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Powered by GitBook
On this page
  • Managed Kubernetes Services
  • Real-Life Workload Examples
  • 2025 Best Practices
  • Example: Deploying a Web App to Kubernetes
  • Multi-Cloud & Hybrid Kubernetes
  • Related Topics
  • References
Edit on GitHub
  1. Containers & Orchestration
  2. Containerization Overview

Kubernetes

Kubernetes is the leading open-source platform for automating deployment, scaling, and management of containerized applications. It is supported by all major cloud providers and can run on-premises, in the cloud, or in hybrid environments.

Managed Kubernetes Services

Most organizations use a managed Kubernetes service for production workloads. The three most popular are:

  • AKS (Azure Kubernetes Service): Managed by Microsoft Azure, integrates with Azure AD, Azure Monitor, and supports Windows and Linux nodes.

  • EKS (Amazon Elastic Kubernetes Service): Managed by AWS, integrates with IAM, CloudWatch, and supports deep AWS ecosystem integration.

  • GKE (Google Kubernetes Engine): Managed by Google Cloud, offers advanced auto-scaling, rapid upgrades, and native Anthos/multi-cloud support.

Feature
AKS
EKS
GKE

Cloud Provider

Azure

AWS

GCP

OS Support

Linux, Windows

Linux, Windows

Linux

IAM Integration

Azure AD

AWS IAM

Google IAM

Monitoring

Azure Monitor

CloudWatch

Stackdriver

Auto-Scaling

Yes

Yes

Advanced

Upgrades

Manual/Auto

Manual/Auto

Rapid/Auto

Multi-Cloud/Hybrid

Azure Arc

EKS Anywhere

Anthos

Real-Life Workload Examples

  • Web Applications: Deploy scalable web frontends and APIs using Kubernetes Deployments and Services.

  • Big Data & Analytics: Run Spark, Hadoop, or distributed data processing jobs on Kubernetes clusters.

  • Machine Learning: Train and serve ML models using Kubeflow, MLflow, or custom containers.

  • CI/CD Pipelines: Use Kubernetes for dynamic build/test environments and GitOps workflows.

2025 Best Practices

  • Use Infrastructure as Code (Terraform, Bicep) to provision clusters and resources

  • Integrate with cloud-native IAM for secure access (Azure AD, AWS IAM, Google IAM)

  • Automate deployments with GitHub Actions, Azure Pipelines, or GitLab CI/CD

  • Use Helm for application packaging and versioning

  • Enable cluster auto-scaling and node pool management

  • Monitor with Prometheus, Grafana, and cloud-native tools

  • Secure workloads with network policies, RBAC, and secrets management

  • Use LLMs (Copilot, Claude) to generate manifests, Helm charts, and automate troubleshooting

Example: Deploying a Web App to Kubernetes

apiVersion: apps/v1
kind: Deployment
metadata:
  name: webapp
spec:
  replicas: 3
  selector:
    matchLabels:
      app: webapp
  template:
    metadata:
      labels:
        app: webapp
    spec:
      containers:
      - name: webapp
        image: nginx:1.25
        ports:
        - containerPort: 80
---
apiVersion: v1
kind: Service
metadata:
  name: webapp
spec:
  selector:
    app: webapp
  ports:
    - protocol: TCP
      port: 80
      targetPort: 80
  type: LoadBalancer

Multi-Cloud & Hybrid Kubernetes

  • Use tools like Azure Arc, EKS Anywhere, or Anthos for hybrid/multi-cloud management

  • Standardize on GitOps and IaC for portability

  • Monitor and secure clusters consistently across providers

Related Topics

References

PreviousDocker ComposeNextCLI Tools - Essential command-line utilities

Last updated 19 days ago

- Container runtime used by Kubernetes

- Primary CLI tool for managing Kubernetes

- Advanced networking for Kubernetes

- Securing your Kubernetes clusters

- Continuous deployment to Kubernetes

- Solving common Kubernetes problems

🐳
Docker
Kubectl
Service Mesh
Kubernetes Security
GitOps with Flux
Troubleshooting
Kubernetes Official Docs
AKS Documentation
EKS Documentation
GKE Documentation