SkyWalking的简单入门

SkyWalking 入门使用

背景

实际生产中，面对几十个、甚至成百上千个的微服务实例，如果一旦某个实例发生宕机，如果不能快速定位、提交预警，对实际生产造成的损失无疑是巨大的。所以，要对微服务进行监控、预警，对微服务的调用链路进行监控，迅速定位问题

安装Elasticsearch并启动

1. 安装命令（以下命令为Mac命令，Linux下可以使用yum命令，Windows下可以直接在Elasticsearch官网下载对应版本的安装包即可）

brew update
brew search elasticsearch
brew install elasticsearch

2. 启动elasticsearch

brew service start elasticsearch-full

3. 检查是否启动成功

访问localhost:9200，是否有如下类似数据返回

{
  "name" : "******",
  "cluster_name" : "elasticsearch_name",
  "cluster_uuid" : "rp73VaY8RRCgQrl4M5uR9A",
  "version" : {
    "number" : "7.7.1",
    "build_flavor" : "default",
    "build_type" : "tar",
    "build_hash" : "ad56dce891c901a492bb1ee393f12dfff473a423",
    "build_date" : "2020-05-28T16:30:01.040088Z",
    "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"
}

如果没有返回，则去存放日志位置，查看日志里的报错内容，如果不知道日志的存放位置，可以查看elasticsearch.yml中的path.log参数的值，对应的就是日志的存放位置

安装SkyWalking并启动

1. 在SkyWalking官网下载对应的版本，这里下载的是Binary Distribution for ElasticSearch 7版本，因为上面安装的Elasticsearch版本是7

2. 解压并修改配置

   2.1 解压压缩包

   tar -zxvf apache-skywalking-apm-es7-7.0.0.tar.gz
   

   2.2 进入解压后的文件夹，修改/config/application.yml配置

   # Licensed to the Apache Software Foundation (ASF) under one
   # or more contributor license agreements.  See the NOTICE file
   # distributed with this work for additional information
   # regarding copyright ownership.  The ASF licenses this file
   # to you under the Apache License, Version 2.0 (the
   # "License"); you may not use this file except in compliance
   # with the License.  You may obtain a copy of the License at
   #
   #     http://www.apache.org/licenses/LICENSE-2.0
   #
   # Unless required by applicable law or agreed to in writing, software
   # distributed under the License is distributed on an "AS IS" BASIS,
   # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   # See the License for the specific language governing permissions and
   # limitations under the License.
   
   #集群 本地是没有集群，默认单机，把集群的配置删除了
   cluster:
     selector: ${SW_CLUSTER:standalone}
     standalone:
   
