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Deploy MLflow with PostgreSQL backend store and RustFS S3-compatible artifact storage. Includes automatic bucket creation init container. - MLflow v3.10.1 (ghcr.io/mlflow/mlflow) - PostgreSQL 15 Alpine for experiment metadata - RustFS 1.0.0-alpha.90 for artifact storage - Auto-generated secrets for DB password and S3 credentials - Health checks on all services
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Pull request overview
Adds a new Dokploy blueprint for deploying MLflow (experiment tracking + model registry) backed by PostgreSQL and RustFS (S3-compatible artifact store), and registers it in the central template index.
Changes:
- Added a new
mlflowentry tometa.json(with logo/links/tags). - Introduced
blueprints/mlflow/docker-compose.ymlwith 4 services (MLflow, Postgres, RustFS, and a bucket-init job). - Added
blueprints/mlflow/template.tomlvariables/env wiring and anmlflow.svglogo.
Reviewed changes
Copilot reviewed 3 out of 4 changed files in this pull request and generated 1 comment.
| File | Description |
|---|---|
| meta.json | Registers the new mlflow template in the global template catalog. |
| blueprints/mlflow/template.toml | Defines Dokploy variables, env injection, and domain routing for the MLflow service. |
| blueprints/mlflow/docker-compose.yml | Implements the multi-service MLflow deployment (DB + S3 storage + init container). |
| blueprints/mlflow/mlflow.svg | Adds the logo referenced by the meta entry. |
- Pin psycopg2-binary==2.9.11 and boto3==1.42.78 for reproducibility - Add start_period: 120s to MLflow healthcheck to account for pip install time on cold starts
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Adds a template for MLflow, the open source ML lifecycle platform
The setup includes 4 services
All secrets (db password and S3 credentials) are auto-generated at deploy time through Dokploy helpers
Test plan