Kubernetes

Kubernetes

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Kubernetes (often abbreviated as K8s) is an open-source container orchestration platform designed to automate the deployment, scaling, and management of containerized applications. It was originally developed by Google and is now maintained by the Cloud Native Computing Foundation (CNCF).

Key Features of Kubernetes

  1. Container Orchestration

    • Manages the lifecycle of containers (e.g., Docker, containerd) across multiple hosts.

    • Ensures high availability and fault tolerance.

  2. Automated Scaling

    • Scales applications up or down based on demand (Horizontal & Vertical Scaling).

    • Supports Horizontal Pod Autoscaler (HPA) and Cluster Autoscaler.

  3. Self-Healing

    • Automatically restarts failed containers, replaces unresponsive pods and reschedules workloads.

  4. Service Discovery & Load Balancing

    • Assigns DNS names and IP addresses to containers.

    • Distributes network traffic using Ingress Controllers and Services.

  5. Declarative Configuration

    • Uses YAML/JSON manifests to define the desired state of the system.

    • Kubernetes continuously works to match the actual state with the desired state.

  6. Multi-Cloud & Hybrid Support

    • Runs on AWS, GCP, Azure, On Premises and Edge environments.

    • Supports Kubernetes Federation for multi-cluster management.

  7. Extensible & Modular

    • Supports Custom Resource Definitions (CRDs) and Operators for extending functionality.

    • Integrates with CI/CD pipelines, monitoring (Prometheus), logging (ELK) and service meshes (Istio, Linkerd).

Kubernetes Tools & Ecosystem

  • kubectl: CLI tool for managing clusters.

  • Helm: Package manager for Kubernetes (charts).

  • Minikube/ Kind: Local Kubernetes clusters.

  • K9s: Terminal-based UI.

  • ArgoCD/Flux: GitOps based deployment.

  • Prometheus + Grafana: Monitoring.

  • Istio/Linkerd: Service mesh.

Use Cases of Kubernetes

  • Microservices: Manages hundreds of interconnected services.

  • CI/CD Pipelines: Automates deployments (Jenkins, GitLab CI).

  • Big Data & ML: Runs distributed workloads (Spark, TensorFlow).

  • Hybrid & Multi Cloud: Avoids vendor lock in.

  • Edge Computing: Deploys lightweight clusters (K3s, MicroK8s).

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