   core:
     selector: ${SW_CORE:default}
     default:
       # Mixed: Receive agent data, Level 1 aggregate, Level 2 aggregate
       # Receiver: Receive agent data, Level 1 aggregate
       # Aggregator: Level 2 aggregate
       role: ${SW_CORE_ROLE:Mixed} # Mixed/Receiver/Aggregator
       restHost: ${SW_CORE_REST_HOST:0.0.0.0}
       restPort: ${SW_CORE_REST_PORT:12800}
       restContextPath: ${SW_CORE_REST_CONTEXT_PATH:/}
       gRPCHost: ${SW_CORE_GRPC_HOST:0.0.0.0}
       gRPCPort: ${SW_CORE_GRPC_PORT:11800}
       gRPCSslEnabled: ${SW_CORE_GRPC_SSL_ENABLED:false}
       gRPCSslKeyPath: ${SW_CORE_GRPC_SSL_KEY_PATH:""}
       gRPCSslCertChainPath: ${SW_CORE_GRPC_SSL_CERT_CHAIN_PATH:""}
       gRPCSslTrustedCAPath: ${SW_CORE_GRPC_SSL_TRUSTED_CA_PATH:""}
       downsampling:
         - Hour
         - Day
         - Month
       # Set a timeout on metrics data. After the timeout has expired, the metrics data will automatically be deleted.
       enableDataKeeperExecutor: ${SW_CORE_ENABLE_DATA_KEEPER_EXECUTOR:true} # Turn it off then automatically metrics data delete will be close.
       dataKeeperExecutePeriod: ${SW_CORE_DATA_KEEPER_EXECUTE_PERIOD:5} # How often the data keeper executor runs periodically, unit is minute
       recordDataTTL: ${SW_CORE_RECORD_DATA_TTL:90} # Unit is minute
       minuteMetricsDataTTL: ${SW_CORE_MINUTE_METRIC_DATA_TTL:90} # Unit is minute
       hourMetricsDataTTL: ${SW_CORE_HOUR_METRIC_DATA_TTL:36} # Unit is hour
       dayMetricsDataTTL: ${SW_CORE_DAY_METRIC_DATA_TTL:45} # Unit is day
       monthMetricsDataTTL: ${SW_CORE_MONTH_METRIC_DATA_TTL:18} # Unit is month
       # Cache metric data for 1 minute to reduce database queries, and if the OAP cluster changes within that minute,
       # the metrics may not be accurate within that minute.
       enableDatabaseSession: ${SW_CORE_ENABLE_DATABASE_SESSION:true}
       topNReportPeriod: ${SW_CORE_TOPN_REPORT_PERIOD:10} # top_n record worker report cycle, unit is minute
       # Extra model column are the column defined by in the codes, These columns of model are not required logically in aggregation or further query,
       # and it will cause more load for memory, network of OAP and storage.
       # But, being activated, user could see the name in the storage entities, which make users easier to use 3rd party tool, such as Kibana->ES, to query the data by themselves.
       activeExtraModelColumns: ${SW_CORE_ACTIVE_EXTRA_MODEL_COLUMNS:false}
   
   storage:
     selector: ${SW_STORAGE:elasticsearch7}
     elasticsearch7:
       nameSpace: ${SW_NAMESPACE:"elasticsearch7"}
       clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200}
       protocol: ${SW_STORAGE_ES_HTTP_PROTOCOL:"http"}
       # trustStorePath: ${SW_SW_STORAGE_ES_SSL_JKS_PATH:"../es_keystore.jks"}
       # trustStorePass: ${SW_SW_STORAGE_ES_SSL_JKS_PASS:""}
       enablePackedDownsampling: ${SW_STORAGE_ENABLE_PACKED_DOWNSAMPLING:true} # Hour and Day metrics will be merged into minute index.
       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 managed by 3rd party tool.
       indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:2}
       indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:0}
       # Those data TTL settings will override the same settings in core module.
       recordDataTTL: ${SW_STORAGE_ES_RECORD_DATA_TTL:7} # Unit is day
       otherMetricsDataTTL: ${SW_STORAGE_ES_OTHER_METRIC_DATA_TTL:45} # Unit is day
       monthMetricsDataTTL: ${SW_STORAGE_ES_MONTH_METRIC_DATA_TTL:18} # Unit is month
       # 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:""}
   
   receiver-sharing-server:
     selector: ${SW_RECEIVER_SHARING_SERVER:default}
     default:
       authentication: ${SW_AUTHENTICATION:""}
   receiver-register:
     selector: ${SW_RECEIVER_REGISTER:default}
     default:
   
   receiver-trace:
     selector: ${SW_RECEIVER_TRACE:default}
     default:
       bufferPath: ${SW_RECEIVER_BUFFER_PATH:../trace-buffer/}  # Path to trace buffer files, suggest to use absolute path
       bufferOffsetMaxFileSize: ${SW_RECEIVER_BUFFER_OFFSET_MAX_FILE_SIZE:100} # Unit is MB
       bufferDataMaxFileSize: ${SW_RECEIVER_BUFFER_DATA_MAX_FILE_SIZE:500} # Unit is MB
       bufferFileCleanWhenRestart: ${SW_RECEIVER_BUFFER_FILE_CLEAN_WHEN_RESTART:false}
       sampleRate: ${SW_TRACE_SAMPLE_RATE:10000} # The sample rate precision is 1/10000. 10000 means 100% sample in default.
       slowDBAccessThreshold: ${SW_SLOW_DB_THRESHOLD:default:200,mongodb:100} # The slow database access thresholds. Unit ms.
   
