2026-08-09 MLflow Deployment Atlas
What I set out to do
Understand what an MLflow tracking server deployment actually consists of when running on a PostgreSQL backend store with GCS artifact storage: the database tables and their schemas, the artifact layout and root prefixes in the bucket, and the full REST API surface (the “swagger table”). Package it as a polished HTML report.
What I actually did
Ran three parallel codebase explorations against mlflow/mlflow (master @ 79163356e) and synthesized the results into a single interactive HTML report (“MLflow Deployment Atlas”), published as a Claude artifact.
- Database: catalogued all 59 tables in the tracking + model-registry database (alembic head
6f8d9c3b2a1e) plus 12 in the separate basic-auth/RBAC database (headf1a2b3c4d5e6), with full columns, types, PKs, FKs, indexes, and constraints, grouped by functional area (experiments/runs, traces/spans, logged models, registry, AI gateway, MCP registry, auth). - GCS layout: documented the prefix hierarchy
gs://root/<experiment_id>/<run_id>/artifactsplus thetraces/andmodels/m-<uuid>/subtrees, direct vsmlflow-artifacts:proxied access (identical on-bucket layout), and env-var configuration. - API: enumerated ~280 REST routes from the protobuf
rpcoptions, Flask handlers, and FastAPI routers, with method, path, description, and visibility status.
What was striking
- MLflow intentionally serves no swagger/OpenAPI UI:
docs_url/redoc_url/openapi_urlare all disabled in the FastAPI wrapper. The protobuf definitions are the only machine-readable spec. - Trace data is always stored as file artifacts in GCS even with a SQL backend; the DB holds only trace metadata and span rows.
- The GCS repo silently falls back to an anonymous client when credentials fail to resolve, and
delete_artifactsdoes raw prefix matching (deletingfooalso hitsfoobar). - Prompts have no dedicated tables or routes; they are registered models with a tag.
- A malformed proto path registers
/api/2.0mlflow/experiments/search-datasets(missing leading slash).
Related
Report artifact: MLflow Deployment Atlas