Skywalking

一、SkyWalking是什么

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；
SkyWalking是观察性分析平台和应用性能管理系统。提供分布式追踪、服务网格遥测分析、度量聚合和可视化一体化解决方案；

二、Skywalking架构

整个架构，分成上、下、左、右四部分：

• 上部分 Agent ：负责从应用中，收集链路信息，发送给 SkyWalking OAP 服务器。目前支持 SkyWalking、Zikpin、Jaeger 等提供的 Tracing 数据信息。而我们目前采用的是，SkyWalking Agent 收集 SkyWalking Tracing 数据，传递给服务器。

• 下部分 SkyWalking OAP ：负责接收 Agent 发送的 Tracing 数据信息，然后进行分析(Analysis Core) ，存储到外部存储器( Storage )，最终提供查询( Query )功能。

• 右部分 Storage ：Tracing 数据存储。目前支持 ES、MySQL、Sharding Sphere、TiDB、H2 多种存储器。而我们目前采用的是 ES ，主要考虑是 SkyWalking 开发团队自己的生产环境采用 ES 为主。

• 左部分 SkyWalking UI ：负责提供控台，查看链路等等

三、Skywalking部署

3.1、Skywalking单机环境

image.png

3.2、ElasticSearch搭建

1.上传下载的压缩包到服务器并解压

tar -zxvf elasticsearch-7.4.2-linux-x86_64.tar.gz //解压压缩包
cd elasticsearch-7.4.2 //进入目录
mkdir data //创建data文件夹，保存数据

2.修改Elasticsearch配置：config/elasticsearch.yml

cluster.name: apm-application
node.name: node-1
path.data: /opt/elasticsearch-7.4.2/data
path.logs: /opt/elasticsearch-7.4.2/logs
# ES监听的ip地址
network.host: 0.0.0.0
cluster.initial_master_nodes: ["node-1"]

# 需要开启跨域才能给elasticsearch-head，kibana等连接
http.cors.enabled: true
http.cors.allow-origin: "*"
http.cors.allow-headers: Authorization,X-Requested-With,Content-Length,Content-Type

3.创建Elasticsearch启动用户

groupadd elsearch
useradd elsearch -g elsearch 
chown -R elsearch:elsearch elasticsearch-7.4.2

4.修改系统参数，启动elasticsearch

# vi /etc/sysctl.conf
 vm.max_map_count=262144
# sysctl -p

cd elasticsearch-7.4.2
su elsearch
./bin/elasticsearch -d

5.前端访问 IP:9200 查看是否启动

3.3、下载 SkyWalking 软件包

1.下载SkyWalking官方包

我们选择apache-skywalking-apm-es7-8.0.0.tar.gz版本想使用 Elasticsearch 7.X 版本作为存储

2.上传下载的压缩包到linux服务器，解压文件

tar -zxvf apache-skywalking-apm-es7-8.0.0.tar.gz
cd apache-skywalking-apm-bin-es7/

3.4、SkyWalking OAP 搭建

1.修改 OAP 配置文件 config/application.yml

storage:
 selector: ${SW_STORAGE:elasticsearch7}
 elasticsearch:
 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:""}
 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 manag
ed 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} # The index shards number is for store metrics data rather than basic segment record
 superDatasetIndexShardsFactor: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_SHARDS_FACTOR:5} # Super data set has been defined in the codes, such as trace segments. Th
is factor provides more shards for the super data set, shards number = indexShardsNumber * superDatasetIndexShardsFactor. Also, this factor effects Zipkin and Jae
ger traces.
 indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:0}
 # Batch process setting, refer to https://www.elastic.co/guide/en/elasticsearch/client/java-api/5.5/java-docs-bulk-processor.html
 bulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:1000} # Execute the bulk every 1000 requests
 flushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:10} # flush the bulk every 10 seconds whatever the number of requests
 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}
 advanced: ${SW_STORAGE_ES_ADVANCED:""}
 elasticsearch7:
 nameSpace: ${SW_NAMESPACE:""}
 clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:192.168.20.200:9200}
 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.
 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 manag
ed by 3rd party tool.
 indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:1} # The index shards number is for store metrics data rather than basic segment record
 superDatasetIndexShardsFactor: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_SHARDS_FACTOR:5} # Super data set has been defined in the codes, such as trace segments. Th
is factor provides more shards for the super data set, shards number = indexShardsNumber * superDatasetIndexShardsFactor. Also, this factor effects Zipkin and Jae
ger traces.
 indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:0}
 # Batch process setting, refer to https://www.elastic.co/guide/en/elasticsearch/client/java-api/5.5/java-docs-bulk-processor.html
 bulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:1000} # Execute the bulk every 1000 requests
 flushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:10} # flush the bulk every 10 seconds whatever the number of requests
 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}
 advanced: ${SW_STORAGE_ES_ADVANCED:""}

2.启动OAP

$ bin/oapService.sh
SkyWalking OAP started successfully!

3.4 SkyWalking UI 搭建

1.由于SkyWalking UI的默认地址是8080，与很多中间件有冲突，可以修改一下

#修改webapp/webapp.yml
server:
 port: 18080

2.启动 SkyWalking UI 服务

$ bin/webappService.sh
SkyWalking Web Application started successfully!

3.5 SkyWalking Agent

1.修改探针默认配置 agent/config/agent.config

collector.backend_service=${SW_AGENT_COLLECTOR_BACKEND_SERVICES:192.168.20.200:11800}
agent.sample_n_per_3_secs=${SW_AGENT_SAMPLE:1}

采样率修改

agent.sample_n_per_3_secs配置说明：

 在访问量较少时，链路全量收集不会对系统带来太大负担，能够完整的观测到系统的运行状况。但是在访问量较大时，全量的链路收集，对链路收集的客户端（agent探针）、服务端（SkyWalking OAP）、存储器（例如说 Elastcsearch）都会带来较大的性能开销，甚至会影响应用的正常运行。在访问量级较大的情况下，往往会选择抽样采样，只收集部分链路信息。SkyWalking Agent 在 agent/config/agent.config 配置文件中，定义了 agent.sample_n_per_3_secs 配置项，设置每 3 秒可收集的链路数据的数量。

2.放置探针

• 我们需要将 agent 目录，拷贝到 Java 应用所在的服务器上。这样，Java 应用才可以配置使用该 SkyWalking Agent。通过设置启动参数的方式检测系统，没有代码侵入。

#在服务的启动命令中添加参数javaagent、Dskywalking.agent.service_name
nohup java -javaagent:agent/skywalking-agent.jar -Dskywalking.agent.service_name=a  -jar a.jar > a.log  

• Idea 配置，如果我们是本地启动的项目，开发工具使用的IDEA，我们只需要在如下图所示地方配置启动附加信息即可

    # javaagent配置的是agent对应的jar位置。
    # Dskywalking.agent.service_name配置建议使用服务的spring.application.name方便区分。
    -javaagent:D:\Develop\apache-skywalking-apm-bin-es7\agent\skywalking-agent.jar
    -Dskywalking.agent.service_name=leimingtech-admin-api