How I think about building a cloud platform operating model
A practical model for reliability, delivery speed, IAM, observability, and cost ownership.
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Engineering notes from cloud, DevOps, SRE, and AI platform work.
I write to make engineering judgment reusable: operating models, best practices, tradeoffs, and the patterns that make platforms easier to trust.
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Terraform best practices I keep coming back to
Patterns for state, modules, reviews, naming, and repeatable infrastructure delivery.
Read articleObservability foundations for platform teams
How to move from dashboards to signals, ownership, and reliable incident response.
Read articlePractical infrastructure foundations for AI teams
Governed environments, scalable compute, artifact paths, cost controls, and deployment foundations.
Read articleAI Ops trends to watch in 2026
Practical shifts in model observability, reproducibility, governance, and cost-aware lifecycle.
Read articleCloud cost optimization patterns for 2026
Autoscaling economics, spot strategies, and telemetry-driven rightsizing to control cloud spend.
Read articleKubernetes security priorities for 2026
Supply chain hardening, RBAC least-privilege, and runtime protection approaches.
Read articleBuild MCP skills for AI assistants
Practical guidance for designing, validating, and integrating custom AI assistant skills.
Read articleRun AI models locally with OpenLLM
How to use OpenLLM and open-source tooling for local model inference and experimentation.
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