244 saved links. The corpus starts with the classics (Fowler, pipelines, Jenkins), gets deep into GitHub Actions and Azure DevOps practice, and ends where everything else in your vault ends: pipelines that build AI, and AI that runs pipelines.
Related: DevOps · GitOps · Infrastructure as Code · Git
Start here
- Fowler’s thoroughly revised Continuous Integration article — the definition, from the source.
- Clare Liguori: the CI/CD architecture Amazon actually uses — branch management, rollout waves, automated rollback.
- what is CI/CD — the practical guide and a gentle introduction to pipelines.
- the core continuous-deployment patterns — canary, blue/green, and friends in one post.
- 15 CI/CD metrics worth actually tracking.
GitHub Actions in practice
- a guided introduction to GitHub Actions · Awesome Actions.
- Runners: self-hosted runners, step by step · self-hosting runners on cloud infra.
- Security: workflow-authoring security best practices · securing Actions with Azure workload identity federation (video) · adding an SBOM to your containers with Actions.
- Governance: required workflows — confidence in the Friday deploy.
- Patterns: Willison’s minimal pattern: custom site built by Actions, deployed to Pages — the exact pattern behind this site’s deploys · modular, centralized custom Actions · David Fowler’s GitHub↔Azure CI/CD glue utility.
- Testing in the pipeline: Playwright on every commit (video) · validating Terraform in Actions (video).
Pipeline security
- NSA/CISA: Defending CI/CD Environments — the authoritative hardening sheet.
- CI/CD security: risks and best practices · implementing DevSecOps in a CI/CD pipeline, step by step.
- smarter pipelines with conditional rules.
Observability for pipelines
Pipelines are production systems too — the thread that connects this page to SRE & Observability.
The AI-native pipeline
- what an AI-native CI/CD experience looks like — goal-based pipelines from developer intent.
- enforcing quality checks on AI-generated code — “you don’t need a special AI pipeline.”
- Gemini CLI GitHub Actions — an AI teammate inside the pipeline · Willison on the new term for mixing AI into automations.
- Microsoft Foundry adds CI/CD for AI agents — what actually changes.
- Pipelines that ship models: GitHub Actions for agent evaluations in LLMOps · LLMOps with Azure AI, PromptFlow, Bicep, and Actions · model retraining automation via Actions · a continuous-delivery architecture for RAG apps.
Azure DevOps pipelines
- using ADO pipelines as a serverless compute engine — the creative pattern.
- ACR → Azure Container Apps via ADO pipeline · APIM with developer portal, CI/CD’d through ADO.
- Enterprise Azure Policy as Code (EPAC) in CI/CD.
- Symphony — a multi-IaC CI/CD orchestrator with baked-in best practices.