Building an observability platform for Kubernetes using CNCF (Cloud Native Computing Foundation) open-source projects is a great approach to ensuring your cloud-native applications are scalable, reliable, and easy to troubleshoot. Observability platforms typically focus on three pillars: metrics, logs, and traces, providing insights into the health, performance, and behaviour of your Kubernetes clusters and applications.
Here is a step-by-step guide to building an observability platform for Kubernetes using CNCF open-source tools:
1. Metrics Collection with Prometheus
Prometheus is a leading open-source monitoring solution from CNCF, known for scraping metrics from services running in a Kubernetes cluster.
Steps:
Install Prometheus Operator: The Prometheus Operator simplifies the deployment and configuration of Prometheus on Kubernetes.
kubectl apply -f https://github.com/prometheus-operator/ prometheus-operator/blob/main/bundle.yamlConfigure Service Monitors: Prometheus collects metrics by scraping endpoints. You need to create ServiceMonitors to tell Prometheus which services to scrape. The Prometheus Operator manages this for you.
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
name: my-app-metrics
spec:
selector:
matchLabels:
app: my-app
endpoints:
- port: metrics
Visualize Metrics with Grafana: Use Grafana to create dashboards for visualizing the metrics scraped by Prometheus. Install Grafana via Helm:
helm install grafana grafana/grafana
Connect Grafana to Prometheus and create customized dashboards for various components.
2. Log Aggregation with Fluentd and Loki
Logs provide detailed information about the system's events. Fluentd is the de-facto CNCF log aggregator, and Loki from Grafana Labs is a CNCF project designed for log aggregation in Kubernetes environments.
Steps:
Install Fluentd: Fluentd collects, processes, and forwards logs from your Kubernetes nodes and applications.
helm install fluentd stable/fluentd
Configure Fluentd to collect logs from Kubernetes pods and services.
Install Loki: Loki stores logs efficiently by indexing only metadata. It works seamlessly with Prometheus and Grafana.
helm repo add grafana https://grafana.github.io/helm-charts
helm install loki grafana/loki-stack
Integrate with Grafana: Add Loki as a data source in Grafana for querying logs in conjunction with metrics from Prometheus.
3. Distributed Tracing with Jaeger
Tracing helps with understanding the flow of requests across microservices. Jaeger is a CNCF project for distributed tracing, making it easier to debug and monitor complex, microservice-based applications.
Steps:
Install Jaeger Operator: The Jaeger Operator simplifies the deployment and management of Jaeger on Kubernetes.
kubectl create -f https://github.com/jaegertracing/jaeger-operator/ releases/download/v1.22.1/jaeger-operator.yaml
Deploy a Jaeger instance by applying the following custom resource:
apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
name: simple-prod
spec:
strategy: production
Instrument Applications: Use OpenTelemetry SDK to instrument your applications. OpenTelemetry is another CNCF project for telemetry data collection. Make sure your microservices export traces compatible with Jaeger.
Visualize Traces in Jaeger: Jaeger’s UI allows you to visualize traces, which helps in analyzing request flow across services. You can also integrate Jaeger with Grafana for centralized visualization.
4. Kubernetes Cluster Monitoring with Prometheus and Node Exporter
Kubernetes metrics such as CPU, memory, and disk usage from nodes and pods are critical for monitoring the cluster health.
Steps:
Install Kubernetes Metrics Server: The Metrics Server collects resource metrics from Kubernetes nodes and pods. Install it with:
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/ releases/latest/download/components.yamlInstall Node Exporter: Prometheus Node Exporter is used to collect hardware and OS-level metrics from Kubernetes nodes.
helm install node-exporter prometheus/node-exporter
The Node Exporter metrics will be scraped by Prometheus and can be visualized in Grafana.
5. Alerting and Notifications with Alertmanager
Prometheus has a built-in component called Alertmanager to handle alerts based on predefined rules.
Steps:
Set up Prometheus Alerts: Configure alerting rules in Prometheus. For example, you can set an alert for high CPU usage:
Groups:
- name: example-alert
rules:
- alert: HighCpuUsage
expr: node_cpu_seconds_total > 80
for: 1m
labels:
severity: warning
annotations:
summary: "High CPU usage detected"
Configure Alertmanager: Set up Alertmanager to handle alerts and send notifications via channels like Slack, email, or PagerDuty.
Receivers:
- name: 'slack-notifications'
slack_configs:
- send_resolved: true
channel: '#alerts'
username: 'prometheus'
api_url: '<slack-webhook-url>'
6. Visualization and Centralized Dashboards with Grafana
Grafana acts as a centralized hub for visualizing metrics, logs, and traces from Prometheus, Loki, and Jaeger.
Steps:
Create Dashboards: Use pre-built Grafana dashboards from the Grafana dashboard library, or build custom dashboards based on your metrics and traces.
Monitor Across Metrics, Logs, and Traces: Grafana allows you to correlate metrics, logs, and traces in a single interface. You can drill down from a metric anomaly to related logs and traces, making it easier to debug issues.
Optional CNCF Tools:
KubeStateMetrics: This tool provides detailed metrics about Kubernetes objects (such as Deployments, DaemonSets, etc.), which Prometheus scrapes.
Thanos: For long-term storage of Prometheus metrics and a global view of multiple Prometheus instances.
OpenTelemetry: For unified collection of telemetry data across metrics, logs, and traces in Kubernetes.
Final Architecture Overview:
Prometheus for metrics collection, scraping data from Kubernetes and applications.
Fluentd and Loki for log aggregation and query.
Jaeger for distributed tracing.
Grafana as the unified interface to visualize and correlate metrics, logs, and traces.
Alertmanager for alerting and notification.
This setup ensures you have complete observability into your Kubernetes clusters and applications, leveraging CNCF open-source tools.