技术分享 | 在GreatDB分布式部署模式中使用Chaos Mesh做混沌测试

ywz888
发布于 2022-8-29 15:38
浏览
0收藏

● 1. 需求背景与万里安全数据库软件GreatDB分布式部署模式介绍
● 2. 环境准备
● 3. Chaos Mesh的使用
● 4. 在argo中编排测试流程

 

1. 需求背景与万里安全数据库软件GreatDB分布式部署模式介绍


1.1 需求背景


混沌测试是检测分布式系统不确定性、建立系统弹性信心的一种非常好的方式,因此我们采用开源工具Chaos Mesh来做GreatDB分布式集群的混沌测试。

 

1.2 万里安全数据库软件GreatDB分布式部署模式介绍


万里安全数据库软件GreatDB 是一款关系型数据库软件,同时支持集中式和分布式的部署方式,本文涉及的是分布式部署方式。

 

分布式部署模式采用shared-nothing架构;通过数据冗余与副本管理确保数据库无单点故障;数据sharding与分布式并行计算实现数据库系统高性能;可无限制动态扩展数据节点,满足业务需要。

 

整体架构如下图所示:技术分享 | 在GreatDB分布式部署模式中使用Chaos Mesh做混沌测试-鸿蒙开发者社区

 

2. 环境准备


2.1 Chaos Mesh安装


在安装Chaos Mesh之前请确保已经预先安装了helm,docker,并准备好了一个kubernetes环境。

 

● 使用Helm安装


1)在 Helm 仓库中添加 Chaos Mesh 仓库:

helm repo add chaos-mesh https://charts.chaos-mesh.org

 

2)查看可以安装的 Chaos Mesh 版本:

helm search repo chaos-mesh

 

3)创建安装 Chaos Mesh 的命名空间:

kubectl create ns chaos-testing

 

4)在docker环境下安装Chaos Mesh:

helm install chaos-mesh chaos-mesh/chaos-mesh -n=chaos-testing

 

● 验证安装


执行以下命令查看Chaos Mesh的运行情况:

 

kubectl get pod -n chaos-testing

 

下面是预期输出:

NAME                                       READY   STATUS    RESTARTS   AGE
chaos-controller-manager-d7bc9ccb5-dbccq   1/1     Running   0          26d
chaos-daemon-pzxc7                         1/1     Running   0          26d
chaos-dashboard-5887f7559b-kgz46           1/1     Running   1          26d

 

如果3个pod的状态都是Running,表示 Chaos Mesh 已经成功安装。

 

2.2 准备测试需要的镜像


2.2.1 准备mysql镜像


一般情况下,mysql使用官方5.7版本的镜像,mysql监控采集器使用的是mysqld-exporter,也可以直接从docker hub下载:

docker pull mysql:5.7
docker pull prom/mysqld-exporter

 

2.2.2 准备zookeeper镜像


zookeeper使用的是官方3.5.5版本镜像,zookeeper组件涉及的监控有jmx-prometheus-exporter 和zookeeper-exporter,均从docker hub下载:

docker pull zookeeper:3.5.5
docker pull sscaling/jmx-prometheus-exporter
docker pull josdotso/zookeeper-exporter

 

2.2.3 准备GreatDB镜像


选择一个GreatDB的tar包,将其解压得到一个./greatdb目录,再将greatdb-service-docker.sh文件拷贝到这个解压出来的./greatdb目录里:

cp greatdb-service-docker.sh ./greatdb/

 

将greatdb Dockerfile放到./greatdb文件夹的同级目录下,然后执行以下命令构建GreatDB镜像:

docker build -t greatdb/greatdb:tag2021 .

