Building GitLab with GitLab: Why there is no MLOps without DevSecOps

This post details how GitLab's Data Science team uses GitLab CI/CD to build and store standardized data science container images in the GitLab Container Registry, enhancing experiment reproducibility. It also explains how GPU-enabled GitLab Runners are used for faster ML model training, triggered by commit messages, and introduces the use of GitLab's ML experiment tracker for storing pipeline metadata and artifacts.