MLflow Tracking Server for the ML lifecycle — experiment tracking, model registry, and run metadata over a REST/UI on port 5000. Packaged as the lightweight mlflow-skinny stack (gunicorn + psycopg2 + boto3) on a hardened Wolfi python base; needs an external PostgreSQL backend store and an artifact store (S3 or PVC).
The latest line lives at the base page; older lines have their own page so you can pin and verify exactly that version.
Released version
This is the 0.0.6 release of the mlflow chart, published 2026-07-10.For the live security report and the currently deployed image digest, see the latest release.
Signed
cosign keyless
SBOM
SPDX, on image
Provenance
SLSA build
Architectures
amd64, arm64
Runs as
nonroot (uid 1001)
Root filesystem
read-only
Security report (Trivy)
D· 0/1009 fixable · rebuild clears them
0
Critical
6
High
3
Medium
0
Low
0
Unknown
Security report (Trivy) · image mlflow 3.15.0
Install the chart
Deploy to Kubernetes with hardened defaults. The chart pins its image by signed digest, so you never track it yourself.
The chart publishes its attestations on GitHub and the image it deploys carries its own on the same digest, publicly verifiable with the commands above. Both log to the Sigstore transparency log (Rekor), which cosign verify checks for you.