dev commit

another/Dockerfile

@@ -0,0 +1,24 @@
+FROM python:3.7.0
+LABEL maintainer="Albert Franzi"
+
+ENV MLFLOW_HOME /opt/mlflow
+ENV SERVER_PORT 5000
+ENV SERVER_HOST 0.0.0.0
+ENV FILE_STORE ${MLFLOW_HOME}/fileStore
+ENV ARTIFACT_STORE ${MLFLOW_HOME}/artifactStore
+
+RUN pip install mlflow && \
+    mkdir -p ${MLFLOW_HOME}/scripts && \
+    mkdir -p ${FILE_STORE} && \
+    mkdir -p ${ARTIFACT_STORE}
+
+COPY scripts/run.sh ${MLFLOW_HOME}/scripts/run.sh
+RUN chmod +x ${MLFLOW_HOME}/scripts/run.sh
+
+EXPOSE ${SERVER_PORT}/tcp
+
+VOLUME ["${MLFLOW_HOME}/scripts/", "${FILE_STORE}", "${ARTIFACT_STORE}"]
+
+WORKDIR ${MLFLOW_HOME}
+
+ENTRYPOINT ["./scripts/run.sh"]

another/scripts/run.sh

@@ -0,0 +1,7 @@
+#!/bin/sh
+
+mlflow server \
+    --file-store $FILE_STORE \
+    --default-artifact-root $ARTIFACT_STORE \
+    --host $SERVER_HOST \
+    --port $SERVER_PORT

docker-compose.yml

@@ -0,0 +1,35 @@
+version: '3'
+services:
+    sftp:
+        image: atmoz/sftp
+        #volumes:
+        #    - <host-dir>/upload:/home/foo/upload
+        ports:
+            - "2222:22"
+        command: ftpuser:ftppass:::0
+        networks:
+            - A
+    database:
+        container_name: pg_mlflow
+        image: postgres:13
+        environment:
+            - POSTGRES_USER=pgsql
+            - POSTGRES_PASSWORD=pg_password
+            - POSTGRES_DB=mlflow
+        networks:
+            - A
+    tracker:
+        container_name: tracker_mlflow
+        image: tracker_ml
+        build:
+            context: ./mlflow
+            dockerfile: Dockerfile
+        ports:
+            - "5000:5000"
+        networks:
+            - A
+
+        entrypoint: mlflow server --default-artifact-root sftp://ftpuser:ftppass@localhost:2222 -h 0.0.0.0
+networks:
+    A:
+        driver: bridge

mlflow/Dockerfile

@@ -1,7 +1,5 @@
 FROM continuumio/miniconda3:latest
 
-MAINTAINER JianKai Wang "https://jiankaiwang.no-ip.biz"
-
 ADD . /app
 WORKDIR /app
 

quickstart/mlflow_tracking.py

@@ -1,9 +1,11 @@
 import os
 from random import random, randint
 
-from mlflow import log_metric, log_param, log_artifacts
+from mlflow import mlflow,log_metric, log_param, log_artifacts
 
 if __name__ == "__main__":
+    with mlflow.start_run() as run:
+        mlflow.set_tracking_uri('http://localhost:5000')
         print("Running mlflow_tracking.py")
 
         log_param("param1", randint(0, 100))

test.sh

@@ -0,0 +1,3 @@
+#!/bin/bash
+export MLFLOW_TRACKING_UI=http://localhost:5000
+mlflow run git@github.com:databricks/mlflow-example.git -P alpha=0.5 --no-conda