Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.
A practical risk-management framework for release timing, Friday deployment policies, progressive delivery, and how elite teams protect reliability and people.
Cut Kubernetes spend without hurting reliability using a practical FinOps playbook for rightsizing, autoscaling guardrails, showback, and weekly waste cleanup.
A practical way to define SLOs and error budgets, connect them to release decisions, and avoid reliability debates without data.
How to implement Backstage with real templates, scorecards, and golden paths so internal platform work reduces delivery friction.
A practical pattern for monorepo CI with path filters, matrix builds, caching, and deployment guards that keep feedback fast as teams scale.
A production-focused guide to Azure DevOps: standardized YAML templates, secure service connections, rollout safety, and measurable delivery reliability.
A practical production playbook for AI systems: evaluation gates, guardrails, observability, cost control, and reliable release management.
A practical field manual for engineering teams who want AI features that survive real users, incidents, and budgets — not just demo day.
AI Inference Cost Optimization. Practical guidance for reliable, scalable platform operations.
SLO-Based Monitoring for APIs. Practical guidance for reliable, scalable platform operations.
Secure Container Supply Chain Controls. Practical guidance for reliable, scalable platform operations.
Infrastructure Documentation as Code. Practical guidance for reliable, scalable platform operations.
