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Docker best practices

  1. Dockerfile Optimization

    • Use multi-stage builds to reduce image size.
    • Choose minimal base images (e.g., alpine, scratch).
    • Combine commands to reduce the number of layers.
    • Clean up temporary files and package manager caches.

  2. Security

    • Run containers with a non-root user.
    • Regularly update base images to include security patches.
    • Use Docker Bench for Security to audit your Docker setup.
    • Limit container capabilities using the --cap-drop and --cap-add flags.

  3. Runtime Efficiency

    • Use resource limits (--memory, --cpus) to prevent resource exhaustion.
    • Leverage Docker Compose for managing multi-container applications.
    • Use health checks to monitor container status.

  4. Networking

    • Use user-defined networks for better isolation and communication between containers.
    • Avoid using the host network mode unless absolutely necessary.

  5. Volume Management

    • Use named volumes for persistent data storage.
    • Regularly back up important data stored in volumes.

  6. Logging and Monitoring

    • Use centralized logging solutions (e.g., ELK stack, Fluentd).
    • Monitor container performance using tools like Prometheus and Grafana.

  7. Image Management

    • Regularly clean up unused images, containers, and volumes using docker system prune.
    • Tag images appropriately for versioning and rollback purposes.

  8. Documentation

    • Maintain clear and concise documentation for Dockerfiles and deployment processes.
    • Use comments in Dockerfiles to explain non-obvious instructions.

Kubernetes best practices

  1. Cluster Design
    • Use namespaces to isolate different environments (e.g., dev, staging, production).
    • Implement role-based access control (RBAC) for secure access management.
    • Use labels and annotations for better resource organization and management.
  2. Resource Management
    • Define resource requests and limits for CPU and memory in pod specifications.
    • Use Horizontal Pod Autoscaler (HPA) to automatically scale pods based on demand.
    • Monitor resource usage and adjust allocations as needed.
  3. Networking
    • Use Network Policies to control traffic between pods.
    • Implement service meshes (e.g., Istio, Linkerd) for advanced traffic management.
  4. Storage
    • Use Persistent Volumes (PVs) and Persistent Volume Claims (PVCs) for stateful applications.
    • Choose appropriate storage classes based on performance and availability requirements.
  5. Deployment Strategies
    • Use rolling updates for zero-downtime deployments.
    • Implement canary deployments for testing new versions with a subset of users.
    • Use Helm charts for managing complex applications and dependencies.
  6. Monitoring and Logging
    • Use centralized logging solutions (e.g., EFK stack, Loki).
    • Monitor cluster health and performance using tools like Prometheus and Grafana.
    • Set up alerts for critical events and resource thresholds.
  7. Security
    • Regularly update Kubernetes components to the latest stable versions.
    • Use Pod Security Policies (PSPs) or Open Policy Agent (OPA) for enforcing security standards.
    • Scan container images for vulnerabilities before deployment.
  8. Backup and Disaster Recovery
    • Regularly back up etcd data and cluster configurations.
    • Test disaster recovery procedures to ensure data integrity and availability.
  9. Documentation
    • Maintain clear documentation for cluster architecture, deployment processes, and operational procedures.
    • Use comments in YAML manifests to explain configurations and choices.
    • Keep an updated runbook for incident response and troubleshooting.