Docker – Working of Kubernetes
Kubernetes orchestrates Docker containers by managing deployment, scaling, and operation across a cluster of machines. Understanding its working helps you deploy applications efficiently in production environments.
How Kubernetes Works with Docker
- Pods: Kubernetes runs Docker containers inside pods, the smallest deployable unit.
- Nodes: Worker nodes host pods and communicate with the master node.
- Master Node: Schedules pods, manages desired states, and monitors nodes.
- Deployments: Define desired state, scaling, and rolling updates for pods.
- Services: Expose pods internally or externally for networking and load balancing.
Pod Lifecycle
Pods go through phases: Pending, Running, Succeeded, Failed, and Unknown. Kubernetes continuously monitors pod status and restarts failed containers to maintain desired state.
Scaling and Load Balancing
- Kubernetes can automatically scale pods based on CPU, memory, or custom metrics.
- Services provide load balancing to distribute traffic across multiple pod instances.
- Horizontal Pod Autoscaler (HPA) manages dynamic scaling automatically.
Updating Applications
Kubernetes supports rolling updates, ensuring that new versions of applications are deployed without downtime. Failed updates can be rolled back to maintain stability.
Monitoring and Logging
- Kubernetes integrates with monitoring tools like Prometheus and Grafana.
- Centralized logging collects container logs for troubleshooting.
- Alerts can be configured to detect anomalies and failures.
Conclusion
Kubernetes works seamlessly with Docker to automate container orchestration. By managing pods, deployments, services, and scaling, it ensures applications run efficiently, reliably, and with minimal manual intervention in production environments.
