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ArgoCD 简介
ArgoCD 是一个基于 GitOps 的持续交付工具，专为 Kubernetes 环境设计，以声明式的方式部署和管理应用程序。
ArgoCD 通过 Prometheus 协议暴露指标，通过这些指标可用于监控 ArgoCD 服务状态和应用状态。ArgoCD 主要暴露三类指标：
- Application Controller Metrics：ArgoCD 应用相关指标，例如应用数、ArgoCD 状态等。
- API Server Metrics：ArgoCD API 请求指标，例如请求数、响应码等。
- Repo Server Metrics：Repo Server 相关指标，例如 Git 请求数、Git 响应时间等。
本次介绍的是通过 KubernetesPrometheus 的自动发现，采集 ArgoCD 的指标数据。
观测云
观测云是一款专为IT工程师打造的全链路可观测产品，它集成了基础设施监控、应用程序性能监控和日志管理，为整个技术栈提供实时可观察性。这款产品能够帮助工程师全面了解端到端的用户体验追踪，了解应用内函数的每一次调用，以及全面监控云时代的基础设施。此外，观测云还具备快速发现系统安全风险的能力，为数字化时代提供安全保障。
部署 DataKit
登录观测云控制台，点击「集成」 -「DataKit」 - 「Kubernetes」，下载 datakit.yaml，拷贝第 3 步中的 token。
编辑 datakit.yaml ，把 token 粘贴到 ENV_DATAWAY 环境变量值中“token=”后面。
kubectl apply -f datakit.yaml
kubectl get pod -n datakit
采集器配置
ArgoCD 指标采集
datakit.yaml 修改 KubernetesPrometheus 采集配置。
mountPath 挂载把 KubernetesPrometheus 的配置文件挂载到容器内。
- mountPath: /usr/local/datakit/conf.d/kubernetesprometheus/kubernetesprometheus.confname: datakit-confsubPath: kubernetesprometheus.confreadOnly: true
添加 datakit.yaml 的 configmap 文件下添加 kubernetesprometheus.conf。
kubernetesprometheus.conf: |-[inputs.kubernetesprometheus][[inputs.kubernetesprometheus.instances]]role = "service"namespaces = ["argocd"]selector = "app.kubernetes.io/name=argocd-server-metrics"scrape = "true"scheme = "http"port = "__kubernetes_service_port_metrics_targetport"path = "/metrics"params = ""[inputs.kubernetesprometheus.instances.custom]measurement = "argocd-server"job_as_measurement = false[inputs.kubernetesprometheus.instances.custom.tags]svc_name = "__kubernetes_service_name"pod_name = "__kubernetes_service_target_name"pod_namespace = "__kubernetes_service_target_namespace"[[inputs.kubernetesprometheus.instances]]role = "service"namespaces = ["argocd"]selector = "aapp.kubernetes.io/name=argocd-metrics"scrape = "true"scheme = "http"port = "__kubernetes_service_port_metrics_targetport"path = "/metrics"params = ""[inputs.kubernetesprometheus.instances.custom]measurement = "argocd"job_as_measurement = false[inputs.kubernetesprometheus.instances.custom.tags]svc_name = "__kubernetes_service_name"pod_name = "__kubernetes_service_target_name"pod_namespace = "__kubernetes_service_target_namespace"[[inputs.kubernetesprometheus.instances]]role = "service"namespaces = ["argocd"]selector = "app.kubernetes.io/name=argocd-notifications-controller-metrics"scrape = "true"scheme = "http"port = "__kubernetes_service_port_metrics_targetport"path = "/metrics"params = ""[inputs.kubernetesprometheus.instances.custom]measurement = "argocd-application-controller"job_as_measurement = false[inputs.kubernetesprometheus.instances.custom.tags]svc_name = "__kubernetes_service_name"pod_name = "__kubernetes_service_target_name"pod_namespace = "__kubernetes_service_target_namespace"[inputs.kubernetesprometheus.global_tags]instance = "__kubernetes_mate_instance"host = "__kubernetes_mate_host"
- role ：填需要采集的负载的类型，比如 service，nodes，deployment，statefulset
- namespaces： 填对应的 ArgoCD 采集指标服务所在的空间
- selector： 填对应服务的label信息，或者 selector 信息
- port： ArgoCD 指标暴露的端口，这里默认不用改
- path：指标暴露的路径
- measurement： 自定义指标集名称
