Pillar Guide
Cloud architecture: decisions that matter more than the venue
Cloud architecture as engineering, not ideology: landing zones, identity, network, data gravity, and egress economics — the decisions that actually matter.
Topic
Infrastructure & Platform Engineering
Infrastructure engineering is the design and operation of the compute, storage, network, and platform layers that applications depend on. This section covers Kubernetes and platform engineering, cloud architecture, observability, and the operational discipline that keeps systems available.
- Kubernetes and container platforms
- Cloud and hybrid architecture
- Observability and SRE
- Hosting and data-center operations
- Automation and DevOps
Start here
The pillar guides — orientation pages that map this territory and point to the deep-dive articles.
Pillar Guide
Kubernetes in production: what it is and when it earns it
Kubernetes explained as a control loop over desired state: when it earns its complexity, the production-readiness territory, and what operating it costs.
Articles & guides
Infrastructure modernization without the theater
An infrastructure modernization approach without transformation theater: what to replace, what to keep, strangler patterns, funding, and risk-first sequencing.
Infrastructure as Code Is an Operating Model, Not a Tool
Infrastructure as code beyond the tooling: repo structure, review gates, drift management, state security, and CI/CD pipelines that make IaC trustworthy.
Cloud vs On-Premises: An Honest Decision Framework
A cloud vs on-premises framework built on real constraints: egress costs, data gravity, compliance, latency, and staffing — and why hybrid is the usual answer.
Building a Home Lab With Production Discipline
How to build an engineering home lab that mirrors production: hardware tiers, virtualization choices, network segmentation, and the skills worth practicing.
Observability Stack Design: Metrics, Logs, Traces, and Cost
How to design an observability stack that engineers trust: Prometheus and Loki-class architecture, retention and cost engineering, and symptom-based alerting.
Kubernetes Troubleshooting: A Method That Always Finds It
A systematic Kubernetes troubleshooting method — cluster, node, workload, network, storage — with the kubectl commands in order and common failure signatures.
Production Kubernetes Architecture: What Actually Changes
Production Kubernetes architecture decisions that separate lab clusters from real platforms: control plane topology, node pools, ingress, storage, upgrades.