Monitoring Cilium in production involves a series of steps that ensure visibility, performance, and operational health of the Kubernetes environment. This documentation outlines the key components and provides comprehensive code examples for effective monitoring using Cilium’s capabilities.

Overview

Cilium leverages eBPF technology for observability, enabling the extraction of metrics and insights with minimal overhead. Its architecture allows for seamless integration with existing monitoring systems, primarily through Prometheus and Grafana.

Step 1: Setting Up Metrics Exporting

Cilium supports the exportation of metrics which can be ingested by Prometheus. This is critical for monitoring the performance and health of services running within the Kubernetes cluster.

Code Example for Metrics Exporter

The following code snippet outlines how to configure a metrics exporter in a Cilium environment:

const ciliumMetricsConfig = {
  apiVersion: 'v1',
  kind: 'ServiceMonitor',
  metadata: {
    name: 'cilium-metrics',
    labels: {
      app: 'cilium',
    },
  },
  spec: {
    selector: {
      matchLabels: {
        app: 'cilium',
      },
    },
    endpoints: [
      {
        port: 'metrics',
        interval: '30s',
      },
    ],
  },
};

This configuration sets up a Kubernetes ServiceMonitor that periodically scrapes metrics from Cilium’s metrics endpoint.

Step 2: Integrating with Prometheus

Cilium exposes various metrics that can be used for monitoring. To visualize these metrics, integrate Prometheus with your Kubernetes cluster.

Prometheus Deployment Example

Here’s an example YAML file for deploying Prometheus and connecting it with Cilium:

apiVersion: v1
kind: Service
metadata:
  name: prometheus
  labels:
    app: prometheus
spec:
  ports:
    - port: 9090
  selector:
    app: prometheus
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: prometheus
spec:
  replicas: 1
  selector:
    matchLabels:
      app: prometheus
  template:
    metadata:
      labels:
        app: prometheus
    spec:
      containers:
        - name: prometheus
          image: prom/prometheus
          args: ['--config.file=/etc/prometheus/prometheus.yml']
          ports:
            - containerPort: 9090
          volumeMounts:
            - name: config-volume
              mountPath: /etc/prometheus
      volumes:
        - name: config-volume
          configMap:
            name: prometheus-config

Ensure the Prometheus configuration file includes Cilium metrics endpoint.

Step 3: Utilizing Grafana for Visualization

Once Prometheus is configured, Grafana can be set up for a better visualization of metrics collected from Cilium.

Grafana Setup Example

An example of setting up Grafana to visualize Cilium metrics:

apiVersion: v1
kind: Service
metadata:
  name: grafana
  labels:
    app: grafana
spec:
  ports:
    - port: 3000
  selector:
    app: grafana
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: grafana
spec:
  replicas: 1
  selector:
    matchLabels:
      app: grafana
  template:
    metadata:
      labels:
        app: grafana
    spec:
      containers:
        - name: grafana
          image: grafana/grafana
          ports:
            - containerPort: 3000

Access the Grafana UI and configure data sources to connect to your Prometheus instance.

Step 4: Monitoring and Alerts

Cilium offers built-in health checks and status overviews, which can be monitored through the integrated Prometheus and Grafana setup. Alerts can also be configured based on the metrics exported.

Alert Configuration Example

An example of an alert rule in Prometheus for monitoring Cilium connectivity issues:

groups:
  - name: cilium-alerts
    rules:
      - alert: CiliumConnectivityIssues
        expr: sum(irate(cilium_cluster_connectivity_latency[5m])) > 100
        for: 10m
        labels:
          severity: critical
        annotations:
          summary: "High Latency in Cilium Connectivity"
          description: "Investigate high latency detected in Cilium connectivity over the last 10 minutes."

This alert triggers if the latency exceeds 100 milliseconds for an extended period.

Conclusion

By following these steps, production engineers can effectively monitor Cilium deployments, ensuring high availability and performance in their Kubernetes environments. This integration facilitates the identification of potential issues before they impact services, allowing for proactive incident management.

Source: Information is derived from the official Cilium documentation and articles related to observability, monitoring setups, Prometheus integration, and Grafana usage.