A practical explanation of observability vs monitoring for engineering teams building and operating cloud-native applications.
Terraform Best Practices for Cloud Infrastructure Teams
A practical Terraform best practices guide for cloud teams managing infrastructure modules, state, environments, secrets, and governance.
Docker Image Optimization: Smaller, Safer, Faster Containers
A practical Docker image optimization guide for smaller, safer, faster containers that build cleanly and deploy reliably.
CI/CD Pipeline Best Practices for Kubernetes Deployments
A practical guide to CI/CD best practices for Kubernetes deployments, from build and scan to rollout, rollback, GitOps, and observability.
Cloud Cost Optimization Checklist for AWS Teams
A practical AWS cloud cost optimization checklist for engineering and finance teams who want lower spend without hurting reliability.
How to Build Secure Internal AI Search Over Company Docs
A practical guide to secure internal AI search over company documents with permissions, citations, data boundaries, logging, and evaluation.
LLM Evaluation Framework: How to Test AI Apps Before Launch
A practical LLM evaluation framework for testing AI applications before launch with golden data, automated checks, review, and release gates.
Prompt Engineering for Production Apps: Patterns That Matter
A practical prompt engineering guide for production AI applications, focused on structure, context, evaluation, versioning, and reliability.
Vector Database vs Knowledge Graph: Which Is Better for AI Search?
A practical comparison of vector databases and knowledge graphs for AI search, including RAG retrieval, relationships, permissions, and hybrid designs.
How to Build an Enterprise AI Roadmap That Actually Ships
A practical enterprise AI roadmap for leaders and engineering teams who want pilots that move into production instead of staying in slide decks.