 

2.2.4 准备GreatDB分布式集群部署/清理的镜像


下载集群部署脚本cluster-setup,集群初始化脚本init-zk 以及集群helm charts包(可咨询4.0开发/测试组获取)

 

将上述材料放在同一目录下,编写如下Dockerfile:

FROM debian:buster-slim as init-zk

COPY ./init-zk /root/init-zk
RUN chmod +x /root/init-zk

FROM debian:buster-slim as cluster-setup
\# Set aliyun repo for speed
RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list && \
  sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list

RUN apt-get -y update && \
  apt-get -y install \
  curl \
  wget

RUN curl -L https://storage.googleapis.com/kubernetes-release/release/v1.20.1/bin/linux/amd64/kubectl -o /usr/local/bin/kubectl && \
  chmod +x /usr/local/bin/kubectl && \
  mkdir /root/.kube && \
  wget https://get.helm.sh/helm-v3.5.3-linux-amd64.tar.gz && \
  tar -zxvf helm-v3.5.3-linux-amd64.tar.gz && \
  mv linux-amd64/helm /usr/local/bin/helm

COPY ./config /root/.kube/
COPY ./helm /helm
COPY ./cluster-setup /

 

执行以下命令构建所需镜像:

docker build --target init-zk -t greatdb/initzk:latest .

docker build --target cluster-setup -t greatdb/cluster-setup:v1 .

 

2.2.5 准备测试用例的镜像


目前测试支持的用例有:bank,bank2,pbank,tpcc,flashback等,每个用例都是一个可执行文件。

 

以flashback测例为例构建测试用例的镜像,先将用例下载到本地,在用例的同一目录下编写如下内容的Dockerfile:

FROM debian:buster-slim
COPY ./flashback /
RUN cd / && chmod +x ./flashback

 

执行以下命令构建测试用例镜像:

docker build -t greatdb/testsuite-flashback:v1 .

 

2.3 将准备好的镜像上传到私有仓库中


创建私有仓库和上传镜像操作请参考:https://zhuanlan.zhihu.com/p/78543733

 

3. Chaos Mesh的使用


3.1 搭建GreatDB分布式集群


在上一章2.2.4 中cluster-setup目录下执行以下命令块去搭建测试集群:

./cluster-setup  \
-clustername=c0 \
-namespace=test \
-enable-monitor=true \
-mysql-image=mysql:5.7 \
-mysql-replica=3 \
-mysql-auth=1 \
-mysql-normal=1 \
-mysql-global=1 \
-mysql-partition=1 \
-zookeeper-repository=zookeeper \
-zookeeper-tag=3.5.5 \
-zookeeper-replica=3 \
-greatdb-repository=greatdb/greatdb \
-greatdb-tag=tag202110 \
-greatdb-replica=3 \
-greatdb-serviceHost=172.16.70.249

 

输出信息:

liuxinle@liuxinle-OptiPlex-5060:~/k8s/cluster-setup$ ./cluster-setup \
> -clustername=c0 \
> -namespace=test \
> -enable-monitor=true \
> -mysql-image=mysql:5.7 \
> -mysql-replica=3 \
> -mysql-auth=1 \
> -mysql-normal=1 \
> -mysql-global=1 \
> -mysql-partition=1 \
> -zookeeper-repository=zookeeper \
> -zookeeper-tag=3.5.5 \
> -zookeeper-replica=3 \
> -greatdb-repository=greatdb/greatdb \
> -greatdb-tag=tag202110 \
> -greatdb-replica=3 \
> -greatdb-serviceHost=172.16.70.249
INFO[2021-10-14T10:41:52+08:00] SetUp the cluster ...                         NameSpace=test
INFO[2021-10-14T10:41:52+08:00] create namespace ...                         
INFO[2021-10-14T10:41:57+08:00] copy helm chart templates ...                
INFO[2021-10-14T10:41:57+08:00] setup ...                                     Component=MySQL
INFO[2021-10-14T10:41:57+08:00] exec helm install and update greatdb-cfg.yaml ... 
INFO[2021-10-14T10:42:00+08:00] waiting mysql pods running ...               
INFO[2021-10-14T10:44:27+08:00] setup ...                                     Component=Zookeeper
INFO[2021-10-14T10:44:28+08:00] waiting zookeeper pods running ...           
INFO[2021-10-14T10:46:59+08:00] update greatdb-cfg.yaml                      
INFO[2021-10-14T10:46:59+08:00] setup ...                                     Component=greatdb
INFO[2021-10-14T10:47:00+08:00] waiting greatdb pods running ...             
INFO[2021-10-14T10:47:21+08:00] waiting cluster running ...                  
INFO[2021-10-14T10:47:27+08:00] waiting prometheus server running...         
INFO[2021-10-14T10:47:27+08:00] Dump Cluster Info                            
INFO[2021-10-14T10:47:27+08:00] SetUp success.                                ClusterName=c0 NameSpace=test

