Track ML model experiments with new GitLab MLFlow integration

This post introduces the integration of MLFlow experiment tracking directly into the GitLab DevSecOps platform. It enables users to track ML model experiments by pointing the MLFlow client to their GitLab project, with experiments and runs recorded on GitLab without needing to set up a separate MLFlow server. It highlights features like user access management tied to GitLab projects, managing candidates (MLFlow runs) directly in the GitLab UI, and downloading candidate data as CSV. The post also mentions future plans for managing the entire ML model lifecycle within GitLab and seeks feedback on this experimental feature.