Anatomy of an MLOps Pipeline - Part 2: Deployment and Infrastructure
Complete MLOps Series: ← Part 1: Pipeline | Part 2 (current) | Part 3: Production → Anatomy of an MLOps Pipeline - Part 2: Deployment and Infrastructure 8. CI/CD with GitHub Actions: The Philosophy of Automated MLOps The Philosophical Foundation: Why Automation Isn’t Optional Before diving into YAML, let’s address the fundamental question: why do we automate ML pipelines? The naive answer is “to save time.” The real answer is more profound: because human memory is unreliable, manual processes don’t scale, and production systems demand reproducibility. ...