasticSearch-5.x

注意6.X版本不支持；新版本的skywalking使用ES作为存储，所以先安装es。

  • JDK8+ (SkyWalking collector和WebUI部署在jdk8及以上版本)
  • JDK6+(被监控的应用程序运行在jdk6及以上版本)
  • 其他

二、地址

  • apache官网下载地址

http://skywalking.apache.org/downloads/

  • gitlib部署文档

https://github.com/apache/incubator-skywalking/blob/v5.0.0-alpha/docs/README_ZH.md

  • 项目地址

https://github.com/OpenSkywalking/skywalking-netcore

三、部署过程

【参考】

https://github.com/apache/incubator-skywalking/blob/5.x/docs/cn/Deploy-backend-in-cluster-mode-CN.md

1、Elasticsearch

参考文档：2、2-SkyWalking部署文档-Linux.docx

2、SW-collector

2.1 端口要求

确保端口10800,11800,12800不被占用

2.2 存储要求

collector配置ElasticSearch作为运行存储介质

2.3 时间设置要求

被监控应用的宿主服务器系统时间(包含时区)与collectors,UIs部署的宿主服务器时间设置正确且相同

2.4 配置

2.4.1位置

..\config\application.yml

2.4.2配置项解释

【官方解释】

下面是关于collector连接配置的5种类型方式

<1>、naming :agent使用HTTP协议连接collectors

<2>、agent_gRPC :agent使用gRPC协议连接collectors

<3>、remote :Collector使用gRPC协议连接collector

<4>、ui :使用HTTP协议连接collector,(大多数情况不需要修改)

<5>、agent_jetty:agent使用HTTP协议连接collectors(可选连接)

2.4.3配置内容-参考1

参考文档：2、2-SkyWalking部署文档-Linux.docx

2.4.4配置内容-参考2-节点1

##########节点1：ip=192.168.0.3
#cluster:
zookeeper:
hostPort: 192.168.0.101:2181, 192.168.0.102:2181，192.168.103.10
# zookeeper集群的主机IP地址及端口，使用逗号分隔
    sessionTimeout: 100000
naming:
  jetty:
    #OS real network IP(binding required), for agent to find collector cluster
host: 192.168.0.3
# 部署collector的主机IP地址，即当前节点的ip地址
    port: 10800
    contextPath: /
cache:
#  guava:
  caffeine:
remote:
  gRPC:
    # OS real network IP(binding required), for collector nodes communicate with each other in cluster. collectorN --(gRPC) --> collectorM
host: 192.168.0.3
# 部署collector的主机IP地址，即当前节点的ip地址
    port: 11800
agent_gRPC:
  gRPC:
    #OS real network IP(binding required), for agent to uplink data(trace/metrics) to collector. agent--(gRPC)--> collector
host: 192.168.0.3
# 部署collector的主机IP地址，即当前节点的ip地址 
    port: 11800
    # Set these two setting to open ssl
    #sslCertChainFile: $path
    #sslPrivateKeyFile: $path
 