   receiver-jvm:
     selector: ${SW_RECEIVER_JVM:default}
     default:
   
   receiver-clr:
     selector: ${SW_RECEIVER_CLR:default}
     default:
   
   receiver-profile:
     selector: ${SW_RECEIVER_PROFILE:default}
     default:
   
   service-mesh:
     selector: ${SW_SERVICE_MESH:default}
     default:
       bufferPath: ${SW_SERVICE_MESH_BUFFER_PATH:../mesh-buffer/}  # Path to trace buffer files, suggest to use absolute path
       bufferOffsetMaxFileSize: ${SW_SERVICE_MESH_OFFSET_MAX_FILE_SIZE:100} # Unit is MB
       bufferDataMaxFileSize: ${SW_SERVICE_MESH_BUFFER_DATA_MAX_FILE_SIZE:500} # Unit is MB
       bufferFileCleanWhenRestart: ${SW_SERVICE_MESH_BUFFER_FILE_CLEAN_WHEN_RESTART:false}
   
   istio-telemetry:
     selector: ${SW_ISTIO_TELEMETRY:default}
     default:
   
   envoy-metric:
     selector: ${SW_ENVOY_METRIC:default}
     default:
       alsHTTPAnalysis: ${SW_ENVOY_METRIC_ALS_HTTP_ANALYSIS:""}
   
   receiver_zipkin:
     selector: ${SW_RECEIVER_ZIPKIN:-}
     default:
       host: ${SW_RECEIVER_ZIPKIN_HOST:0.0.0.0}
       port: ${SW_RECEIVER_ZIPKIN_PORT:9411}
       contextPath: ${SW_RECEIVER_ZIPKIN_CONTEXT_PATH:/}
   
   receiver_jaeger:
     selector: ${SW_RECEIVER_JAEGER:-}
     default:
       gRPCHost: ${SW_RECEIVER_JAEGER_HOST:0.0.0.0}
       gRPCPort: ${SW_RECEIVER_JAEGER_PORT:14250}
   
   query:
     selector: ${SW_QUERY:graphql}
     graphql:
       path: ${SW_QUERY_GRAPHQL_PATH:/graphql}
   
   alarm:
     selector: ${SW_ALARM:default}
     default:
   
   telemetry:
     selector: ${SW_TELEMETRY:none}
     none:
     prometheus:
       host: ${SW_TELEMETRY_PROMETHEUS_HOST:0.0.0.0}
       port: ${SW_TELEMETRY_PROMETHEUS_PORT:1234}
     so11y:
       prometheusExporterEnabled: ${SW_TELEMETRY_SO11Y_PROMETHEUS_ENABLED:true}
       prometheusExporterHost: ${SW_TELEMETRY_PROMETHEUS_HOST:0.0.0.0}
       prometheusExporterPort: ${SW_TELEMETRY_PROMETHEUS_PORT:1234}
   
   receiver-so11y:
     selector: ${SW_RECEIVER_SO11Y:-}
     default:
   # 配置中心，这里没有，把多余的配置删掉了
   configuration:
     selector: ${SW_CONFIGURATION:none}
     none:
    
   exporter:
     selector: ${SW_EXPORTER:-}
     grpc:
       targetHost: ${SW_EXPORTER_GRPC_HOST:127.0.0.1}
       targetPort: ${SW_EXPORTER_GRPC_PORT:9870}
   
   

   配置说明：

   cluster: 有几种注册中心可以选择，默认standalone-单机

   core: 默认配置

   storage: 用来存储trace的数据存储，以便查询、展示，提供了H2、Mysql、ES、InfluxDB这几种存储方式，recordDataTTL是存储数据多长时间，默认是7天

   这里选择es7，把其他几种存储方式注释掉。然后在storage的selector选项中选择elasticsearch7
   其他多余的配置都被删掉了，如果想要配置集群、配置中心、或者存储选择H2、MySQL等，参考官方配置再加上即可

