使用docker-compose 一键部署你的分布式调用链跟踪框架skywalking
一旦你的程序docker化之后，你会遇到各种问题，比如原来采用的本地记日志的方式就不再方便了，虽然你可以挂载到宿主机，但你使用 –scale 的话，会导致
记录日志异常，所以最好的方式还是要搭elk日志中心，另一个问题，原来一个请求在一个进程中的痉挛失败，你可以在日志中巡查出调用堆栈，但是docker化之后，
原来一个进程的东西会拆成几个微服务，这时候最好就要有一个分布式的调用链跟踪，类似于wcf中的svctraceview工具。
一：搭建skywalking
gihub地址是： https://github.com/apache/incubator-skywalking ，从文档中大概看的出来，大体分三个部分：存储，收集器，探针，存储这里就选用推荐的
elasticsearch。收集器准备和es部署在一起，探针就有各自语言的实现了，总之这里就有三个docker container： es，kibana，skywalking， 如果不用容器编排工
具的话就比较麻烦。
1. elasticsearch.yml
es的配置文件，不过这里有一个坑，就是一定要将 network.publish_host： 0.0.0.0 ，否则skywalking会连不上 9300端口。
network.publish_host: 0.0.0.0 transport.tcp.port: 9300 network.host: 0.0.0.0
2. elasticsearch.dockerfile
在up的时候，将这个es文件copy到 容器的config文件夹下。
FROM elasticsearch:5.6.4 EXPOSE 9200 9300 COPY elasticsearch.yml /usr/share/elasticsearch/config/
3. application.yml
skywalking的配置文件，这里也有一个坑：连接es的地址中，配置的 clustername一定要修改成和es的clustername保持一致，否则会连不上，这里容器之间用link
进行互联，所以es的ip改成elasticsearch就可以了，其他的ip改成0.0.0.0 。
# 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. #cluster: # zookeeper: # hostPort: localhost:2181 # sessionTimeout: 100000 naming: jetty: host: 0.0.0.0 port: 10800 contextPath: / cache: # guava: caffeine: remote: gRPC: host: 0.0.0.0 port: 11800 agent_gRPC: gRPC: host: 0.0.0.0 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: host: 0.0.0.0 port: 12800 contextPath: / analysis_register: default: analysis_jvm: default: analysis_segment_parser: default: bufferFilePath: ../buffer/ bufferOffsetMaxFileSize: 10M bufferSegmentMaxFileSize: 500M bufferFileCleanWhenRestart: true ui: jetty: host: 0.0.0.0 port: 12800 contextPath: / storage: elasticsearch: clusterName: elasticsearch clusterTransportSniffer: true clusterNodes: elasticsearch:9300 indexShardsNumber: 2 indexReplicasNumber: 0 highPerformanceMode: true ttl: 7 #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
4. skywalking.dockerfile
接下来就是 skywalking的 下载安装，使用dockerfile流程化。
FROM centos:7 LABEL username="hxc@qq.com" WORKDIR /app RUN yum install -y wget && \ yum install -y java-1.8.0-openjdk ADD http://mirrors.hust.edu.cn/apache/incubator/skywalking/5.0.0-RC2/apache-skywalking-apm-incubating-5.0.0-RC2.tar.gz /app RUN tar -xf apache-skywalking-apm-incubating-5.0.0-RC2.tar.gz && \ mv apache-skywalking-apm-incubating skywalking RUN ls /app #copy文件 COPY application.yml /app/skywalking/config/application.yml WORKDIR /app/skywalking/bin USER root RUN echo "tail -f /dev/null" >> /app/skywalking/bin/startup.sh CMD ["/bin/sh","-c","/app/skywalking/bin/startup.sh" ]
5. docker-compose.yml
最后就是将这三个容器进行编排，要注意的是，因为收集器会将数据放入到es中，所有一定要将es的data挂载到宿主机的大硬盘下，否则你的空间会不足的。
version: '3.1' services: #elastic 镜像 elasticsearch: build: context: . dockerfile: elasticsearch.dockerfile # ports: # - "9200:9200" # - "9300:9300" volumes: - "/data/es2:/usr/share/elasticsearch/data" #kibana 可视化查询，暴露 5601 kibana: image: kibana links: - elasticsearch ports: - 5601:5601 depends_on: - "elasticsearch" #skywalking skywalking: build: context: . dockerfile: skywalking.dockerfile ports: - "10800:10800" - "11800:11800" - "12800:12800" - "8080:8080" links: - elasticsearch depends_on: - "elasticsearch"
大概就是这样的一个目录：
二：一键部署
要部署在docker中，你还得需要安装docker-ce 和 docker-compose，大家可以参照官方安装一下。
1. Docker-ce 的安装
sudo yum remove docker \ docker-client \ docker-client-latest \ docker-common \ docker-latest \ docker-latest-logrotate \ docker-logrotate \ docker-selinux \ docker-engine-selinux \ docker-engine sudo yum install -y yum-utils \ device-mapper-persistent-data \ lvm2 sudo yum-config-manager \ --add-repo \ https://download.docker.com/linux/centos/docker-ce.repo sudo yum install docker-ce
然后启动一下docker 服务，可以看到版本是18.06.1
[root@localhost ~]# service docker start Redirecting to /bin/systemctl start docker.service [root@localhost ~]# docker -v Docker version 18.06.1-ce, build e68fc7a
2. docker-compose的安装
sudo curl -L "https://github.com/docker/compose/releases/download/1.22.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose sudo chmod +x /usr/local/bin/docker-compose
