> tpl_cld_012
Kubernetes Readiness and Production Qualification
Production qualification scorecard and operational readiness checklist evaluating Kubernetes workload sizing (CPU/memory requests and limits), Pod Disruption Budgets (PDB), graceful termination, liveness/readiness probes, NetworkPolicies, Horizontal Pod Autoscaling (HPA), and admission controller governance.
Kubernetes production readiness scorecard evaluating workload sizing, PDBs, probes, network policies, autoscaling, and admission security.
Important Tech Document Template & Operational Notice
TinyCTO.tv Tech Document Template Notice: This template is a general educational and operational starting point. It is not legal, tax, accounting, investment, procurement, regulatory, security or certification advice. Requirements vary by jurisdiction, organization, contract and risk. Review and adapt it with qualified professionals before relying on it.
Problem Solved
Engineering teams deploy applications to Kubernetes without resource limits, missing liveness/readiness probes, and lacking Pod Disruption Budgets, leading to node cascading OOM-kills, zero-downtime deployment failures during node drains, and unrestricted cross-namespace lateral network movement.
When to Use
- •Conducting formal pre-production qualification audits for new containerized microservices deploying to EKS, GKE, or AKS
- •Auditing cluster-wide resilience configurations before high-traffic commercial launches or peak seasonal events
- •Verifying compliance against CNCF hardening guidelines, Pod Security Standards, and Kyverno/Gatekeeper admission policies
When NOT to Use
- •For overarching physical or cloud infrastructure provisioning via Terraform (use TPL-CLD-011)
- •For container image vulnerability scanning and software supply chain attestations (use TPL-SEC-015)
5 Template Sections & Structural Outline
Mandating non-zero CPU and memory requests and limits for every container. Establishing Guaranteed vs Burstable QoS classes to prevent noisy-neighbor starvation and runaway memory leaks triggering kernel OOM-killer.
Enforcing multi-replica deployments (minimum 3 pods across distinct AZs) combined with Pod Disruption Budgets (minAvailable: 2 or maxUnavailable: 25%) and topologySpreadConstraints to survive node drains and cluster upgrades.
Specifying calibrated startup, liveness, and readiness probes with realistic initial delays. Configuring preStop lifecycle hooks and SIGTERM terminationGracePeriodSeconds (minimum 30s) to drain in-flight HTTP requests.
Deploying default-deny ingress and egress NetworkPolicies per namespace. Restricting pod egress to required external FQDNs and internal database ports, preventing lateral movement in multi-tenant clusters.
Enforcing Pod Security Standards (restricted profile): runAsNonRoot, readOnlyRootFilesystem, drop ALL capabilities, allowPrivilegeEscalation: false. Validating automated Kyverno/Gatekeeper rejection of privileged containers.
Completion Instructions
Independent Review Checklist
- All mandatory sections completed
- No secrets or passwords included
- Executive sponsor sign-off obtained
Kubernetes Readiness and Production Qualification - Worked Case Study
Fictional Entity: Fintech Payments Platform (80+ Microservices on Managed AWS EKS Multi-AZ Cluster)
Real-world production case study demonstrating complete operational adoption for Fintech Payments Platform (80+ Microservices on Managed AWS EKS Multi-AZ Cluster).
- •Eliminated node drain downtime to 0 milliseconds by enforcing PDBs and 35-second preStop hooks
- •Prevented cascading OOM crashes across 12 worker nodes via calibrated memory limits and Guaranteed QoS
- •Enforced 100% compliance with CNCF Restricted Pod Security Standards across all production namespaces
Frequently Asked Questions
Why does missing a Pod Disruption Budget (PDB) cause outages during routine Kubernetes node upgrades?
When an automated node drain command executes during an AMI upgrade, Kubernetes terminates pods on that node. Without a PDB specifying minimum available replicas, the eviction controller can evict all replicas simultaneously before replacements become ready, causing an immediate service blackout.
Why should the readiness probe check internal dependencies while the liveness probe remains isolated?
If a liveness probe fails when an external database is sluggish, Kubernetes kills and restarts the pod. If every replica restarts simultaneously, the cluster enters an infinite crash loop. The readiness probe should handle traffic removal when dependencies are degraded, while the liveness probe strictly monitors internal deadlocks.
How do Horizontal Pod Autoscalers (HPA) and cluster autoscalers interact during sudden traffic spikes?
When an unexpected traffic spike occurs, HPA scales pod replicas based on CPU/memory utilization or custom metrics (e.g. queue depth). If the existing worker nodes lack sufficient capacity to schedule the new pods, they enter Pending state, which immediately triggers the cluster autoscaler (or Karpenter) to provision additional compute nodes within 45 to 90 seconds.
Download Tech Document Pack
Auth RequiredDownload all blank templates, worked scenarios, and verification manifests in a single verified archive.
Authoritative Sources
- Kubernetes Pod Security Standards (Baseline & Restricted Profiles)Kubernetes.io • OFFICIAL REQUIREMENT
- NSA / CISA Kubernetes Hardening Cybersecurity Technical ReportNSA / CISA • OFFICIAL REQUIREMENT
- CNCF Production Readiness & Reliability Best PracticesCloud Native Computing Foundation (CNCF) • OFFICIAL REQUIREMENT