ArgoCD Rollouts介绍 & 部署【三】

Argocd Rollouts

Argocd 架构

#ArgoCD Rollouts
Argo Rollouts
◼ 由一个控制器和一组CRD组成，可为Kubernetes提供高级部署功能，包括
◆blue-green
◆canary
◆canary analysis
◆experimentation
◆progressive delivery
◼ 支持与Ingress Controller（Nginx和ALB）及ServiceMesh（Istio、Linkerd和SMI）集成，利用它们的流量治理能
力实现流量迁移过程
◼ 能够查询和解释来自多种指标系统（Prometheus、Kubernetes Jobs、Web、Datadog等）的指标来验证BlueGreen或Canary部署结果，并根据结果自动决定执行升级或回滚
◼ 几个相关的CRD
◆Rollout、AnalysisTemplate、ClusterAnalysisTemplate和AnalysisRun
基本工作机制
◼ 与Deployment相似，Argo Rollouts控制器借助于ReplicaSet完成应用的创建、缩放和删除；
◼ ReplicaSet资源由Rollout的spec.template字段进行定义

#Rollout Controller


◼ 负责管理Rollout CRD资源对象
Rollout CRD
◼ 由Argo Rollout引入的自定义资源类型，与Kubernetes Deployment兼容，但具有控制高级部署方法的阶段、阈
值和方法的额外字段
◼ 并不会对Kubernetes Deployment施加任何影响，或要使用Rollout的功能，用户需要手动将资源从Deployment迁
移至Rollout
Ingress/Service
◼ Argo Rollouts使用标准的Kubernetes Service，但需要一些额外的元数据
◼ 针对Canary部署，Rollouts支持多种不同的ServiceMesh和Ingress Controller，实现精细化的流量分割和迁移
AnalysisTemplate和AnalysisRun
◼ Analysis是将Rollout连接至特定的Metric Provider，并为其支持的某些指标定义特定的阈值的能力，于是，这些
指标的具体值将决定更新操作是否成功进行；
◼ 若指标查询结果满足阈值，则继续进行；若不能满足，则执行回滚；若查询结果不确定，则暂停；
◼ 为了执行Analysis，Argo Rollouts提供了AnalysisTemplate和AnalysisRun两个CRD

#部署

https://argoproj.github.io/argo-rollouts/
https://github.com/argoproj/argo-rollouts/releases

【实验使用1.3.1】
https://github.com/argoproj/argo-rollouts/releases/tag/v1.3.1
#下载yaml文件
https://github.com/argoproj/argo-rollouts/releases/download/v1.3.1/dashboard-install.yaml
https://github.com/argoproj/argo-rollouts/releases/download/v1.3.1/install.yaml

#下载镜像
crictl pull quay.io/argoproj/argo-rollouts:v1.3.1 && \
crictl pull quay.io/argoproj/kubectl-argo-rollouts:v1.3.1

#Official执行
kubectl create namespace argo-rollouts
kubectl apply -n argo-rollouts -f https://github.com/argoproj/argo-rollouts/releases/download/v1.3.1/install.yaml
kubectl apply -n argo-rollouts -f https://github.com/argoproj/argo-rollouts/releases/download/v1.3.1/dashboard-install.yaml

#本地实验执行
[root@xianchaomaster1 KnativeSrc]# kubectl apply -f install.yaml -f dashboard-install.yaml -n argo-rollouts

[root@xianchaomaster1 KnativeSrc]# kubectl get pods -n argo-rollouts
NAME                                       READY   STATUS    RESTARTS   AGE
argo-rollouts-7f75b9fb76-cjdb7             1/1     Running   0          16s
argo-rollouts-dashboard-69c4f8f8dd-8v2gs   1/1     Running   0          16s

[root@xianchaomaster1 KnativeSrc]# kubectl api-resources --api-group=argoproj.io
NAME                       SHORTNAMES         APIVERSION             NAMESPACED   KIND
analysisruns               ar                 argoproj.io/v1alpha1   true         AnalysisRun
analysistemplates          at                 argoproj.io/v1alpha1   true         AnalysisTemplate
applications               app,apps           argoproj.io/v1alpha1   true         Application
applicationsets            appset,appsets     argoproj.io/v1alpha1   true         ApplicationSet
appprojects                appproj,appprojs   argoproj.io/v1alpha1   true         AppProject
clusteranalysistemplates   cat                argoproj.io/v1alpha1   false        ClusterAnalysisTemplate
experiments                exp                argoproj.io/v1alpha1   true         Experiment
rollouts                   ro                 argoproj.io/v1alpha1   true         Rollout

