Kubernetes - Built-in Metrics

Introduction

Understanding built-in Kubernetes metrics is essential for monitoring the health and performance of your clusters. This guide provides an intermediate-level overview of the built-in metrics available in Kubernetes, covering their usage and how to access them.

Types of Built-in Metrics

Kubernetes provides several built-in metrics categorized into different types:

• Node Metrics: Metrics related to the health and performance of nodes.
• Pod Metrics: Metrics related to the health and performance of pods.
• Container Metrics: Metrics related to the resource usage of containers.
• Namespace Metrics: Aggregated metrics at the namespace level.
• Cluster Metrics: Overall metrics for the entire cluster.

Accessing Built-in Metrics

You can access built-in metrics using kubectl or by setting up monitoring tools that integrate with Kubernetes.

Using kubectl top

The kubectl top command provides a way to view resource usage metrics. Ensure the Metrics Server is installed in your cluster.

# Install Metrics Server (if not already installed)
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml

# View node metrics
kubectl top nodes

# View pod metrics
kubectl top pods --all-namespaces

# View container metrics in a specific pod
kubectl top pod  --containers
                

Using the Metrics API

The Metrics API provides programmatic access to metrics data. Here’s how you can use it:

# Get node metrics using the Metrics API
kubectl get --raw "/apis/metrics.k8s.io/v1beta1/nodes"

# Get pod metrics using the Metrics API
kubectl get --raw "/apis/metrics.k8s.io/v1beta1/namespaces/default/pods"
                

Common Metrics and Their Usage

Here are some common metrics and how they can be used:

• CPU Usage: Monitor CPU usage to ensure nodes and pods have sufficient CPU resources.
• Memory Usage: Monitor memory usage to prevent memory exhaustion and ensure smooth operation.
• Disk I/O: Monitor disk I/O to detect bottlenecks and ensure storage performance.
• Network I/O: Monitor network I/O to detect network issues and ensure communication between components.

Using Monitoring Tools

In addition to built-in metrics, you can use monitoring tools like Prometheus and Grafana to collect, store, and visualize metrics data.

Setting Up Prometheus

# Install Prometheus using Helm
helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
helm repo update
helm install prometheus prometheus-community/prometheus

# Access the Prometheus UI
kubectl port-forward svc/prometheus-server 9090:80
                

Setting Up Grafana

# Install Grafana using Helm
helm repo add grafana https://grafana.github.io/helm-charts
helm repo update
helm install grafana grafana/grafana

# Access the Grafana UI
kubectl port-forward svc/grafana 3000:80

# Add Prometheus as a data source in Grafana and create dashboards to visualize metrics
                

Best Practices for Monitoring with Built-in Metrics

• Regular Monitoring: Continuously monitor metrics to detect and resolve issues proactively.
• Set Alerts: Configure alerts for critical metrics to get notified of potential issues.
• Analyze Trends: Use metrics to analyze trends and plan for resource scaling.
• Integrate with Tools: Integrate built-in metrics with monitoring tools for better visibility and analysis.
• Keep Metrics Server Updated: Ensure the Metrics Server and other components are updated to the latest versions for accurate and efficient monitoring.

Conclusion

Understanding and utilizing built-in Kubernetes metrics is essential for maintaining the health and performance of your clusters. By following the steps and best practices outlined in this guide, you can effectively monitor your Kubernetes environment and ensure its smooth operation.