把 datakit.yaml 上传到可以连接到 Kubernetes 集群的主机上，执行如下命令。
kubectl apply -f datakit.yaml
kubectl get pod -n datakit
当看到状态是“Running”后表示安装 DataKit 成功。
ArgoCD 链路采集
修改 datakit.yaml 打开 opentelemetry 链路采集器。
apiVersion: v1
kind: ConfigMap
metadata:name: datakit-confnamespace: datakit
data:#### opentelemetryopentelemetry.conf: |-[[inputs.opentelemetry]][inputs.opentelemetry.http]enable = truehttp_status_ok = 200[inputs.opentelemetry.grpc]trace_enable = truemetric_enable = trueaddr = "0.0.0.0:4317"
apiVersion: apps/v1
kind: DaemonSet
metadata:labels:app: daemonset-datakitname: datakitnamespace: datakit
spec:...template:...spec:...containers:...volumeMounts:...- mountPath: /usr/local/datakit/conf.d/opentelemetry/opentelemetry.confname: datakit-confsubPath: opentelemetry.conf...
开启 datakit 服务 opentelemetry svc 的端口。
apiVersion: v1
kind: Service
metadata:name: datakit-servicenamespace: datakit
spec:selector:app: daemonset-datakitports:- name: datakitprotocol: TCPport: 9529targetPort: 9529- name: opentelemetryprotocol: TCPport: 4317targetPort: 4317
修改 Argo CD 的 ConfigMap argocd-cmd-params-cm，加入 otlp.address 地址，即可获取 Argo CD 的链路。
argocd-cmd-params-cm.yaml
apiVersion: v1
kind: ConfigMap
metadata:labels:app.kubernetes.io/name: argocd-cmd-params-cmapp.kubernetes.io/part-of: argocdname: argocd-cmd-params-cmnamespace: argocd
data:otlp.address: datakit-service.datakit:4317
执行命令：kubectl apply -f argocd-cmd-params-cm.yaml 然后重启 ArgoCD 服务即可。
ArgoCD 日志采集
DataKit 默认会采集容器的标准输出日志，无需额外配置采集。
关键指标
argocd-server
| Metric | Description |
|---|---|
| process_start_time_seconds | The start time of the process since unix epoch in seconds in the API Server |
| go_goroutines | The number of goroutines that currently exist in the API Server |
| grpc_server_handled_total | The total number of RPCs completed on the server regardless of success or failure |
| grpc_server_started_total | The total number of RPCs started on the server |
| go_memstats_alloc_bytes | The number of heap bytes allocated and still in use in the API Server |
argocd-application-controller
| Metric | Description |
|---|---|
| argocd_app_info | Information about Applications. It contains tags such as syncstatus and healthstatus that reflect the application state in Argo CD. The metric value is constant |
| go_memstats_heap_alloc_bytes | The number of heap bytes allocated and still in use in the Application Controller |
| process_cpu_seconds_total | The total user and system CPU time spent in seconds in the Application Controller |
| argocd_app_reconcile_count | Reconcile count |
| argocd_app_reconcile_bucket | Count of Application Reconciliation by Duration Bounds |
| workqueue_depth | Depth of the Workqueue |
| argocd_kubectl_exec_total | Count of Kubectl Executions |
| argocd_app_k8s_request_total | Count of Kubernetes Requests Executed |
| argocd_kubectl_exec_pending | Count of Pending Kubectl Executions |
argocd-repo-server
| Metric | Description |
|---|---|
| argocd_git_request_total | Count of Git Ls-Remote Requests |
| argocd_git_request_duration_seconds_bucket | Git Ls-Remote Requests Performance |
场景视图
监控器配置
ArgoCD 异常检测
window("M::argocd-server:(avg(argocd_info)) BY version", '5m')
