如何使用Istio的Prometheus配置kubernetes hpa?

时间:2018-08-14 12:02:17

标签: kubernetes prometheus istio

我们有一个Istio集群,我们正在尝试为Kubernetes配置水平容器自动缩放。我们希望将请求计数用作hpa的自定义指标。我们如何才能将Istio的Prometheus用于相同的目的?

1 个答案:

答案 0 :(得分:2)

这个问题比我预期的要复杂得多,但是最后我得到了答案。

  1. 首先,您需要配置应用程序以提供自定义指标。它在开发应用程序方面。这是一个使用Go语言制作示例:Watching Metrics With Prometheus

  2. 其次,您需要定义应用程序部署(或Pod或所需的任何组件)并将其部署到Kubernetes,例如:

    apiVersion: extensions/v1beta1
    kind: Deployment
    metadata:
      name: podinfo
    spec:
      replicas: 2
      template:
        metadata:
          labels:
            app: podinfo
          annotations:
            prometheus.io/scrape: 'true'
        spec:
          containers:
          - name: podinfod
            image: stefanprodan/podinfo:0.0.1
            imagePullPolicy: Always
            command:
              - ./podinfo
              - -port=9898
              - -logtostderr=true
              - -v=2
            volumeMounts:
              - name: metadata
                mountPath: /etc/podinfod/metadata
                readOnly: true
            ports:
            - containerPort: 9898
              protocol: TCP
            readinessProbe:
              httpGet:
                path: /readyz
                port: 9898
              initialDelaySeconds: 1
              periodSeconds: 2
              failureThreshold: 1
            livenessProbe:
              httpGet:
                path: /healthz
                port: 9898
              initialDelaySeconds: 1
              periodSeconds: 3
              failureThreshold: 2
            resources:
              requests:
                memory: "32Mi"
                cpu: "1m"
              limits:
                memory: "256Mi"
                cpu: "100m"
          volumes:
            - name: metadata
              downwardAPI:
                items:
                  - path: "labels"
                    fieldRef:
                      fieldPath: metadata.labels
                  - path: "annotations"
                    fieldRef:
                      fieldPath: metadata.annotations
    ---
    apiVersion: v1
    kind: Service
    metadata:
      name: podinfo
      labels:
        app: podinfo
    spec:
      type: NodePort
      ports:
        - port: 9898
          targetPort: 9898
          nodePort: 31198
          protocol: TCP
      selector:
        app: podinfo
    

    请注意字段annotations: prometheus.io/scrape: 'true'。需要请求Prometheus从资源中读取指标。另请注意,还有两个其他注释,它们具有默认值;但是如果您在应用程序中更改了它们,则需要为它们添加正确的值:

    • prometheus.io/path:如果指标路径不是/ metrics,请使用此注释进行定义。
    • prometheus.io/port:在指定的端口上刮除Pod,而不要刮除Pod声明的端口(如果未声明,则默认为无端口目标)。
  3. 下一步,Istio中的Prometheus使用自己修改的Istio目的配置,默认情况下,它会跳过Pod中的自定义指标。因此,您需要对其进行一些修改。 就我而言,我从this example中获取了Pod指标的配置,并仅针对Pod修改了Istio的Prometheus配置:

    kubectl edit configmap -n istio-system prometheus
    

    我根据前面提到的示例更改了标签的顺序:

