Update to latest MLFlow and Python versions (#18)

- Update MLFlow 1.3 -> MLFlow 1.13
- Change internal file system store to SQLite
  (file system URIs are unsupported for model artifact tracking stores)
- Update Python 3.7 -> Python 3.9
- Update boto3 1.9.240 -> boto3 1.16.46
- Remove some unused defaults in Dockerfile

mlflow_tracking_server/Dockerfile

@@ -1,15 +1,12 @@
-FROM python:3.7
+FROM python:3.9
 
 LABEL maintainer "Florian Muchow <flmuchow@gmail.com>"
 
-RUN pip install mlflow==1.3.0 && \
+RUN pip install mlflow==1.13 && \
     pip install awscli --upgrade --user && \
-    pip install boto3==1.9.240
+    pip install boto3==1.16.46
 
 ENV PORT 5000
-ENV AWS_BUCKET bucket
-ENV AWS_ACCESS_KEY_ID aws_id
-ENV AWS_SECRET_ACCESS_KEY aws_key
 
 COPY files/run.sh /
 

mlflow_tracking_server/files/run.sh

@@ -12,18 +12,8 @@ if [ -z $AWS_BUCKET ]; then
   exit 1
 fi
 
-if [ -z $AWS_ACCESS_KEY_ID ]; then
-  echo >&2 "AWS_ACCESS_KEY_ID must be set"
-  exit 1
-fi
-
-if [ -z $AWS_SECRET_ACCESS_KEY ]; then
-  echo >&2 "AWS_SECRET_ACCESS_KEY must be set"
-  exit 1
-fi
-
 mkdir -p $FILE_DIR && mlflow server \
-    --backend-store-uri file://${FILE_DIR} \
+    --backend-store-uri sqlite:///${FILE_DIR}/sqlite.db \
     --default-artifact-root s3://${AWS_BUCKET}/artifacts \
     --host 0.0.0.0 \
     --port $PORT