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Kubernetes Production Mastery

Platform Engineering Playbook Course​

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Presenter: Production Engineering Instructor Total Duration: 10 episodes, ~2.5 hours total Target Audience: Senior platform engineers, SREs, DevOps engineers with 5+ years experience Difficulty: Intermediate to Advanced

Course Overview​

You know Kubernetes basics—Pods, Deployments, Services. You've followed tutorials and deployed to development clusters. But here's the reality: 98% of organizations face challenges running Kubernetes in production. Not development. Production.

This course bridges the gap between "it works on my laptop" and "it works at scale under load with real users." We cover the complete production operations toolkit: failure pattern prevention, stateful workloads, observability, security, cost optimization, and GitOps automation.

Through 10 focused episodes, you'll learn systematic debugging workflows, production-ready configurations, and decision frameworks used by senior engineers managing 20+ clusters in production environments.

What You'll Learn​

By the end of this course, you'll be able to:

  • Diagnose and prevent the 5 most common Kubernetes production failures
  • Debug systematically: OOMKilled, CrashLoopBackOff, ImagePullBackOff, networking, storage issues
  • Secure production clusters with RBAC best practices and secrets management (Sealed Secrets, External Secrets)
  • Deploy stateful workloads: Databases, caches, and message queues with StatefulSets and persistent storage
  • Build observability stack: Prometheus metrics, log aggregation, actionable alerts using golden signals
  • Implement GitOps: Deployment automation with ArgoCD or Flux, Helm vs Kustomize decision-making
  • Optimize costs: FinOps techniques for resource right-sizing and waste elimination
  • Operate at scale: Multi-cluster management patterns for 20+ cluster environments

Prerequisites​

Before starting this course, you should have:

  • Basic Kubernetes knowledge (Pods, Deployments, Services, kubectl)
  • Docker container experience
  • Production engineering or SRE experience (5+ years recommended)
  • Familiarity with command-line tools

Time Commitment​

  • Total Duration: ~2.5 hours (10 episodes × 12-18 min average)
  • Recommended Pace: 2-3 episodes per week
  • Completion Time: 3-4 weeks at recommended pace

Course Curriculum​

Module 1: Foundation (Episode 1)​

Build the production engineering mindset that separates development from production operations.

📖 Episode 1: Production Mindset - From Dev to Production​

Duration: 12 min • 📝 Transcript

Learn about:

  • The critical shift from development to production thinking
  • 5 production failure patterns that don't appear in tutorials
  • The 6-item production readiness checklist
  • Rapid Kubernetes basics refresher for experienced engineers

Module 2: Core Production Patterns (Episodes 2-7)​

Master production operations foundations through systematic approaches to resource management, security, troubleshooting, storage, networking, and observability.

📖 Episode 2: Resource Management - Preventing OOMKilled​

Duration: 15 min • 📝 Transcript

Learn about:

  • Understanding resource requests vs limits (and why both matter)
  • Debugging OOMKilled errors from symptoms to root cause
  • Quality of Service (QoS) classes and their impact
  • Right-sizing strategies using load testing and capacity planning

📖 Episode 3: Security Foundations - RBAC & Secrets​

Duration: 18 min • 📝 Transcript: Coming Soon

Learn about:

  • Why RBAC is the #1 Kubernetes security misconfiguration
  • Implementing namespace-scoped roles with least privilege
  • Service account security (avoiding token abuse and wildcards)
  • Secrets management with Sealed Secrets and External Secrets Operator
  • Common RBAC attack patterns and how to prevent them

📖 Episode 4: Troubleshooting Crashes - CrashLoopBackOff & Beyond​

Duration: 15 min • 📝 Transcript

Learn about:

  • Systematic troubleshooting workflow: describe → logs → events
  • Debugging CrashLoopBackOff, ImagePullBackOff, Pending pods
  • Configuring effective health checks (liveness, readiness, startup probes)
  • Understanding exit codes and backoff patterns
  • Building team runbooks for common failure scenarios