3. 最后在centos上执行 docker-compopse up –build 就可以了，如果不想terminal上运行，可以加 -d 使用后台执行。
[root@localhost docker]# docker-compose up --build Building elasticsearch Step 1/3 : FROM elasticsearch:5.6.4 ---> 7a047c21aa48 Step 2/3 : EXPOSE 9200 9300 ---> Using cache ---> 8d66bb57b09d Step 3/3 : COPY elasticsearch.yml /usr/share/elasticsearch/config/ ---> Using cache ---> 02b516c03b95 Successfully built 02b516c03b95 Successfully tagged docker_elasticsearch:latest Building skywalking Step 1/12 : FROM centos:7 ---> 5182e96772bf Step 2/12 : LABEL username="hxc@qq.com" ---> Using cache ---> b95b96a92042 Step 3/12 : WORKDIR /app ---> Using cache ---> afdf4efe3426 Step 4/12 : RUN yum install -y wget && yum install -y java-1.8.0-openjdk ---> Using cache ---> 46be0ca0f7b5 Step 5/12 : ADD http://mirrors.hust.edu.cn/apache/incubator/skywalking/5.0.0-RC2/apache-skywalking-apm-incubating-5.0.0-RC2.tar.gz /app ---> Using cache ---> d5c30bcfd5ea Step 6/12 : RUN tar -xf apache-skywalking-apm-incubating-5.0.0-RC2.tar.gz && mv apache-skywalking-apm-incubating skywalking ---> Using cache ---> 1438d08d18fa Step 7/12 : RUN ls /app ---> Using cache ---> b594124672ea Step 8/12 : COPY application.yml /app/skywalking/config/application.yml ---> Using cache ---> 10eaf0805a65 Step 9/12 : WORKDIR /app/skywalking/bin ---> Using cache ---> bc0f02291536 Step 10/12 : USER root ---> Using cache ---> 4498afca5fe6 Step 11/12 : RUN echo "tail -f /dev/null" >> /app/skywalking/bin/startup.sh ---> Using cache ---> 1c4be7c6b32a Step 12/12 : CMD ["/bin/sh","-c","/app/skywalking/bin/startup.sh" ] ---> Using cache ---> ecfc97e4c97d Successfully built ecfc97e4c97d Successfully tagged docker_skywalking:latest Recreating docker_elasticsearch_1 ... WARNING: Service "elasticsearch" is using volume "/usr/share/elasticsearch/data" from the previous container. Host mapping "/data/es2" has no effect. Remove the existing containers (with `docker-compose rm elasticsea Recreating docker_elasticsearch_1 ... done Recreating docker_skywalking_1 ... done Recreating docker_kibana_1 ... done Attaching to docker_elasticsearch_1, docker_kibana_1, docker_skywalking_1 elasticsearch_1 | [2018-09-17T23:30:29,689][INFO ][o.e.n.Node ] [] initializing ... skywalking_1 | SkyWalking Collector started successfully! elasticsearch_1 | [2018-09-17T23:30:29,830][INFO ][o.e.e.NodeEnvironment ] [C3Z3xlS] using [1] data paths, mounts [[/usr/share/elasticsearch/data (/dev/sda3)]], net usable_space [5.1gb], net total_space [22.1gb], spins? [possibly], types [xfs] elasticsearch_1 | [2018-09-17T23:30:29,831][INFO ][o.e.e.NodeEnvironment ] [C3Z3xlS] heap size [1.9gb], compressed ordinary object pointers [true] elasticsearch_1 | [2018-09-17T23:30:30,071][INFO ][o.e.n.Node ] node name [C3Z3xlS] derived from node ID [C3Z3xlScTmq1MbtJsGKZ0Q]; set [node.name] to override elasticsearch_1 | [2018-09-17T23:30:30,071][INFO ][o.e.n.Node ] version[5.6.4], pid[1], build[8bbedf5/2017-10-31T18:55:38.105Z], OS[Linux/3.10.0-327.el7.x86_64/amd64], JVM[Oracle Corporation/OpenJDK 64-Bit Server VM/1.8.0_151/25.151-b12] elasticsearch_1 | [2018-09-17T23:30:30,071][INFO ][o.e.n.Node ] JVM arguments [-Xms2g, -Xmx2g, -XX:+UseConcMarkSweepGC, -XX:CMSInitiatingOccupancyFraction=75, -XX:+UseCMSInitiatingOccupancyOnly, -XX:+AlwaysPreTouch, -Xss1m, -Djava.awt.headless=true, -Dfile.encoding=UTF-8, -Djna.nosys=true, -Djdk.io.permissionsUseCanonicalPath=true, -Dio.netty.noUnsafe=true, -Dio.netty.noKeySetOptimization=true, -Dio.netty.recycler.maxCapacityPerThread=0, -Dlog4j.shutdownHookEnabled=false, -Dlog4j2.disable.jmx=true, -Dlog4j.skipJansi=true, -XX:+HeapDumpOnOutOfMemoryError, -Des.path.home=/usr/share/elasticsearch] skywalking_1 | SkyWalking Web Application started