    # pod's declared ports (default is a port-free target if none are declared).
    - job_name: 'kubernetes-pods'
      # if you want to use metrics on jobs, set the below field to
      # true to prevent Prometheus from setting the `job` label
      # automatically.
      honor_labels: false
      kubernetes_sd_configs:
      - role: pod
      # skip verification so you can do HTTPS to pods
      tls_config:
        insecure_skip_verify: true
      # make sure your labels are in order
      relabel_configs:
      # these labels tell Prometheus to automatically attach source
      # pod and namespace information to each collected sample, so
      # that they'll be exposed in the custom metrics API automatically.
      - source_labels: [__meta_kubernetes_namespace]
        action: replace
        target_label: namespace
      - source_labels: [__meta_kubernetes_pod_name]
        action: replace
        target_label: pod
      # these labels tell Prometheus to look for
      # prometheus.io/{scrape,path,port} annotations to configure
      # how to scrape
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
        action: keep
        regex: true
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
        action: replace
        target_label: __metrics_path__
        regex: (.+)
      - source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port]
        action: replace
        regex: ([^:]+)(?::\d+)?;(\d+)
        replacement: $1:$2
        target_label: __address__
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scheme]
        action: replace
        target_label: __scheme__
    

    此后,自定义指标出现在Prometheus中。但是,在更改Prometheus配置时要小心,因为Istio所需的某些指标可能会消失,请仔细检查所有内容。

  4. 现在是时候安装Prometheus custom metric adapter

    • 下载this存储库
    • 在文件<repository-directory>/deploy/manifests/custom-metrics-apiserver-deployment.yaml中更改Prometheus服务器的地址。例如- --prometheus-url=http://prometheus.istio-system:9090/
    • 运行命令kubectl apply -f <repository-directory>/deploy/manifests 一段时间后,custom.metrics.k8s.io/v1beta1应该出现在命令“ kubectl api-vesions”的输出中。

    此外,使用命令kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1" | jq .kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/default/pods/*/http_requests" | jq .检查自定义API的输出 下一个示例的输出应类似于以下示例:

    {
      "kind": "MetricValueList",
      "apiVersion": "custom.metrics.k8s.io/v1beta1",
      "metadata": {
        "selfLink": "/apis/custom.metrics.k8s.io/v1beta1/namespaces/default/pods/%2A/http_requests"
      },
      "items": [
        {
          "describedObject": {
            "kind": "Pod",
            "namespace": "default",
            "name": "podinfo-6b86c8ccc9-kv5g9",
            "apiVersion": "/__internal"
              },
              "metricName": "http_requests",
              "timestamp": "2018-01-10T16:49:07Z",
              "value": "901m"    },
            {
          "describedObject": {
            "kind": "Pod",
            "namespace": "default",
            "name": "podinfo-6b86c8ccc9-nm7bl",
            "apiVersion": "/__internal"
          },
          "metricName": "http_requests",
          "timestamp": "2018-01-10T16:49:07Z",
          "value": "898m"
        }
      ]
    }
    

    如果是,则可以转到下一步。如果没有,请查看CustomMetrics kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1" | jq . | grep "pods/"中的Pod和http_requests kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1" | jq . | grep "http"中可用的API。 MetricNames是根据Prometheus从Pods收集的度量标准生成的,如果它们为空,则需要朝该方向查看。

  5. 最后一步是配置HPA并对其进行测试。因此,就我而言,我为podinfo应用程序创建了HPA,该应用程序之前已定义:

    apiVersion: autoscaling/v2beta1
    kind: HorizontalPodAutoscaler
    metadata:
      name: podinfo
    spec:
      scaleTargetRef:
        apiVersion: extensions/v1beta1
        kind: Deployment
        name: podinfo
      minReplicas: 2
      maxReplicas: 10
      metrics:
      - type: Pods
        pods:
          metricName: http_requests
          targetAverageValue: 10
    

    并使用简单的Go应用程序测试负载:

    #install hey
    go get -u github.com/rakyll/hey
    #do 10K requests rate limited at 25 QPS
    hey -n 10000 -q 5 -c 5 http://<K8S-IP>:31198/healthz
    

    一段时间后,我看到使用命令kubectl describe hpakubectl get hpa

我使用了Ensure High Availability and Uptime With Kubernetes Horizontal Pod Autoscaler and Prometheus文章中有关创建自定义指标的说明

所有有用的链接都放在一个位置: