#kubernetes

Implement GitOps workflow using ArgoCD. Setup: 1. Install ArgoCD on Kubernetes cluster. 2. Connect Git repository as source of truth. 3. Create Application manifests for each microservice. 4. Configure automated sync policies. 5. Set up health checks and sync waves. 6. Implement progressive delivery with Argo Rollouts (canary, blue-green). 7. RBAC for team access control. Use separate repos for app code and manifests. Include rollback procedures and disaster recovery plan.

Deploy Istio service mesh on Kubernetes. Features: 1. Automatic sidecar injection for traffic management. 2. Mutual TLS for service-to-service encryption. 3. Traffic routing (canary deployments, A/B testing). 4. Circuit breaking and retry policies. 5. Distributed tracing with Jaeger. 6. Service-level metrics and dashboards. 7. Ingress gateway for external traffic. Configure virtual services and destination rules. Use Kiali for visualization. Include performance impact analysis and troubleshooting guide.

Create production-ready Kubernetes manifests for a microservice. Resources: 1. Deployment with rolling update strategy and resource limits. 2. Service (ClusterIP) for internal communication. 3. Ingress with TLS termination. 4. ConfigMap for environment variables. 5. Secret for sensitive data. 6. HorizontalPodAutoscaler for auto-scaling. 7. PodDisruptionBudget for availability. Use namespaces, labels, and health checks (liveness/readiness probes). Include Helm chart structure for templating.

Implement zero-downtime deployments with Kubernetes. Setup: 1. Create blue and green deployment manifests with identical specs. 2. Configure service selector to route traffic between environments. 3. Implement health checks and readiness probes. 4. Set up Helm charts for version management. 5. Create CI/CD pipeline with automated testing gates. 6. Add rollback mechanism with previous version retention. 7. Implement traffic splitting for canary testing. 8. Monitor deployment metrics with Prometheus and Grafana. Include namespace isolation and resource quotas.

Deploy with Kubernetes. Concepts: 1. Pods as deployment units. 2. Deployments for replica management. 3. Services for networking. 4. ConfigMaps and Secrets for config. 5. Namespaces for isolation. 6. Ingress for HTTP routing. 7. Resource limits and requests. 8. Health and readiness probes. Use kubectl and YAML manifests. Implement rolling updates and rollbacks. Monitor with Prometheus.

Master Docker containerization for microservices with optimization and security best practices. Dockerfile optimization: 1. Multi-stage builds: separate build and runtime environments, reduce image size by 70-80%. 2. Base image selection: Alpine Linux for minimal footprint, distroless for security. 3. Layer caching: order instructions from least to most frequently changing. 4. Security practices: non-root user, minimal packages, vulnerability scanning. Container orchestration: 1. Docker Compose: local development, service dependencies, network configuration. 2. Production considerations: resource limits (CPU: 1 core, Memory: 512MB typical), health checks every 30 seconds. Image management: 1. Registry strategy: private registries for proprietary code, image tagging conventions (semantic versioning). 2. Security scanning: Trivy, Clair for vulnerability detection, policy enforcement. 3. Image optimization: .dockerignore files, multi-arch builds (AMD64, ARM64). Microservices patterns: 1. Service mesh: Istio/Linkerd for inter-service communication, observability. 2. API gateway: rate limiting, authentication, request routing. Monitoring: container metrics (CPU, memory, disk I/O), log aggregation, distributed tracing with Jaeger/Zipkin.

Generate the YAML for a basic Kubernetes Deployment and Service. The Deployment should run 3 replicas of the `nginx:alpine` image. The Service should expose the Nginx deployment on port 80 using a `ClusterIP`.

Deploy and manage applications on Kubernetes with advanced orchestration and scaling strategies. Cluster architecture: 1. Master nodes: API server, etcd, controller manager, scheduler (minimum 3 for HA). 2. Worker nodes: kubelet, kube-proxy, container runtime (Docker/containerd). 3. Networking: CNI plugins (Calico, Flannel), ingress controllers (NGINX, Traefik). Workload management: 1. Deployments: rolling updates with maxUnavailable: 25%, maxSurge: 25%. 2. StatefulSets: ordered deployment for databases, persistent volume claims. 3. DaemonSets: node-level services (log collectors, monitoring agents). 4. Jobs/CronJobs: batch processing, scheduled tasks with timezone support. Resource management: 1. Resource quotas: CPU/memory limits per namespace, prevent resource exhaustion. 2. Horizontal Pod Autoscaler: target CPU 70%, memory 80%, custom metrics scaling. 3. Vertical Pod Autoscaler: right-size resource requests based on usage patterns. Security practices: 1. RBAC: role-based access control, principle of least privilege. 2. Network policies: ingress/egress rules, microsegmentation. 3. Pod Security Standards: restricted profile, security contexts, read-only filesystems. Monitoring stack: Prometheus for metrics, Grafana for visualization, AlertManager for notifications, target 99.9% uptime.