#启动Dashboard
https://argoproj.github.io/argo-rollouts/dashboard/

#外部访问dashboard
【1】通过Istio开放访问
[root@ca-k8s-master01 argo-rollouts]# cat 03-argo-rollouts-dashboard-virtualservice.yaml
---
apiVersion: networking.istio.io/v1beta1
kind: DestinationRule
metadata:
  name: argo-rollouts-dashboard
  namespace: argo-rollouts
spec:
  host: argo-rollouts-dashboard
  trafficPolicy:
    tls:
      mode: DISABLE
---
apiVersion: networking.istio.io/v1beta1
kind: Gateway
metadata:
  name: argo-rollouts-dashboard-gateway
  namespace: istio-system
spec:
  selector:
    app: istio-ingressgateway
  servers:
  - port:
      number: 80
      name: http
      protocol: HTTP
    hosts:
    - "argo-rollouts.magedu.com"
    - "rollouts.magedu.com"
---
apiVersion: networking.istio.io/v1beta1
kind: VirtualService
metadata:
  name: argo-rollouts-dashboard-virtualservice
  namespace: argo-rollouts
spec:
  hosts:
  - "argo-rollouts.magedu.com"
  - "rollouts.magedu.com"
  gateways:
  - istio-system/argo-rollouts-dashboard-gateway
  http:
  - match:
    - uri:
        prefix: /
    route:
    - destination:
        host: argo-rollouts-dashboard
        port:
          number: 3100
---
[root@ca-k8s-master01 argo-rollouts]# kubectl apply -f 03-argo-rollouts-dashboard-virtualservice.yaml
#配置域名解析  浏览器访问
http://argo-rollouts.magedu.com/

【2】修改svc NodePort类型
[root@xianchaomaster1 KnativeSrc]# kubectl get svc -n argo-rollouts
NAME                      TYPE        CLUSTER-IP       EXTERNAL-IP   PORT(S)    AGE
argo-rollouts-dashboard   ClusterIP   10.105.138.153   <none>        3100/TCP   25m
argo-rollouts-metrics     ClusterIP   10.97.119.54     <none>        8090/TCP   25m

[root@xianchaomaster1 KnativeSrc]# kubectl edit svc argo-rollouts-dashboard -n argo-rollouts
    NodePort
service/argo-rollouts-dashboard edited

[root@xianchaomaster1 KnativeSrc]# kubectl get svc -n argo-rollouts
NAME                      TYPE        CLUSTER-IP       EXTERNAL-IP   PORT(S)          AGE
argo-rollouts-dashboard   NodePort    10.105.138.153   <none>        3100:31124/TCP   26m
argo-rollouts-metrics     ClusterIP   10.97.119.54     <none>        8090/TCP         27m

#访问dashboard
http://192.168.40.180:31124/rollouts/

#部署工具
下载：https://github.com/argoproj/argo-rollouts/releases/download/v1.3.1/kubectl-argo-rollouts-linux-amd64

[root@xianchaomaster1 KnativeSrc]# cp kubectl-argo-rollouts-linux-amd64 /usr/bin/kubectl-argo-rollouts
You have new mail in /var/spool/mail/root
[root@xianchaomaster1 KnativeSrc]# chmod +x /usr/bin/kubectl-argo-rollouts
[root@xianchaomaster1 KnativeSrc]# kubectl-argo-rollouts --help
This command consists of multiple subcommands which can be used to manage Argo Rollouts.