 

执行如下命令,查看集群pod状态:

kubectl get pod -n test -o wide

 

输出信息:

NAME                                    READY   STATUS      RESTARTS   AGE     IP             NODE                     NOMINATED NODE   READINESS GATES
c0-auth0-mysql-0                        2/2     Running     0          10m     10.244.87.18   liuxinle-optiplex-5060   <none>           <none>
c0-auth0-mysql-1                        2/2     Running     0          9m23s   10.244.87.54   liuxinle-optiplex-5060   <none>           <none>
c0-auth0-mysql-2                        2/2     Running     0          8m39s   10.244.87.57   liuxinle-optiplex-5060   <none>           <none>
c0-greatdb-0                            2/2     Running     1          5m3s    10.244.87.58   liuxinle-optiplex-5060   <none>           <none>
c0-greatdb-1                            2/2     Running     0          4m57s   10.244.87.20   liuxinle-optiplex-5060   <none>           <none>
c0-greatdb-2                            2/2     Running     0          4m50s   10.244.87.47   liuxinle-optiplex-5060   <none>           <none>
c0-glob0-mysql-0                        2/2     Running     0          10m     10.244.87.51   liuxinle-optiplex-5060   <none>           <none>
c0-glob0-mysql-1                        2/2     Running     0          9m23s   10.244.87.41   liuxinle-optiplex-5060   <none>           <none>
c0-glob0-mysql-2                        2/2     Running     0          8m38s   10.244.87.60   liuxinle-optiplex-5060   <none>           <none>
c0-nor0-mysql-0                         2/2     Running     0          10m     10.244.87.29   liuxinle-optiplex-5060   <none>           <none>
c0-nor0-mysql-1                         2/2     Running     0          9m29s   10.244.87.4    liuxinle-optiplex-5060   <none>           <none>
c0-nor0-mysql-2                         2/2     Running     0          8m45s   10.244.87.25   liuxinle-optiplex-5060   <none>           <none>
c0-par0-mysql-0                         2/2     Running     0          10m     10.244.87.55   liuxinle-optiplex-5060   <none>           <none>
c0-par0-mysql-1                         2/2     Running     0          9m26s   10.244.87.13   liuxinle-optiplex-5060   <none>           <none>
c0-par0-mysql-2                         2/2     Running     0          8m42s   10.244.87.21   liuxinle-optiplex-5060   <none>           <none>
c0-prometheus-server-6697649b76-fkvh9   2/2     Running     0          4m36s   10.244.87.37   liuxinle-optiplex-5060   <none>           <none>
c0-zookeeper-0                          1/1     Running     1          7m35s   10.244.87.44   liuxinle-optiplex-5060   <none>           <none>
c0-zookeeper-1                          1/1     Running     0          6m41s   10.244.87.30   liuxinle-optiplex-5060   <none>           <none>
c0-zookeeper-2                          1/1     Running     0          6m10s   10.244.87.49   liuxinle-optiplex-5060   <none>           <none>
c0-zookeeper-initzk-7hbfs               0/1     Completed   0          7m35s   10.244.87.17   liuxinle-optiplex-5060   <none>           <none>

 

看到c0-zookeeper-initzk-7hbfs的状态是Completed,其他pod的状态为Running,表示集群搭建成功。

 

3.2 在GreatDB分布式集群中使用Chaos Mesh做混沌测试


Chaos Mesh在kubernetes环境支持注入的故障类型包括:模拟Pod故障、模拟网络故障、模拟压力场景等,这里我们以模拟Pod故障中的pod-kill为例。

 

将实验配置写入到文件中 pod-kill.yaml,内容示例如下:

apiVersion: chaos-mesh.org/v1alpha1
kind: PodChaos   # 要注入的故障类型
metadata:
  name: pod-failure-example
  namespace: test   # 测试集群pod所在的namespace
spec:
  action: pod-kill   # 要注入的具体故障类型
  mode: all    # 指定实验的运行方式,all(表示选出所有符合条件的 Pod)
  duration: '30s'    # 指定实验的持续时间 
  selector: 
    labelSelectors:
      "app.kubernetes.io/component": "greatdb"    # 指定注入故障目标pod的标签,通过kubectl describe pod c0-greatdb-1 -n test 命令返回结果中Labels后的内容得到

