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2022-08-17

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dotnet-monitor可以在Kubernetes中作为Sidecar运行，Sidecar是一个容器，它与应用程序在同一个Pod中运行，利用Sidecar模式使我们可以诊断及监控应用程序。

如下图所示，这是我们最终要实现的目标，通过可视化界面查看应用程序的指标信息。

应用服务

创建dotnetmonitor.yaml文件，如下所示。

apiVersion: apps/v1 kind: Deployment metadata:   name: dotnet-monitor-example spec:   replicas: 3   selector:     matchLabels:       app: dotnet-monitor-example   template:     metadata:       annotations:         prometheus.io/scrape: 'true'         prometheus.io/port: "52325"       labels:         app: dotnet-monitor-example     spec:       containers:         - name: server           image: mcr.microsoft.com/dotnet/core/samples:aspnetapp           ports:             - containerPort: 80           volumeMounts:             - mountPath: /tmp               name: tmp         - name: sidecar           image: mcr.microsoft.com/dotnet/monitor           ports:             - containerPort: 52323           resources:             requests:               cpu: 50m               memory: 32Mi             limits:               cpu: 250m               memory: 256Mi           args: ["--no-auth"]           env:             - name: DOTNETMONITOR_Urls               value: "http://+:52323"           volumeMounts:             - name: tmp               mountPath: /tmp       volumes:         - name: tmp           emptyDir: {}

Sidecar和应用程序共享tmp目录，同时将目录映射到emptyDir类型的 Volume中。接下来，创建dotnetmonitor-service.yaml，为应用程序和Sidecar开放端口。

apiVersion: v1 kind: Service metadata:   name: dotnetmonitor   labels:     app: dotnetmonitor spec:   type: NodePort   ports:     - name: sidecar       protocol: TCP       port: 52323       nodePort: 31623     - name: app       protocol: TCP       port: 80       nodePort: 31624   selector:     app: dotnet-monitor-example

Prometheus配置

创建prometheus-config.yaml文件，通过ConfigMaps管理Prometheus的配置文件，并写入如下内容。

apiVersion: v1 kind: ConfigMap metadata:   name: prometheus-config data:   prometheus.yaml: |     global:       scrape_interval:     2s        evaluation_interval: 2s     scrape_configs:       - job_name: 'prometheus'         static_configs:         - targets: ['localhost:9090']       - job_name: default/dotnet-monitor-example/0         honor_timestamps: true         scrape_interval: 10s         scrape_timeout: 10s         metrics_path: /metrics         scheme: http         follow_redirects: true         relabel_configs:           # 使用 Label "__meta_kubernetes_pod_container_name" 的值         - source_labels: [__meta_kubernetes_pod_container_name]           separator: ;           # 正则表达式，用于匹配源标签值使用的           regex: sidecar           # replacement指定的替换后的标签（target_label）对应的数值           replacement: $1           # keep就是保留符合正则表达式targets，并显示出来           action: keep             - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]           action: keep           regex: true         - source_labels: [__meta_kubernetes_pod_name]           action: replace           target_label: pod         kubernetes_sd_configs:         - role: endpoints           follow_redirects: true           namespaces:             names:             - default

在Prometheus中如果采用静态服务发现（static_configs）模式注册，那么HPA（HorizontalPodAutoscaler，Pod水平自动伸缩）的变动会导致服务很难快速的注册，如果频繁更改配置文件，那么也是得不偿失的，所以，在此处选择kubernetes服务发现（kubernetes_sd_configs）模式，除此之外Prometheus还支持其他方式的服务发现。

static_configs: 静态服务发现
dns_sd_configs: DNS 服务发现
file_sd_configs: 文件服务发现
kubernetes_sd_configs: Kubernetes 服务发现
gce_sd_configs: GCE 服务发现
ec2_sd_configs: EC2 服务发现
openstack_sd_configs: OpenStack 服务发现
azure_sd_configs: Azure 服务发现

现在，意味着我们会在Kubernetes中的会保留__meta_kubernetes_pod_container_name值为sidecar的，同时也需要满足__meta_kubernetes_pod_annotation_prometheus_io_scrape属性为true的Pod。

接下来，创建prometheus-rbac-setup.yaml文件，为了使Prometheus可以访问到Kubernetes API，我们需要对Prometheus进行访问授权，在Kubernetes中通过基于角色的访问控制模型（Role-Based Access Control），用于访问Kubernetes的资源。首先我们定义角色（ClusterRole）并设置相应的访问权限；为Prometheus创建账号（ServiceAccount）；最后将账号与角色进行绑定（ClusterRoleBinding）。

apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata:   name: prometheus rules: - apiGroups: [""]   resources:   - nodes   - nodes/proxy   - services   - endpoints   - pods   verbs: ["get", "list", "watch"] - apiGroups:   - extensions   resources:   - ingresses   verbs: ["get", "list", "watch"] - nonResourceURLs: ["/metrics"]   verbs: ["get"] --- apiVersion: v1 kind: ServiceAccount metadata:   name: prometheus   namespace: default --- apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata:   name: prometheus roleRef:   apiGroup: rbac.authorization.k8s.io   kind: ClusterRole   name: prometheus subjects: - kind: ServiceAccount   name: prometheus   namespace: default

创建prometheus-deployment.yaml文件。

apiVersion: apps/v1 kind: Deployment metadata:   labels:     name: prometheus   name: prometheus spec:   replicas: 1   selector:     matchLabels:       app: prometheus     template:     metadata:       labels:         app: prometheus     spec:       serviceAccountName: prometheus       containers:       - name: prometheus         image: prom/prometheus:latest         command:         - "/bin/prometheus"         args:         - "--config.file=/etc/prometheus/prometheus.yml"         ports:         - containerPort: 9090           protocol: TCP         volumeMounts:         - mountPath: "/etc/prometheus"           name: prometheus-config       volumes:       - name: prometheus-config         configMap:           name: prometheus-config

创建prometheus-service.yaml文件。

apiVersion: v1 kind: Service metadata:   name: prometheus   labels:     name: prometheus spec:   type: NodePort   ports:   - name: prometheus     protocol: TCP     port: 9090     targetPort: 9090     nodePort: 32732   selector:     app: prometheus

如下所示，展示了Prometheus仪表盘