Usage:
  kubectl-argo-rollouts COMMAND [flags]
  kubectl-argo-rollouts [command]

Examples:
  # Get guestbook rollout and watch progress
  kubectl argo rollouts get rollout guestbook -w

  # Pause the guestbook rollout
  kubectl argo rollouts pause guestbook

  # Promote the guestbook rollout
  kubectl argo rollouts promote guestbook

  # Abort the guestbook rollout
  kubectl argo rollouts abort guestbook

  # Retry the guestbook rollout
  kubectl argo rollouts retry guestbook

Available Commands:
  abort         Abort a rollout
  completion    Generate completion script
  create        Create a Rollout, Experiment, AnalysisTemplate, ClusterAnalysisTemplate, or AnalysisRun resource
  dashboard     Start UI dashboard
  get           Get details about rollouts and experiments
  help          Help about any command
  lint          Lint and validate a Rollout
  list          List rollouts or experiments
  notifications Set of CLI commands that helps manage notifications settings
  pause         Pause a rollout
  promote       Promote a rollout
  restart       Restart the pods of a rollout
  retry         Retry a rollout or experiment
  set           Update various values on resources
  status        Show the status of a rollout
  terminate     Terminate an AnalysisRun or Experiment
  undo          Undo a rollout
  version       Print version

Flags:
      --as string                      Username to impersonate for the operation. User could be a regular user or a service account in a namespace.
      --as-group stringArray           Group to impersonate for the operation, this flag can be repeated to specify multiple groups.
      --as-uid string                  UID to impersonate for the operation.
      --cache-dir string               Default cache directory (default "/root/.kube/cache")
      --certificate-authority string   Path to a cert file for the certificate authority
      --client-certificate string      Path to a client certificate file for TLS
      --client-key string              Path to a client key file for TLS
      --cluster string                 The name of the kubeconfig cluster to use
      --context string                 The name of the kubeconfig context to use
  -h, --help                           help for kubectl-argo-rollouts
      --insecure-skip-tls-verify       If true, the server's certificate will not be checked for validity. This will make your HTTPS connections insecure
  -v, --kloglevel int                  Log level for kubernetes client library
      --kubeconfig string              Path to the kubeconfig file to use for CLI requests.
      --loglevel string                Log level for kubectl argo rollouts (default "info")
  -n, --namespace string               If present, the namespace scope for this CLI request
      --request-timeout string         The length of time to wait before giving up on a single server request. Non-zero values should contain a corresponding time unit (e.g. 1s, 2m, 3h). A value of zero means don't timeout requests. (default "0")
  -s, --server string                  The address and port of the Kubernetes API server
      --tls-server-name string         Server name to use for server certificate validation. If it is not provided, the hostname used to contact the server is used
      --token string                   Bearer token for authentication to the API server
      --user string                    The name of the kubeconfig user to use

Use "kubectl-argo-rollouts [command] --help" for more information about a command.

或者[root@xianchaomaster1 KnativeSrc]# kubectl argo rollouts

Rollout CRD的资源规范

#Rollout的功能在很大程度上与Deployment兼容，支持的字段也有不少相同之处
#Rollout CRD的spec字段支持使用的字段包括
    ◼ replicas <integer>：运行的Pod实例数量，默认为1；
    ◼ selector <Object>：筛选Pod对象的标签选择器；
    ◼ template <Object>：ReplicaSet模板对象；
    ◼ revisionHistoryLimit <integer>：更新历史中保留的ReplicaSet Revision数量；
    ◼ minReadySeconds <integer>：无容器crash的情况下，新建的Pod被视为可用的最短时长，默认为0，即立即转为Ready；
    ◼ paused <boolean>：是否置为暂停状态；
    ◼ progressDeadlineSeconds <integer>：更新过程中，更新步骤的最大等待时长，默认为600秒；
    ◼ progressDeadlineAbort <boolean>： 未使用analysis或experiment而progressDeadlineSeconds超时的情况下，是否中止更新过程，默认为否；
    ◼ restartAt <string>：重启Pod的时刻，其值为UTC时间戳格式；
    ◼ strategy <Object>：更新策略，支持canary和blueGreen两种；

Rollout strategy 更新策略之Canary

#通过spec.strategy.canary启用
#支持内嵌的字段
    ◼ canaryService <string>：由控制器用来匹配到Canary Pods上的Service，trafficRouting依赖于该字段；
    ◼ stableService <string>：由控制器用来匹配到Stable Pods上的Service， trafficRouting依赖于该字段；
    ◼ canaryMetadata <Object>：需要添加到Canary版本的Pod上的元数据，仅存于Canary更新期间，更新完成后即成为Stable；
    ◼ stableMetadata <Object>：需要添加到Stable版本的Pod上的元数据；
    ◼ maxSurge <>
    ◼ maxUnavailable <>
    ◼ scaleDownDelayRevisionLimit <integer>：在旧RS上启动缩容之前，可运行着的旧RS的数量；
    ◼ abortScaleDownDelaySeconds <integer>：启用了trafficRouting时，因更新中止 而收缩Canary版本Pod数量之前的延迟时长，默认为30s；
    ◼ scaleDownDelaySeconds <integer>： 启用了trafficRouting时，缩容前一个ReplicaSet规模的延迟时长，默认为30s；
    ◼ analysis <Object>：在滚动更新期间于后台运行的analysis，可选；
    ◼ steps <[]Object>：Canary更新期间要执行的步骤，可选；
    ◼ trafficRouting <Object>：设定Ingress Controller或ServiceMesh如何动态调整配置以完成精细化地流量分割和流量迁移；
    ◼ antiAffinity <Object>：定义Canary Pod与旧ReplicaSet Pod之间的反亲和关系；

常用的Step

#常用的Step
    ◼ pause <Object>：暂停step
        ◆用于暂停滚动过程
        ◆可内嵌duration字段指定暂停时长，或留空而一直暂停至由用户设定继续进行
    ◼ setWeight <integer>：设定Canary版本ReplicSet激活的Pod比例，以及调度至Canary版本的流量比例；
    ◼ setCanaryScale <Object>：设定Canary扩容期间Pod扩增与流量扩增的对应关系，支持如下三种配置之一
        ◆replicas <integer>：明确设定Canary RS的规模为该处指定的Pod数量，但不改变先前设定的流量比例；
        ◆weight <integer>：明确设定Canary RS的规模为该处指定的比例，但不改变先前设定的流量比例；
        ◆matchTrafficWeight <boolean>：设定Canary的Pod规模与调度至这些Pod的流量同比例滚动；
    ◼ analysis <Object>：内联定义或调用的analysis step；
        ◆args <[]Object>
        ◆dryRun <[]Object>
        ◆templates <[]Object>
        ◆measurementRetention <[]Object>
    ◼ experiment <Object>：内联定义或调用的experiment step；
        ◆analyses <[]Object>
        ◆duration <string>
        ◆templates <[]Object>

#analysis的相关配置
    ◼ args <[]Object>：Canary更新期间，要按需临时设定的参数
        ◆name <string>：要动态设定其值的参数的名称
        ◆value <string>：为相关参数指定一个具体值
        ◆valueFrom <Object>：相关参数的值引用自其它属性或字段的值
    ◼  templates <[]Object>：要引用的AnalysisTemplate
        ◆clusterScope <boolean>
        ◆templateName <string>：引用的AnalysisTemplate的名称
    ◼ dryRun <[]Object>
    ◼ startingStep <integer>
    ◼ measurementRetention <[]Object>

#trafficRouting的相关配置
    ◼ istio <Object>：与Istio协同完成流量迁移
        ◆destinationRule <Object>：Canary期间要自动动态调整其配置以完成流量迁移的DestinationRule资源
            ⚫ name <string>：DestinationRule资源的名称
            ⚫ canarySubsetName <string>：DestinationRule中临时使用的Canary子集的名称
            ⚫ stableSubsetName <string>：DestinationRule中临时使用的Stable子集的名称
        ◆virtualService <Object>：Canary期间要自动动态调整其配置以完成流量迁移的的VirtualService资源
            ⚫ name <string>：VirtualService资源的名称
            ⚫ routes <[]string>：指定的VirtualService资源上要动态调整的路由条目的名称列表，仅有一个路由时可省略该字段
            ⚫ tlsRoutes <[]Object>：指定的VirtualService资源上要动态调整的tls路由条目列表
        ◆virtualServices <[]Object>：Canary期间要自动动态调整其配置以完成流量迁移的的VirtualService资源列表
    ◼ nginx <Object>：与Ingress Nginx协同完成流量迁移
        ◆additionalIngressAnnotations <map[string]string>
        ◆annotationPrefix <string>
        ◆stableIngress <string>：要调整的Stable Ingress资源的名称

posted @ 2023-07-18 11:41 しみずよしだ阅读(417) 评论(0) 收藏举报

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ArgoCD Rollouts介绍 & 部署【三】

Argocd Rollouts

Argocd 架构

#Rollout Controller

#部署

Rollout CRD的资源规范

Rollout strategy 更新策略之Canary

常用的Step

公告