 

创建故障实验,命令如下:

kubectl create -n test -f pod-kill.yaml

 

创建完故障实验之后,执行命令 kubectl get pod -n test -o wide 结果如下:

NAME                                    READY   STATUS              RESTARTS   AGE     IP             NODE                     NOMINATED NODE   READINESS GATES
c0-auth0-mysql-0                        2/2     Running             0          14m     10.244.87.18   liuxinle-optiplex-5060   <none>           <none>
c0-auth0-mysql-1                        2/2     Running             0          14m     10.244.87.54   liuxinle-optiplex-5060   <none>           <none>
c0-auth0-mysql-2                        2/2     Running             0          13m     10.244.87.57   liuxinle-optiplex-5060   <none>           <none>
c0-greatdb-0                            0/2     ContainerCreating   0          2s      <none>         liuxinle-optiplex-5060   <none>           <none>
c0-greatdb-1                            0/2     ContainerCreating   0          2s      <none>         liuxinle-optiplex-5060   <none>           <none>
c0-glob0-mysql-0                        2/2     Running             0          14m     10.244.87.51   liuxinle-optiplex-5060   <none>           <none>
c0-glob0-mysql-1                        2/2     Running             0          14m     10.244.87.41   liuxinle-optiplex-5060   <none>           <none>
c0-glob0-mysql-2                        2/2     Running             0          13m     10.244.87.60   liuxinle-optiplex-5060   <none>           <none>
c0-nor0-mysql-0                         2/2     Running             0          14m     10.244.87.29   liuxinle-optiplex-5060   <none>           <none>
c0-nor0-mysql-1                         2/2     Running             0          14m     10.244.87.4    liuxinle-optiplex-5060   <none>           <none>
c0-nor0-mysql-2                         2/2     Running             0          13m     10.244.87.25   liuxinle-optiplex-5060   <none>           <none>
c0-par0-mysql-0                         2/2     Running             0          14m     10.244.87.55   liuxinle-optiplex-5060   <none>           <none>
c0-par0-mysql-1                         2/2     Running             0          14m     10.244.87.13   liuxinle-optiplex-5060   <none>           <none>
c0-par0-mysql-2                         2/2     Running             0          13m     10.244.87.21   liuxinle-optiplex-5060   <none>           <none>
c0-prometheus-server-6697649b76-fkvh9   2/2     Running             0          9m24s   10.244.87.37   liuxinle-optiplex-5060   <none>           <none>
c0-zookeeper-0                          1/1     Running             1          12m     10.244.87.44   liuxinle-optiplex-5060   <none>           <none>
c0-zookeeper-1                          1/1     Running             0          11m     10.244.87.30   liuxinle-optiplex-5060   <none>           <none>
c0-zookeeper-2                          1/1     Running             0          10m     10.244.87.49   liuxinle-optiplex-5060   <none>           <none>
c0-zookeeper-initzk-7hbfs               0/1     Completed           0          12m     10.244.87.17   liuxinle-optiplex-5060   <none>           <none>

 

可以看到有带greatdb名字的pod正在被重启,说明注入故障成功。

 

4. 在argo中编排测试流程


Argo 是一个开源的容器本地工作流引擎,用于在Kubernetes上完成工作,可以将多步骤工作流建模为一系列任务,完成测试流程编排。

 

我们使用argo定义一个测试任务,基本的测试流程是固定的,如下所示:技术分享 | 在GreatDB分布式部署模式中使用Chaos Mesh做混沌测试-鸿蒙开发者社区

 

测试流程的step1是部署测试集群,接着开启两个并行任务,step2跑测试用例,模拟业务场景,step3同时使用Chaos Mesh注入故障,step2的测试用例执行结束之后,step4终止故障注入,最后step5清理集群环境。

 

4.1 用argo编排一个混沌测试工作流(以flashback测试用例为例)


