Deep-dive technical articles on cloud architecture, networking, security, databases, and infrastructure. Written by practitioners who build and scale production systems.
A practical guide to Kubernetes autoscaling: how HPA, VPA, KEDA, and Cluster Autoscaler work, when to use each, and how to avoid the pitfalls that catch most teams.
Comprehensive guide to encryption at rest and in transit covering implementation, key management, TLS configuration, performance impact, and compliance requirements.
Opinionated guide to stored procedures covering performance benefits, maintainability costs, security implications, and practical guidelines for when they help vs hurt.
Practical guide to cloud storage snapshots and volumes covering architecture, performance, cost optimization, backup strategies, and disaster recovery patterns.
How to implement per-PR ephemeral preview environments on Kubernetes using ArgoCD ApplicationSets, Neon database branching, wildcard TLS, and automated cleanup — plus an honest look at managed platforms like Okteto and Bunnyshell.
In-depth comparison of columnar and row-oriented databases covering storage architecture, compression, query performance, and choosing the right one for your workload.
A practical guide to LLM quantization formats for production inference: when to use GGUF vs AWQ vs GPTQ vs FP8, VRAM arithmetic that actually works, and the infrastructure decisions that follow.
A principal cloud architect's guide to Kafka Schema Registry in production: choosing between Avro and Protobuf, understanding compatibility modes, and evaluating your options after IBM acquired Confluent.
A deep dive into Kubernetes CPU requests, memory limits, QoS classes, LimitRange, and ResourceQuota. Learn why pods get OOMKilled and evicted, and how to right-size your workloads for reliable production clusters.
A hands-on guide to Cloud Development Environments (CDEs): how Coder, DevPod, GitHub Codespaces, and devcontainers work, when to adopt them, and why AI agents are making this the most important platform engineering decision of 2026.
Apache Flink 2.x is the dominant engine for stateful stream processing. Here is how checkpoints, state backends, watermarks, and the Kubernetes operator actually work in production, with the hard lessons I have learned running Flink at scale.
A principal cloud architect's guide to detecting leaked credentials in git history, CI logs, and container images using Gitleaks, TruffleHog, and GitGuardian. Includes pre-commit setup, CI integration, and how to handle the scary historical scan.
Practical deep dives on infrastructure, security, and scaling. No spam, no fluff.
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