Kubernetes Architecture, Patterns & Production Best Practices

Kubernetes has become the de facto standard for running containerized workloads, but most production challenges don’t come from “how to deploy a Pod”, but from architectural decisions, operational trade-offs, and ecosystem complexity.

This page acts as a technical hub collecting all my in-depth articles on Kubernetes, focused on real-world usage, production patterns, and non-obvious problems that appear once clusters grow beyond toy examples.

The content is aimed at engineers and architects who already use Kubernetes and want to understand why certain things behave the way they do, when to use (or avoid) specific features, and how to operate clusters reliably at scale.

Kubernetes Mental Model

Kubernetes is best understood as a set of loosely coupled control planes, each solving a different concern. Most production issues happen at the boundaries between these concerns.

  • Core architecture & primitives
  • Networking & traffic management
  • Scheduling & workload placement
  • Security & policy enforcement
  • State, storage & persistence
  • Operations, upgrades & troubleshooting

🧩 Architecture & Core Concepts

🌐 Networking, Ingress & Traffic Management

🗂 Scheduling & Workload Placement

🔐 Security, Policies & Governance

🧠 Storage, State & Platform Dependencies

🛠 Operations, Troubleshooting & Production Reality

🧭 How to Use This Kubernetes Hub

New to Kubernetes in production?
Start with Ingress and scheduling articles — they expose the most common architectural pitfalls.

Running Kubernetes at scale?
Focus on policy enforcement, traffic management, and storage decisions.

Designing platforms, not just apps?
Pay attention to ecosystem boundaries (Ingress, storage, security tools).

❓ FAQ

🔗 Related Topics

  • Helm & application packaging
  • Service Mesh & traffic policies
  • CI/CD and policy enforcement