1)修改 cluster-setup.yaml 中的image信息,改成步骤2.2 准备测试需要的镜像中自己传上去的集群部署/清理镜像名和tag

 

2)修改 testsuite-flashback.yaml 中的image信息,改成步骤2.2 准备测试需要的镜像中自己传上去的测试用例镜像名和tag

 

3)将集群部署、测试用例和工具模板的yaml文件全部使用 kubectl apply -n argo -f xxx.yaml 命令创建资源 (这些文件定义了一些argo template,方便用户写workflow时候使用)

kubectl apply -n argo -f cluster-setup.yaml
kubectl apply -n argo -f testsuite-flashback.yaml
kubectl apply -n argo -f tools-template.yaml

 

4)复制一份workflow模板文件 workflow-template.yaml,将模板文件中注释提示的部分修改为自己的设置即可,然后执行以下命令创建混沌测试工作流:

kubectl apply -n argo -f workflow-template.yaml

 

以下是一份workflow模板文件:

apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
  generateName: chaostest-c0-0-
  name: chaostest-c0-0
  namespace: argo
spec:
  entrypoint: test-entry #测试入口,在这里传入测试参数,填写clustername、namespace、host、greatdb镜像名和tag名等基本信息
  serviceAccountName: argo
  arguments:
    parameters:
      - name: clustername
        value: c0
      - name: namespace
        value: test
      - name: host
        value: 172.16.70.249
      - name: port
        value: 30901
      - name: password
        value: Bgview@2020
      - name: user
        value: root
      - name: run-time
        value: 10m
      - name: greatdb-repository
        value: greatdb/greatdb
      - name: greatdb-tag
        value: tag202110
      - name: nemesis
        value: kill_mysql_normal_master,kill_mysql_normal_slave,kill_mysql_partition_master,kill_mysql_partition_slave,kill_mysql_auth_master,kill_mysql_auth_slave,kill_mysql_global_master,kill_mysql_global_slave,kill_mysql_master,kill_mysql_slave,net_partition_mysql_normal,net_partition_mysql_partition,net_partition_mysql_auth,net_partition_mysql_global
      - name: mysql-partition
        value: 1
      - name: mysql-global
        value: 1
      - name: mysql-auth
        value: 1
      - name: mysql-normal
        value: 2
  templates:
    - name: test-entry
      steps:
        - - name: setup-greatdb-cluster  # step.1 集群部署. 请指定正确的参数,主要是mysql和zookeeper的镜像名、tag名
            templateRef:
              name: cluster-setup-template
              template: cluster-setup
            arguments:
              parameters:
                - name: namespace
                  value: "{{workflow.parameters.namespace}}"
                - name: clustername
                  value: "{{workflow.parameters.clustername}}"
                - name: mysql-image
                  value: mysql:5.7.34
                - name: mysql-replica
                  value: 3
                - name: mysql-auth
                  value: "{{workflow.parameters.mysql-auth}}"
                - name: mysql-normal
                  value: "{{workflow.parameters.mysql-normal}}"
                - name: mysql-partition
                  value: "{{workflow.parameters.mysql-partition}}"
                - name: mysql-global
                  value: "{{workflow.parameters.mysql-global}}"
                - name: enable-monitor
                  value: false
                - name: zookeeper-repository
                  value: zookeeper
                - name: zookeeper-tag
                  value: 3.5.5
                - name: zookeeper-replica
                  value: 3
                - name: greatdb-repository
                  value: "{{workflow.parameters.greatdb-repository}}"
                - name: greatdb-tag
                  value: "{{workflow.parameters.greatdb-tag}}"
                - name: greatdb-replica
                  value: 3
                - name: greatdb-serviceHost
                  value: "{{workflow.parameters.host}}"
                - name: greatdb-servicePort
                  value: "{{workflow.parameters.port}}"
        - - name: run-flashbacktest    # step.2 运行测试用例,请替换为你要运行的测试用例template并指定正确的参数,主要是测试使用的表个数和大小
            templateRef:
              name: flashback-test-template
              template: flashback
            arguments:
              parameters:
                - name: user
                  value: "{{workflow.parameters.user}}"
                - name: password
                  value: "{{workflow.parameters.password}}"
                - name: host
                  value: "{{workflow.parameters.host}}"
                - name: port
                  value: "{{workflow.parameters.port}}"
                - name: concurrency
                  value: 16
                - name: size
                  value: 10000
                - name: tables
                  value: 10
                - name: run-time
                  value: "{{workflow.parameters.run-time}}"
                - name: single-statement
                  value: true
                - name: manage-statement
                  value: true
