Mlflow end to end deployment

Author: IshmeetMehta

use-cases/mlflow-inference-pipeline/mlflow-deployment/mlflow/Dockerfile

@@ -10,9 +10,9 @@ RUN pip3 install --no-cache-dir -r requirements.txt
 
 ENV PYTHONUNBUFFERED 1
 ENV PGPASSWORD=""
-ENV MLP_MLFLOW_DATABASE_URI=postgresql+psycopg2://[email protected]:@127.0.0.1:5432/mlflowdb
-ENV MLP_MLFLOW_ARTIFACT_LOCATION=gkebatchenv3a4ec43f-mlflow-prod-mlflow
+# ENV MLFLOW_DATABASE_URI=V_MLFLOW_DATABASE_URI
+# ENV MLFLOW_ARTIFACT_LOCATION=V_MLFLOW_ARTIFACT_LOCATION
 EXPOSE 5000
 
 # Run the MLflow server 
-CMD ["mlflow", "server", "--host", "0.0.0.0", "--port", "5000", "--backend-store-uri","${MLP_MLFLOW_DATABASE_URI}" , "--default-artifact-root", "${MLP_MLFLOW_ARTIFACT_LOCATION}"]
+CMD ["mlflow", "server", "--host", "0.0.0.0", "--port", "5000", "--backend-store-uri","V_MLFLOW_DATABASE_URI" , "--default-artifact-root", "V_MLFLOW_ARTIFACT_LOCATION"]