mlflow-service

Launch mlflow service via docker

using remote artifacts, MinIO

Setup

1. modify .env from .env.example

    # postgres
    POSTGRES_USER=
    POSTGRES_PASSWORD=
    POSTGRES_DB=mlflow
    
    # mlflow
    BUCKET_NAME=mlflow
    
    # MinIO
    MINIO_ROOT_USER=
    MINIO_ROOT_PASSWORD=
    MINIO_VOLUMES=/mnt/data
    
    # project
    MLFLOW_S3_ENDPOINT_URL=http://localhost:9000
    ## usually same as `MINIO_ROOT_USER` and `MINIO_ROOT_PASSWORD`
    AWS_ACCESS_KEY_ID=
    AWS_SECRET_ACCESS_KEY=

2. [Optional] Create Self-signed certificates and HTTPS request

   1. Create Self-signed certificates

      cd nginx/ssl
      sudo openssl req -x509 -nodes -days 365 -newkey rsa:2048 -keyout private.key -out public.crt
      

   2. Modify service config file in nginx/conf.d

3. Launch Service

   docker-compose up -d
   

4. [Optional] Create Another Assess Keys or Users of MinIO

5. Add Environment Variables add the following environment variables to your application.

   # project
   MLFLOW_S3_ENDPOINT_URL=http://localhost:9000
   ## usually same as `MINIO_ROOT_USER` and `MINIO_ROOT_PASSWORD`
   AWS_ACCESS_KEY_ID=
   AWS_SECRET_ACCESS_KEY=

6. Log to mlflow log_metric.py