          - name: invoke-chaos-for-flashabck-test    # step.3 注入故障,请指定正确的参数,这里run-time和interval分别定义了故障注入的时间和频次,因此省略掉了终止故障注入步骤
            templateRef:
              name: chaos-rto-template
              template: chaos-rto
            arguments:
              parameters:
                - name: user
                  value: "{{workflow.parameters.user}}"
                - name: host
                  value: "{{workflow.parameters.host}}"
                - name: password
                  value: "{{workflow.parameters.password}}"
                - name: port
                  value: "{{workflow.parameters.port}}"
                - name: k8s-config
                  value: /root/.kube/config
                - name: namespace
                  value: "{{workflow.parameters.namespace}}"
                - name: clustername
                  value: "{{workflow.parameters.clustername}}"
                - name: prometheus
                  value: ''
                - name: greatdb-job
                  value: greatdb-monitor-greatdb
                - name: nemesis
                  value: "{{workflow.parameters.nemesis}}"
                - name: nemesis-duration
                  value: 1m
                - name: nemesis-mode
                  value: default
                - name: wait-time
                  value: 5m
                - name: check-time
                  value: 5m
                - name: nemesis-scope
                  value: 1
                - name: nemesis-log
                  value: true
                - name: enable-monitor
                  value: false
                - name: run-time
                  value: "{{workflow.parameters.run-time}}"
                - name: interval
                  value: 1m
                - name: monitor-log
                  value: false
                - name: enable-rto
                  value: false
                - name: rto-qps
                  value: 0.1
                - name: rto-warm
                  value: 5m
                - name: rto-time
                  value: 1m
                - name: log-level
                  value: debug
        - - name: flashbacktest-output         # 输出测试用例是否通过的结果
            templateRef:
              name: tools-template
              template: output-result
            arguments:
              parameters:
                - name: info
                  value: "flashback test pass, with nemesis: {{workflow.parameters.nemesis}}"
        - - name: clean-greatdb-cluster           # step.4 清理测试集群,这里的参数和step.1的参数一致
            templateRef:
              name: cluster-setup-template
              template: cluster-setup
            arguments:
              parameters:
                - name: namespace
                  value: "{{workflow.parameters.namespace}}"
                - name: clustername
                  value: "{{workflow.parameters.clustername}}"
                - name: mysql-image
                  value: mysql:5.7
                - name: mysql-replica
                  value: 3
                - name: mysql-auth
                  value: "{{workflow.parameters.mysql-auth}}"
                - name: mysql-normal
                  value: "{{workflow.parameters.mysql-normal}}"
                - name: mysql-partition
                  value: "{{workflow.parameters.mysql-partition}}"
                - name: mysql-global
                  value: "{{workflow.parameters.mysql-global}}"
                - name: enable-monitor
                  value: false
                - name: zookeeper-repository
                  value: zookeeper
                - name: zookeeper-tag
                  value: 3.5.5
                - name: zookeeper-replica
                  value: 3
                - name: greatdb-repository
                  value: "{{workflow.parameters.greatdb-repository}}"
                - name: greatdb-tag
                  value: "{{workflow.parameters.greatdb-tag}}"
                - name: greatdb-replica
                  value: 3
                - name: greatdb-serviceHost
                  value: "{{workflow.parameters.host}}"
                - name: greatdb-servicePort
                  value: "{{workflow.parameters.port}}"
                - name: clean
                  value: true
        - - name: echo-result
            templateRef:
              name: tools-template
              template: echo
            arguments:
              parameters:
                - name: info
                  value: "{{item}}"
            withItems:
              - "{{steps.flashbacktest-output.outputs.parameters.result}}"

 

Enjoy GreatSQL :)

 

文章转载自公众号:GreatSQL社区

分类
标签
已于2022-8-29 15:38:12修改
收藏
回复
举报
回复
    相关推荐