📖 Episode 5: StatefulSets & Persistent Storage​

Duration: 15 min • 📝 Transcript

Learn about:

  • When to use StatefulSets vs Deployments (decision framework)
  • Storage architecture: PV, PVC, Storage Classes, CSI drivers
  • Diagnosing storage failures (PVC stuck pending, volume not mounting)
  • Backup strategies with Velero
  • Database operator patterns for production workloads

📖 Episode 6: Networking & Ingress​

Duration: 18 min • 📝 Transcript

Learn about:

  • Kubernetes networking model (flat namespace, L4 vs L7)
  • CNI plugins: what they do and when they break (Calico, Cilium, Flannel)
  • Service types decision matrix (ClusterIP, NodePort, LoadBalancer)
  • Ingress controllers (Nginx, Traefik) and TLS termination with cert-manager
  • When you need a service mesh (and when you don't)
  • Network policies for production isolation

📖 Episode 7: Observability - Metrics, Logging, Tracing​

Duration: 15 min • 📝 Transcript

Learn about:

  • Deploying production-ready Prometheus (persistent storage, federation, security)
  • PromQL basics for troubleshooting workloads
  • Log aggregation architecture (Loki, Fluentd, structured logging)
  • Designing actionable alerts using golden signals (latency, traffic, errors, saturation)
  • When to use metrics vs logs vs traces for debugging

Module 3: Operations at Scale (Episodes 8-10)​

Synthesize operations foundations and scale to multi-cluster production environments with cost optimization, GitOps automation, and fleet management.

📖 Episode 8: Cost Optimization at Scale​

Duration: 12 min • 📝 Transcript

Learn about:

  • Why Kubernetes costs spiral (the 20+ cluster problem)
  • The 5 primary sources of cost waste in production
  • Right-sizing strategies using FinOps principles and VPA
  • Cost controls: namespace quotas, LimitRanges, cluster autoscaling
  • Spot instances for batch workloads
  • The "senior engineer problem" (over-engineering costs)

📖 Episode 9: GitOps & Deployment Automation​

Duration: 15 min • 📝 Transcript

Learn about:

  • GitOps principles: Git as source of truth, declarative config, automated sync
  • ArgoCD vs Flux decision framework (when to use which)
  • Helm vs Kustomize for configuration management
  • Deployment strategies beyond rolling updates (blue/green, canary)
  • CI/CD integration patterns and image promotion

📖 Episode 10: Multi-Cluster Management & Course Synthesis​

Duration: 15 min • 📝 Transcript

Learn about:

  • Operating 20+ clusters: fleet management with GitOps
  • Hub-and-spoke model and app-of-apps pattern
  • Policy enforcement at scale (OPA, Gatekeeper, Kyverno)
  • Disaster recovery: backup strategies and multi-region failover
  • Comprehensive review of all course concepts
  • Next steps: CKA/CKAD/CKS certification paths

Learning Resources​

For deeper exploration, see our comprehensive Kubernetes guide.

Official Documentation​

Certification & Advanced Learning​

Production Tools Referenced in Course​

About This Course​

This course uses evidence-based learning techniques to maximize retention and practical application:

  • Spaced Repetition: Key concepts reviewed across multiple episodes for 2-3x better retention
  • Active Recall: Retrieval prompts throughout strengthen memory formation
  • Progressive Complexity: Each lesson builds achievably on previous knowledge
  • Real-World Focus: Production scenarios based on actual incidents and 2024 industry data (98% face production challenges, 20+ cluster average)

Course Philosophy: We assume you're an experienced engineer who knows the basics. We don't waste time re-teaching Pods. Instead, we focus on the gaps between tutorials and production reality—the knowledge that takes years to learn through trial, error, and 2 AM incidents.

What Makes This Course Complete: Unlike most K8s training that focuses only on getting things running, this course covers the full production operations toolkit: stateful workloads (databases), observability (Prometheus, logging), security (RBAC, secrets), cost optimization (FinOps), and GitOps automation. Everything you need to operate Kubernetes at scale in production.

Questions or feedback? This course is open source. Contribute via GitHub.