    # Set your own token to active auth
    #authentication: xxxxxx
agent_jetty:
  jetty:
    # OS real network IP(binding required), for agent to uplink data(trace/metrics) to collector through HTTP. agent--(HTTP)--> collector
    # SkyWalking native Java/.Net/node.js agents don't use this.
    # Open this for other implementor.
host: 192.168.0.3
# 部署collector的主机IP地址，即当前节点的ip地址
    port: 12800
    contextPath: /
analysis_register:
  default:
analysis_jvm:
  default:
analysis_segment_parser:
  default:
    bufferFilePath: ../buffer/
    bufferOffsetMaxFileSize: 10M
    bufferSegmentMaxFileSize: 500M
    bufferFileCleanWhenRestart: true
ui:
  jetty:
    # Stay in `localhost` if UI starts up in default mode.
    # Change it to OS real network IP(binding required), if deploy collector in different machine.
host: 192.168.0.3
# 部署collector的主机IP地址，即当前节点的ip地址
    port: 12800
    contextPath: /
storage:
  elasticsearch:
clusterName: eqx-jz-test
# Elasticsearch的cluster.name值
    clusterTransportSniffer: true
clusterNodes: 192.168.0.17:9303
# Elasticsearch的ip和端口
    indexShardsNumber: 2
    indexReplicasNumber: 0
    highPerformanceMode: true
    # Batch process setting, refer to https://www.elastic.co/guide/en/elasticsearch/client/java-api/5.5/java-docs-bulk-processor.html
    bulkActions: 2000 # Execute the bulk every 2000 requests
    bulkSize: 20 # flush the bulk every 20mb
    flushInterval: 10 # flush the bulk every 10 seconds whatever the number of requests
    concurrentRequests: 2 # the number of concurrent requests
    # Set a timeout on metric data. After the timeout has expired, the metric data will automatically be deleted.
    traceDataTTL: 90 # Unit is minute
    minuteMetricDataTTL: 90 # Unit is minute
    hourMetricDataTTL: 36 # Unit is hour
    dayMetricDataTTL: 45 # Unit is day
    monthMetricDataTTL: 18 # Unit is month
#storage:
#  h2:
#    url: jdbc:h2:~/memorydb
#    userName: sa
configuration:
  default:
    #namespace: xxxxx
    # alarm threshold
    applicationApdexThreshold: 2000
    serviceErrorRateThreshold: 10.00
    serviceAverageResponseTimeThreshold: 2000
    instanceErrorRateThreshold: 10.00
    instanceAverageResponseTimeThreshold: 2000
    applicationErrorRateThreshold: 10.00
    applicationAverageResponseTimeThreshold: 2000
    # thermodynamic
    thermodynamicResponseTimeStep: 50
    thermodynamicCountOfResponseTimeSteps: 40
    # max collection's size of worker cache collection, setting it smaller when collector OutOfMemory crashed.
    workerCacheMaxSize: 10000
#receiver_zipkin:
#  default:
#    host: localhost
#    port: 9411
#    contextPath: /

 

2.4.4配置内容-参考2-节点2

##########节点1：ip=192.168.0.4
#cluster:
zookeeper:
hostPort: 192.168.0.101:2181, 192.168.0.102:2181，192.168.103.10
# zookeeper集群的主机IP地址及端口，使用逗号分隔
    sessionTimeout: 100000
naming:
  jetty:
    #OS real network IP(binding required), for agent to find collector cluster
host: 192.168.0.4
# 部署collector的主机IP地址，即当前节点的ip地址
    port: 10800
    contextPath: /
cache:
#  guava:
  caffeine:
remote:
  gRPC:
    # OS real network IP(binding required), for collector nodes communicate with each other in cluster. collectorN --(gRPC) --> collectorM
host: 192.168.0.4
# 部署collector的主机IP地址，即当前节点的ip地址
    port: 11800
agent_gRPC:
  gRPC:
    #OS real network IP(binding required), for agent to uplink data(trace/metrics) to collector. agent--(gRPC)--> collector
host: 192.168.0.4
# 部署collector的主机IP地址，即当前节点的ip地址 
    port: 11800
    # Set these two setting to open ssl
    #sslCertChainFile: $path
    #sslPrivateKeyFile: $path
 
