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# mlflow-full
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# mlflow-full
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MLFlow docker container with support for Postgres. Implements extra environment variables for convenience.
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MLFlow docker container with support for Postgres. Implements extra environment variables for convenience.
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## Running the Container
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### Basic Usage
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```bash
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# Run with default settings
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docker run -p 5000:5000 gitea.gt-proj.com/brian/mlflow-full:latest
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```
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### With PostgreSQL Backend
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```bash
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# Using environment variables
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docker run -p 5000:5000 \
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-e MLFLOW_BACKEND_STORE_URI="postgresql://user:password@host:5432/mlflow" \
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-e MLFLOW_DEFAULT_ARTIFACT_ROOT="s3://my-bucket/mlflow-artifacts" \
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gitea.gt-proj.com/brian/mlflow-full:latest
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```
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### Complete Example with Docker Compose
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```yaml
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version: '3.8'
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services:
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postgres:
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image: postgres:15
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environment:
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POSTGRES_DB: mlflow
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POSTGRES_USER: mlflow
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POSTGRES_PASSWORD: mlflow_password
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volumes:
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- postgres_data:/var/lib/postgresql/data
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ports:
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- "5432:5432"
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mlflow:
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image: gitea.gt-proj.com/brian/mlflow-full:latest
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ports:
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- "5000:5000"
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environment:
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MLFLOW_BACKEND_STORE_URI: postgresql://mlflow:mlflow_password@postgres:5432/mlflow
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MLFLOW_DEFAULT_ARTIFACT_ROOT: /mlflow/artifacts
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MLFLOW_HOST: 0.0.0.0
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MLFLOW_PORT: 5000
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volumes:
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- mlflow_artifacts:/mlflow/artifacts
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depends_on:
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- postgres
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volumes:
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postgres_data:
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mlflow_artifacts:
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```
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### Environment Variables
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| Variable | Description | Default |
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|----------|-------------|---------|
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| `MLFLOW_BACKEND_STORE_URI` | Database connection string | `sqlite:///mlflow.db` |
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| `MLFLOW_DEFAULT_ARTIFACT_ROOT` | Artifact storage location | `./mlruns` |
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| `MLFLOW_HOST` | Host to bind the server | `0.0.0.0` |
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| `MLFLOW_PORT` | Port to bind the server | `5000` |
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### Advanced Examples
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#### With S3 Artifact Storage
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```bash
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docker run -p 5000:5000 \
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-e MLFLOW_BACKEND_STORE_URI="postgresql://user:password@host:5432/mlflow" \
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-e MLFLOW_DEFAULT_ARTIFACT_ROOT="s3://my-mlflow-bucket/artifacts" \
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-e AWS_ACCESS_KEY_ID="your-access-key" \
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-e AWS_SECRET_ACCESS_KEY="your-secret-key" \
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-e AWS_DEFAULT_REGION="us-west-2" \
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gitea.gt-proj.com/brian/mlflow-full:latest
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```
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#### With Custom Server Arguments
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```bash
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docker run -p 5000:5000 \
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-e MLFLOW_BACKEND_STORE_URI="postgresql://user:password@host:5432/mlflow" \
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gitea.gt-proj.com/brian/mlflow-full:latest \
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--host 0.0.0.0 \
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--port 5000 \
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--workers 4 \
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--expose-prometheus /metrics
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```
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### Kubernetes Deployment
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```yaml
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: mlflow-server
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spec:
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replicas: 1
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selector:
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matchLabels:
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app: mlflow-server
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template:
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metadata:
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labels:
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app: mlflow-server
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spec:
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containers:
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- name: mlflow-server
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image: gitea.gt-proj.com/brian/mlflow-full:latest
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ports:
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- containerPort: 5000
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env:
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- name: MLFLOW_BACKEND_STORE_URI
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value: "postgresql://mlflow:password@postgres-service:5432/mlflow"
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- name: MLFLOW_DEFAULT_ARTIFACT_ROOT
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value: "s3://mlflow-artifacts"
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---
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apiVersion: v1
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kind: Service
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metadata:
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name: mlflow-service
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spec:
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selector:
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app: mlflow-server
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ports:
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- port: 5000
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targetPort: 5000
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type: LoadBalancer
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```
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## Features
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- 🐘 **PostgreSQL Support**: Pre-installed `psycopg2-binary` for PostgreSQL connectivity
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- 🏷️ **OCI Labels**: Fully compliant with OCI image specification
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- 🔄 **Auto-updates**: Daily builds when the base MLflow image is updated
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- 📦 **Lightweight**: Based on official MLflow container
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## Building Locally
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```bash
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# Clone the repository
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git clone https://gitea.gt-proj.com/brian/mlflow-full.git
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cd mlflow-full
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# Build the image
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docker build -t mlflow-full:local .
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# Run your local build
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docker run -p 5000:5000 mlflow-full:local
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```
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