successfully! elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [aggs-matrix-stats] elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [ingest-common] elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [lang-expression] elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [lang-groovy] elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [lang-mustache] elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [lang-painless] elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [parent-join] elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [percolator] elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [reindex] elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [transport-netty3] elasticsearch_1 | [2018-09-17T23:30:31,964][INFO ][o.e.p.PluginsService ] [C3Z3xlS] loaded module [transport-netty4] elasticsearch_1 | [2018-09-17T23:30:31,968][INFO ][o.e.p.PluginsService ] [C3Z3xlS] no plugins loaded kibana_1 | {"type":"log","@timestamp":"2018-09-17T23:30:34Z","tags":["status","plugin:kibana@5.6.11","info"],"pid":11,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
从上图中可以看到 es，kibana，skywalking都启动成功了，你也可以通过docker-compose ps 看一下是否都起来了，netstat 看一下宿主机开放了哪些端口。
[root@localhost docker]# docker ps CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 9aa90401ca16 kibana "/docker-entrypoint.…" 2 minutes ago Up 2 minutes 0.0.0.0:5601->5601/tcp docker_kibana_1 c551248e32af docker_skywalking "/bin/sh -c /app/sky…" 2 minutes ago Up 2 minutes 0.0.0.0:8080->8080/tcp, 0.0.0.0:10800->10800/tcp, 0.0.0.0:11800->11800/tcp, 0.0.0.0:12800->12800/tcp docker_skywalking_1 765d38469ff1 docker_elasticsearch "/docker-entrypoint.…" 2 minutes ago Up 2 minutes 9200/tcp, 9300/tcp docker_elasticsearch_1 [root@localhost docker]# netstat -tlnp Active Internet connections (only servers) Proto Recv-Q Send-Q Local Address Foreign Address State PID/Program name tcp 0 0 192.168.122.1:53 0.0.0.0:* LISTEN 2013/dnsmasq tcp 0 0 0.0.0.0:22 0.0.0.0:* LISTEN 1141/sshd tcp 0 0 127.0.0.1:631 0.0.0.0:* LISTEN 1139/cupsd tcp 0 0 127.0.0.1:25 0.0.0.0:* LISTEN 1622/master tcp6 0 0 :::8080 :::* LISTEN 38262/docker-proxy tcp6 0 0 :::10800 :::* LISTEN 38248/docker-proxy tcp6 0 0 :::22 :::* LISTEN 1141/sshd tcp6 0 0 ::1:631 :::* LISTEN 1139/cupsd tcp6 0 0 :::11800 :::* LISTEN 38234/docker-proxy tcp6 0 0 ::1:25 :::* LISTEN 1622/master tcp6 0 0 :::12800 :::* LISTEN 38222/docker-proxy tcp6 0 0 :::5601 :::* LISTEN 38274/docker-proxy [root@localhost docker]#
然后就可以看一些8080端口的可视化UI，默认用户名密码admin，admin，一个比较耐看的UI就出来了。
三： net下的探针
从nuget上拉取一个SkyWalking.AspNetCore探针进行代码埋点，github地址：https://github.com/OpenSkywalking/skywalking-netcore
在startup类中进行注入，在页面请求中进行一次cnblogs.com的请求操作，然后仔细观察一下调用链跟踪是一个什么样子？
using System; using System.Collections.Generic; using System.Linq; using System.Threading.Tasks; using Microsoft.AspNetCore.Builder; using Microsoft.AspNetCore.Hosting; using Microsoft.AspNetCore.Http; using Microsoft.Extensions.DependencyInjection; using SkyWalking.Extensions; using SkyWalking.AspNetCore; using System.Net; namespace WebApplication1 { public class Startup { // This method gets called by the runtime. Use this method to add services to the container. // For more information on how to configure your application, visit https://go.microsoft.com/fwlink/?LinkID=398940 public void ConfigureServices(IServiceCollection services) { services.AddSkyWalking(option => { // Application code is showed in sky-walking-ui option.ApplicationCode = "10001 测试站点"; //Collector agent_gRPC/grpc service addresses. option.DirectServers = "192.168.23.183:11800"; }); } // This method gets called by the runtime. Use this method to configure the HTTP request pipeline. public void Configure(IApplicationBuilder app, IHostingEnvironment env) { if (env.IsDevelopment()) { app.UseDeveloperExceptionPage(); } app.Run(async (context) => { WebClient client = new WebClient(); var str = client.DownloadString("http://cnblogs.com"); await context.Response.WriteAsync(str); }); } } }
可以看到这张图还是蛮漂亮的哈，也方便我们快速的跟踪代码，发现问题，找出问题， 还有更多的功能期待你的挖掘啦。 好了，本篇就说到这里，希望对你有帮助。
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