Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.
Learn how to reduce LLM model size and inference costs using quantization techniques like Q4, Q8, and GPTQ. Practical guide with benchmarks.
GitHub Actions Pipeline Reliability. Practical guidance for reliable, scalable platform operations.
How a small team moved from single-region risk to a simple active/passive multi-region setup without doubling complexity.
Practical game day scenarios for CI/CD: broken rollbacks, permission issues, and slow feedback loops—and how we fixed them.
A field report from rolling out retrieval-augmented generation in production, including cache bugs, bad embeddings, and how we fixed them.
Docker Image Hardening for Production. Practical guidance for reliable, scalable platform operations.
Compare the top vector databases for AI applications. Learn when to use Pinecone, Weaviate, or ChromaDB based on your requirements.
A real story of removing console-only changes, adding drift detection, and getting Terraform back in charge.
Concrete systemd unit patterns that reduced flakiness: restart policies, resource limits, and structured logs.
Learn how to build production-ready RAG applications using vector databases, embedding models, and LLMs. Complete guide with code examples and best practices.
Kubernetes Cluster Upgrade Strategy. Practical guidance for reliable, scalable platform operations.
Run retrieval-augmented generation at scale. Chunking, caching, and observability.
