本文共 12915 字,大约阅读时间需要 43 分钟。
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做日志中心化,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。
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。
下面是本次搭建的一个目录结构:
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: 0.0.0.0transport.tcp.port: 9300network.host: 0.0.0.0
在up的时候,将这个es文件copy到 容器的config文件夹下。
FROM elasticsearch:5.6.4EXPOSE 9200 9300COPY elasticsearch.yml /usr/share/elasticsearch/config/
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: 100000naming: jetty: host: 0.0.0.0 port: 10800 contextPath: /cache:# guava: caffeine:remote: gRPC: host: 0.0.0.0 port: 11800agent_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: xxxxxxagent_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: trueui: 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: saconfiguration: 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
接下来就是 skywalking的 下载安装,使用dockerfile流程化。
FROM centos:7LABEL username="hxc@qq.com"WORKDIR /appRUN yum install -y wget && \ yum install -y java-1.8.0-openjdkADD http://mirrors.hust.edu.cn/apache/incubator/skywalking/5.0.0-RC2/apache-skywalking-apm-incubating-5.0.0-RC2.tar.gz /appRUN tar -xf apache-skywalking-apm-incubating-5.0.0-RC2.tar.gz && \ mv apache-skywalking-apm-incubating skywalkingRUN ls /app#copy文件COPY application.yml /app/skywalking/config/application.ymlWORKDIR /app/skywalking/binUSER rootRUN echo "tail -f /dev/null" >> /app/skywalking/bin/startup.shCMD ["/bin/sh","-c","/app/skywalking/bin/startup.sh" ]
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"
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。
sudo yum remove docker \docker-client \docker-client-latest \docker-common \docker-latest \docker-latest-logrotate \docker-logrotate \docker-selinux \docker-engine-selinux \docker-enginesudo yum install -y yum-utils \device-mapper-persistent-data \lvm2sudo yum-config-manager \--add-repo \https://download.docker.com/linux/centos/docker-ce.reposudo 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 startRedirecting to /bin/systemctl start docker.service[root@localhost ~]# docker -vDocker version 18.06.1-ce, build e68fc7a
sudo curl -L "https://github.com/docker/compose/releases/download/1.22.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-composesudo chmod +x /usr/local/bin/docker-compose
[root@localhost docker]# docker-compose up --buildCreating network "docker_default" with the default driverBuilding elasticsearchStep 1/3 : FROM elasticsearch:5.6.4 ---> 7a047c21aa48Step 2/3 : EXPOSE 9200 9300 ---> Using cache ---> 8d66bb57b09dStep 3/3 : COPY elasticsearch.yml /usr/share/elasticsearch/config/ ---> Using cache ---> 02b516c03b95Successfully built 02b516c03b95Successfully tagged docker_elasticsearch:latestBuilding skywalkingStep 1/12 : FROM centos:7 ---> 5182e96772bfStep 2/12 : LABEL username="hxc@qq.com" ---> Using cache ---> b95b96a92042Step 3/12 : WORKDIR /app ---> Using cache ---> afdf4efe3426Step 4/12 : RUN yum install -y wget && yum install -y java-1.8.0-openjdk ---> Using cache ---> 46be0ca0f7b5Step 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 ---> d5c30bcfd5eaStep 6/12 : RUN tar -xf apache-skywalking-apm-incubating-5.0.0-RC2.tar.gz && mv apache-skywalking-apm-incubating skywalking ---> Using cache ---> 1438d08d18faStep 7/12 : RUN ls /app ---> Using cache ---> b594124672eaStep 8/12 : COPY application.yml /app/skywalking/config/application.yml ---> Using cache ---> 10eaf0805a65Step 9/12 : WORKDIR /app/skywalking/bin ---> Using cache ---> bc0f02291536Step 10/12 : USER root ---> Using cache ---> 4498afca5fe6Step 11/12 : RUN echo "tail -f /dev/null" >> /app/skywalking/bin/startup.sh ---> Using cache ---> 1c4be7c6b32aStep 12/12 : CMD ["/bin/sh","-c","/app/skywalking/bin/startup.sh" ] ---> Using cache ---> ecfc97e4c97dSuccessfully built ecfc97e4c97dSuccessfully tagged docker_skywalking:latestCreating docker_elasticsearch_1 ... doneCreating docker_skywalking_1 ... doneCreating docker_kibana_1 ... doneAttaching to docker_elasticsearch_1, docker_kibana_1, docker_skywalking_1elasticsearch_1 | [2018-09-17T23:51:57,886][INFO ][o.e.c.m.MetaDataCreateIndexService] [FC_bOh1] [service_metric_day] creating index, cause [api], templates [], shards [2]/[0], mappings [type]elasticsearch_1 | [2018-09-17T23:51:57,962][INFO ][o.e.c.r.a.AllocationService] [FC_bOh1] Cluster health status changed from [YELLOW] to [GREEN] (reason: [shards started [[service_metric_day][0]] ...]).elasticsearch_1 | [2018-09-17T23:51:58,115][INFO ][o.e.c.m.MetaDataCreateIndexService] [FC_bOh1] [application_metric_hour] creating index, cause [api], templates [], shards [2]/[0], mappings [type]elasticsearch_1 | [2018-09-17T23:51:58,176][INFO ][o.e.c.r.a.AllocationService] [FC_bOh1] Cluster health status changed from [YELLOW] to [GREEN] (reason: [shards started [[application_metric_hour][1]] ...]).elasticsearch_1 | [2018-09-17T23:51:58,356][INFO ][o.e.c.m.MetaDataCreateIndexService] [FC_bOh1] [application_metric_month] creating index, cause [api], templates [], shards [2]/[0], mappings [type]elasticsearch_1 | [2018-09-17T23:51:58,437][INFO ][o.e.c.r.a.AllocationService] [FC_bOh1] Cluster health status changed from [YELLOW] to [GREEN] (reason: [shards started [[application_metric_month][0]] ...]).elasticsearch_1 | [2018-09-17T23:51:58,550][INFO ][o.e.c.m.MetaDataCreateIndexService] [FC_bOh1] [instance_mapping_month] creating index, cause [api], templates [], shards [2]/[0], mappings [type]elasticsearch_1 | [2018-09-17T23:52:05,544][INFO ][o.e.c.m.MetaDataCreateIndexService] [FC_bOh1] [gc_metric_minute] creating index, cause [api], templates [], shards [2]/[0], mappings [type]
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 psCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES9aa90401ca16 kibana "/docker-entrypoint.…" 2 minutes ago Up 2 minutes 0.0.0.0:5601->5601/tcp docker_kibana_1c551248e32af 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_1765d38469ff1 docker_elasticsearch "/docker-entrypoint.…" 2 minutes ago Up 2 minutes 9200/tcp, 9300/tcp docker_elasticsearch_1[root@localhost docker]# netstat -tlnpActive 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。
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?
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。
转载地址:http://kakdi.baihongyu.com/