3. 启动OAP、以及SkyWalkingUI

   cd bin
   # 启动OAP
   oapService.sh
   # 启动SkyWalking UI
   webappService.sh
   

   访问localhost:8080，**如果8080端口被占用了怎么办?**进入webapp文件夹下的webaap.yml，修改port即可。启动之后，如图所示
   

   记得把自动按钮点开、以及下面的开始筛选时间配置好，Skywalking就会每隔6秒刷新一次采集到的数据

配置SpringCloud微服务的Agent

1. 以Eureka注册中心为例，演示如何配置agent。

   1.1 在idea中的Run/Debug Configurations的VM options中加入如下配置

# -javaagent后面是skywalking-agent.jar的路径
-javaagent:/Users/jacksparrow414/skywalking/apache-skywalking-apm-bin-es7/agent/skywalking-agent.jar

​ 1.2 在Environment viriables中添加两行配置

SW_AGENT_NAME=eureka;SW_AGENT_COLLECTOR_BACKEND_SERVICES=127.0.0.1:11800

SW_AGENT_NAME 对应的是服务的名字，可以任意取，同一个服务的不同实例，名字是一样的

​ 1.3 类似的配置，分别配置gateway(网关)、one-service(服务1，对应两个实例DemoClientone、DemoClientthree)、two-service(服务2)。服务1、服务2均连接本地3306数据库。一共5个应用，依次启动：

注册中心->网关->服务1(两个实例)->服务2

再启动nginx

为什么启动nginx呢？

实际访问链路为：
web浏览器/App/H5小程序->发起请求->nginx反向代理->将请求转发至网关->网关根据接口路径->路由至不同的微服务实例

​ 1.4 判断agent是否生效，在每个应用启动的时候，控制台会首先打印

​ 1.5 稍等一会，在Skywalking UI会发现

可以看到，有4个应用，1个数据库，是对的

查看SpringCloud的链路调用

单个微服务调用监控

1. 请求one-service的一个实例DemoClientone的接口addSwUser接口，插入一条数据。

稍等一会可以在控制台查看到如下信息

​ 1.1 仪表盘-选择one-service，展示如下

​ 1.2 拓扑图-选择one-service,展示如下

​ 1.3 追踪-选择one-service,展示如下

​ 1.4 在上图的Mysql/JDBC/PrepareStatement/execute中点击看到信息如下如果想要看到执行SQL的参数怎么办呢？

在agent.config配置,设置下面的参数为true即可

plugin.mysql.trace_sql_parameters=${SW_MYSQL_TRACE_SQL_PARAMETERS:true}

配置之后，重启。再次请求接口，查看调用链路中的SQL调用如下

微服务之间调用链路监控

1. 微服务之间调用，外部接口请求two-service，DemoClienttwo负载均衡请求one-service下的两个实例(DemoClientone、DemoClientthree)。

稍等一会，可以在控制台看到如下信息

​ .1 仪表盘-选择two-service，展示如下

​ 1.2 拓扑图-选择two-service,展示如下

​ 1.3 追踪-选择two-serivce,展示如下

可以看到，整个的调用链路为gateway(网关)->two-service->one-service

​ 1.4 在上图的Mysql/JDBC/PrepareStatement/execute中点击看到信息如下

全部微服务调用链路

全部微服务调用链路拓扑图如下

停止SkyWalking

由于官方没有提供关闭的脚本，详情见issue4698,只能手动去kill了

1. 关闭Agent

# 我们配置的是11800，查找占用端口11800的进程
lsof -i:11800
# 使用pkill 直接杀掉父进程
pkill -9 34956

2. 关闭SkyWlking UI的服务端口

# 默认是8080端口
kill -9 8080

停止Elasticsearch

brew service stop elasticsearch-full

总结

1. 快速使用SkyWalking完成对SpringCloud类的微服务架构进行简单的检测
2. 告警功能的使用？
3. 以上调用只是微服务的调用，而且还很单一。对于微服务集群，如：注册中心集群、网关集群、以及业务集群(一个实际业务服务，多个实例节点)。在集群的情况下，如何对集群中的服务进行平滑的适配SkyWalking，并被检测到？
4. 对于集群的配置，如何结合配置中心来使配置简单、易用？
5. 由于网关集群的前面可能是Nginx集群，如何把Nginx集群也纳入到SkyWalking的管理范围内？