Update docker-compose.yml

fix build problem in macos m1

.github/workflows/verify-docker-compose.yml

@@ -4,7 +4,7 @@ jobs:
   verify:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
       - name: Show the config
         run: docker-compose config
       - name: Run

README.md

@@ -28,7 +28,7 @@
 
 1. Configure your client-side
 
-For running mlflow files you need various environment variables set on the client side. To generate them user the convienience script `./bashrc_install.sh`, which installs it on your system or `./bashrc_generate.sh`, which just displays the config to copy & paste.
+For running mlflow files you need various environment variables set on the client side. To generate them use the convienience script `./bashrc_install.sh`, which installs it on your system or `./bashrc_generate.sh`, which just displays the config to copy & paste.
 
 > $ ./bashrc_install.sh   
 > [ OK ] Successfully installed environment variables into your .bashrc!

docker-compose.yml

@@ -1,7 +1,7 @@
 version: "3.9"
 services:
   s3:
-    image: minio/minio:RELEASE.2021-11-24T23-19-33Z
+    image: minio/minio:RELEASE.2023-11-01T18-37-25Z
     restart: unless-stopped
     ports:
       - "9000:9000"
@@ -14,9 +14,9 @@ services:
       - internal
       - public
     volumes:
-      - minio_volume:/data
+      - minio_new_volume:/data
   db:
-    image: mysql/mysql-server:5.7.28
+    image: mysql:8-oracle # -oracle tag supports arm64 architecture!
     restart: unless-stopped
     container_name: mlflow_db
     expose:
@@ -27,16 +27,13 @@ services:
       - MYSQL_PASSWORD=${MYSQL_PASSWORD}
       - MYSQL_ROOT_PASSWORD=${MYSQL_ROOT_PASSWORD}
     volumes:
-      - db_volume:/var/lib/mysql
+      - db_new_volume:/var/lib/mysql
     networks:
       - internal
   mlflow:
+    image: ubuntu/mlflow:2.1.1_1.0-22.04
     container_name: tracker_mlflow
-    image: tracker_ml
     restart: unless-stopped
-    build:
-      context: ./mlflow
-      dockerfile: Dockerfile
     ports:
       - "5000:5000"
     environment:
@@ -70,10 +67,30 @@ services:
     command: tcp db:3306 -t 90s -i 250ms
     networks:
       - internal
+  run_test_experiment:
+    build:
+      context: ./test_experiment
+      dockerfile: Dockerfile
+    platform: linux/amd64  # once continuumio/miniconda3:latest image work on native aarch64 (arm), remove this line 
+    depends_on:
+      - "mlflow"
+    environment:
+      - AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID}
+      - AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}
+      - AWS_DEFAULT_REGION=${AWS_REGION}
+      - MLFLOW_S3_ENDPOINT_URL=http://s3:9000
+      - MLFLOW_TRACKING_URI=http://mlflow:5000
+    entrypoint: >
+      /bin/sh -c "
+      python3 mlflow_tracking.py;
+      exit 0;
+      "
+    networks:
+      - internal
 networks:
   internal:
   public:
     driver: bridge
 volumes:
-  db_volume:
-  minio_volume:
+  db_new_volume:
+  minio_new_volume:

quickstart/mlflow_tracking.py

@@ -1,22 +1,22 @@
 import os
 from random import random, randint
 
-from mlflow import mlflow,log_metric, log_param, log_artifacts
+import mlflow
 
 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))
+        mlflow.log_param("param1", randint(0, 100))
         
-        log_metric("foo", random())
-        log_metric("foo", random() + 1)
-        log_metric("foo", random() + 2)
+        mlflow.log_metric("foo", random())
+        mlflow.log_metric("foo", random() + 1)
+        mlflow.log_metric("foo", random() + 2)
 
         if not os.path.exists("outputs"):
             os.makedirs("outputs")
         with open("outputs/test.txt", "w") as f:
             f.write("hello world!")
 
-        log_artifacts("outputs")
+        mlflow.log_artifacts("outputs")

test_experiment/Dockerfile

@@ -1,7 +1,6 @@
 FROM continuumio/miniconda3:latest
 
-RUN pip install mlflow boto3 pymysql
+RUN pip install mlflow boto3
 
-ADD . /app
 WORKDIR /app
-
+COPY . .

test_experiment/mlflow_tracking.py

@@ -0,0 +1,22 @@
+import os
+from random import random, randint
+
+import mlflow
+
+if __name__ == "__main__":
+    with mlflow.start_run() as run:
+        mlflow.set_tracking_uri('http://mlflow:5000')
+        print("Running mlflow_tracking.py")
+
+        mlflow.log_param("param1", randint(0, 100))
+        
+        mlflow.log_metric("foo", random())
+        mlflow.log_metric("foo", random() + 1)
+        mlflow.log_metric("foo", random() + 2)
+
+        if not os.path.exists("outputs"):
+            os.makedirs("outputs")
+        with open("outputs/test.txt", "w") as f:
+            f.write("hello world!")
+
+        mlflow.log_artifacts("outputs")