    # Set your own token to active auth
    #authentication: xxxxxx
agent_jetty:
  jetty:
    # OS real network IP(binding required), for agent to uplink data(trace/metrics) to collector through HTTP. agent--(HTTP)--> collector
    # SkyWalking native Java/.Net/node.js agents don't use this.
    # Open this for other implementor.
host: 192.168.0.4
# 部署collector的主机IP地址，即当前节点的ip地址
    port: 12800
    contextPath: /
analysis_register:
  default:
analysis_jvm:
  default:
analysis_segment_parser:
  default:
    bufferFilePath: ../buffer/
    bufferOffsetMaxFileSize: 10M
    bufferSegmentMaxFileSize: 500M
    bufferFileCleanWhenRestart: true
ui:
  jetty:
    # Stay in `localhost` if UI starts up in default mode.
    # Change it to OS real network IP(binding required), if deploy collector in different machine.
host: 192.168.0.4
# 部署collector的主机IP地址，即当前节点的ip地址
    port: 12800
    contextPath: /
storage:
  elasticsearch:
clusterName: eqx-jz-test
# Elasticsearch的cluster.name值
    clusterTransportSniffer: true
clusterNodes: 192.168.0.17:9303
# Elasticsearch的ip和端口
    indexShardsNumber: 2
    indexReplicasNumber: 0
    highPerformanceMode: true
    # Batch process setting, refer to https://www.elastic.co/guide/en/elasticsearch/client/java-api/5.5/java-docs-bulk-processor.html
    bulkActions: 2000 # Execute the bulk every 2000 requests
    bulkSize: 20 # flush the bulk every 20mb
    flushInterval: 10 # flush the bulk every 10 seconds whatever the number of requests
    concurrentRequests: 2 # the number of concurrent requests
    # Set a timeout on metric data. After the timeout has expired, the metric data will automatically be deleted.
    traceDataTTL: 90 # Unit is minute
    minuteMetricDataTTL: 90 # Unit is minute
    hourMetricDataTTL: 36 # Unit is hour
    dayMetricDataTTL: 45 # Unit is day
    monthMetricDataTTL: 18 # Unit is month
#storage:
#  h2:
#    url: jdbc:h2:~/memorydb
#    userName: sa
configuration:
  default:
    #namespace: xxxxx
    # alarm threshold
    applicationApdexThreshold: 2000
    serviceErrorRateThreshold: 10.00
    serviceAverageResponseTimeThreshold: 2000
    instanceErrorRateThreshold: 10.00
    instanceAverageResponseTimeThreshold: 2000
    applicationErrorRateThreshold: 10.00
    applicationAverageResponseTimeThreshold: 2000
    # thermodynamic
    thermodynamicResponseTimeStep: 50
    thermodynamicCountOfResponseTimeSteps: 40
    # max collection's size of worker cache collection, setting it smaller when collector OutOfMemory crashed.
    workerCacheMaxSize: 10000
#receiver_zipkin:
#  default:
#    host: localhost
#    port: 9411
#    contextPath: /

2.5 启动

参考文档：2、2-SkyWalking部署文档-Linux.docx

【注】请分别启动各个节点的collectorService.sh脚本，然后再分别启动步骤3.2.3中的脚本webappService.sh

2.6 验证

参考文档：2、2-SkyWalking部署文档-Linux.docx

3、SW-Web UI

3.1 位置

Web UI的配置项保存在**\webapp\webapp.yml中

3.2 配置

其他配置参考文档：2、2-SkyWalking部署文档-Linux.docx

3.2.1、节点1

server:
  port: 8091
collector:
  path: /graphql
  ribbon:
    ReadTimeout: 10000
    listOfServers: 192.168.0.3:10800,192.168.0.4:10800
security:
  user:
    admin:
      password: admin

3.2.2、节点2

server:
  port: 8091
collector:
  path: /graphql
  ribbon:
    ReadTimeout: 10000
    listOfServers: 192.168.0.3:10800,192.168.0.4:10800
security:
  user:
    admin:
      password: admin

3.2.3 启动

分别启动集群每个节点脚本 bin/webappService.sh，

3.2.4 验证

参考文档：2、2-SkyWalking部署文档-Linux.docx

4、SW-Agent

参考文档：2、4-SkyWalking部署文档-Docker-Agent客户端集群.docx

  • 启动顺序

1、ElasticSearch

启动elasticsearch.sh

2、SkyWalking

【注】集群环境，首先在各个节点分别启动脚本collectorService.sh，然后在各个节点分别启动脚本webappService.sh

3、启动被监控的程序

参考文档：2、2-SkyWalking部署文档-Linux.docx

六、参考资源

1、collector集群配置文件

skywalking 集群管理器 kubernetes skywalking集群部署_运维

skywalking 集群管理器 kubernetes skywalking集群部署_skywalking_02

 

 

2、collector集群和web ui关系

问题：

skywalking 集群管理器 kubernetes skywalking集群部署_监控类_03

 

答案：

skywalking 集群管理器 kubernetes skywalking集群部署_经验分享_04

skywalking 集群管理器 kubernetes skywalking集群部署_经验分享_05