Kubernetes Production Readiness: The Complete Checklist

Moving Kubernetes workloads from development to production requires careful planning and systematic validation across multiple domains. This checklist represents learnings from managing dozens of production Kubernetes clusters across different organizations and cloud providers.

Use this as a comprehensive guide to ensure your Kubernetes environment is truly production-ready, not just “it works on my machine” ready.

Infrastructure Foundation

Cluster Architecture

• Multi-zone deployment with node distribution across availability zones
• Separate node pools for different workload types (system, application, data)
• Right-sized nodes based on workload requirements and cost optimization
• Auto-scaling configured with appropriate min/max limits and scale-down policies
• Network policies implemented for micro-segmentation between namespaces
• Pod security policies or Pod Security Standards configured and enforced

High Availability

• Control plane HA with multiple master nodes (managed or self-hosted)
• etcd backup strategy with automated, tested restore procedures
• Network redundancy with multiple ingress points and load balancers
• DNS redundancy with backup DNS servers configured
• Cross-region disaster recovery plan documented and tested

Security Hardening

Authentication & Authorization

• RBAC enabled with principle of least privilege
• Service accounts properly configured with minimal permissions
• Pod security contexts defined with non-root users and read-only filesystems
• Network policies restricting inter-pod communication
• API server security with audit logging and admission controllers

Secrets Management

• External secrets management (HashiCorp Vault, AWS Secrets Manager, etc.)
• Secret rotation automated and tested
• Encryption at rest enabled for etcd
• Image scanning integrated into CI/CD pipeline
• Container runtime security (gVisor, Kata Containers, or similar)

Image Security

• Base image hardening with minimal attack surface
• Image vulnerability scanning in CI/CD pipeline
• Image signing and verification (Cosign, Notary, etc.)
• Private container registry with access controls
• Runtime security monitoring (Falco, Sysdig, etc.)

Monitoring & Observability

Metrics Collection

• Prometheus deployed with persistent storage and HA configuration
• Node metrics collected (node-exporter)
• Cluster metrics monitored (kube-state-metrics)
• Application metrics instrumented and scraped
• Custom metrics for business KPIs and SLIs

Logging Infrastructure

• Centralized logging (ELK, Fluentd, Loki)
• Log aggregation from all nodes and pods
• Log retention policies defined and implemented
• Structured logging enforced across applications
• Log analysis and alerting capabilities

Distributed Tracing

• Tracing system deployed (Jaeger, Zipkin, etc.)
• Application instrumentation for distributed tracing
• Service mesh integration if applicable
• Performance monitoring and bottleneck identification
• Error tracking and analysis

Alerting & Incident Response

• Alert manager configured with proper routing
• SLI/SLO definitions for critical services
• Runbooks documented for common scenarios
• On-call rotation established with escalation procedures
• Incident response procedures documented and practiced

Networking & Service Mesh

Network Configuration

• CNI plugin properly configured (Calico, Cilium, etc.)
• Ingress controller with SSL/TLS termination
• Load balancer configuration optimized
• DNS configuration with proper search domains
• Network performance tested under load

Service Discovery & Communication

• Service mesh evaluated and deployed if needed (Istio, Linkerd, etc.)
• mTLS configured for service-to-service communication
• Circuit breakers and retry policies implemented
• Rate limiting configured at ingress and service levels
• API gateway for external traffic if applicable

Storage & Data Management

Persistent Storage

• Storage classes defined for different performance tiers
• Volume provisioning automated with CSI drivers
• Backup strategy for persistent volumes implemented
• Disaster recovery procedures for stateful workloads
• Storage monitoring and capacity planning

Database Management

• Database operators deployed for stateful services (if applicable)
• Backup automation with tested restore procedures
• High availability configuration for databases
• Performance monitoring and optimization
• Security hardening for database access

Application Deployment & Management

Deployment Strategies

• Rolling deployment configured with proper readiness/liveness probes
• Blue-green deployment capability if needed
• Canary deployment process defined
• Rollback procedures automated and tested
• Resource quotas and limits properly configured

Configuration Management

• ConfigMaps and Secrets properly managed
• Environment-specific configurations handled
• Configuration drift detection and remediation
• GitOps workflow implemented (ArgoCD, Flux, etc.)
• Immutable infrastructure principles followed

Resource Management

• Resource requests and limits defined for all containers
• Quality of Service classes properly assigned
• Horizontal Pod Autoscaling configured where appropriate
• Vertical Pod Autoscaling evaluated and configured if beneficial
• Pod disruption budgets defined for critical services

Operational Procedures

Backup & Recovery

• Cluster backup strategy (etcd, manifests, configurations)
• Application data backup automated and tested
• Disaster recovery runbooks documented and practiced
• RTO/RPO requirements defined and validated
• Cross-region failover procedures tested

Maintenance & Updates

• Cluster upgrade strategy defined and tested
• Node maintenance procedures with workload migration
• Security patching automated where possible
• Capacity planning based on growth projections
• Cost optimization regular reviews and actions

Documentation & Training

• Architecture documentation complete and current
• Operational runbooks for common tasks
• Troubleshooting guides for known issues
• Training materials for new team members
• Emergency contact lists and escalation procedures

Performance & Cost Optimization

Performance Tuning

• Resource allocation optimized based on actual usage
• Network performance tuned for workload requirements
• Storage performance optimized for access patterns
• Application performance profiled and optimized
• Load testing conducted under realistic conditions

Cost Management

• Resource utilization monitoring and optimization
• Right-sizing of nodes and workloads
• Spot instances utilized where appropriate
• Cost allocation and chargeback mechanisms
• Budget alerts and automated cost controls

Compliance & Governance

Policy Enforcement

• Admission controllers configured for policy enforcement
• Security scanning integrated into CI/CD pipeline
• Compliance reporting automated where possible
• Audit logging comprehensive and retained appropriately
• Change management processes integrated with deployments

Data Protection

• Data encryption at rest and in transit
• Data classification and handling procedures
• Privacy controls for sensitive data
• Data retention policies implemented
• Right to be forgotten capabilities if required

Pre-Production Validation

Testing Strategy

• Load testing at expected production scale
• Chaos engineering experiments conducted
• Failure scenarios tested and validated
• Performance benchmarks established
• Security penetration testing completed

Go-Live Readiness

• Team training completed for all operational procedures
• Support processes established and tested
• Monitoring dashboards configured and validated
• Alert fatigue minimized with proper alert tuning
• Launch plan documented with rollback procedures

Conclusion

Production readiness for Kubernetes is not a one-time effort but an ongoing process of validation, monitoring, and improvement. This checklist provides a comprehensive framework, but your specific requirements may vary based on your organization’s needs, compliance requirements, and risk tolerance.

Remember that production readiness is ultimately about confidence—confidence that your system will perform as expected, that you can detect and respond to issues quickly, and that you can recover from failures gracefully.

Start with the foundational elements (infrastructure, security, monitoring) and build up to the more advanced capabilities. Regular reviews and updates to your production readiness criteria ensure your Kubernetes environment evolves with your organization’s needs.