diff --git a/README.md b/README.md
index c823346..5e0d62a 100644
--- a/README.md
+++ b/README.md
@@ -47,18 +47,18 @@ source ~/.bashrc
 7. Test the pipeline with below command with conda. If you dont have conda installed run with `--no-conda`
 
 ```shell
-MLFLOW_S3_ENDPOINT_URL=http://localhost:9000/mlflow MLFLOW_TRACKING_URI=http://localhost:5000 mlflow run git@github.com:databricks/mlflow-example.git -P alpha=0.5
+MLFLOW_S3_ENDPOINT_URL=http://localhost:9000 MLFLOW_TRACKING_URI=http://localhost:5000 mlflow run git@github.com:databricks/mlflow-example.git -P alpha=0.5
 ```
 
 Optionally you can run 
 ```shell
-MLFLOW_S3_ENDPOINT_URL=http://localhost:9000/mlflow MLFLOW_TRACKING_URI=http://localhost:5000 python ./quickstart/mlflow_tracking.py
+MLFLOW_S3_ENDPOINT_URL=http://localhost:9000 MLFLOW_TRACKING_URI=http://localhost:5000 python ./quickstart/mlflow_tracking.py
 
 ```
 
 8. To make the setting permament move the MLFLOW_S3_ENDPOINT_URL and MLFLOW_TRACKING_URI into your .bashrc
 
 ```bash
-export MLFLOW_S3_ENDPOINT_URL=http://localhost:9000/mlflow
+export MLFLOW_S3_ENDPOINT_URL=http://localhost:9000
 export MLFLOW_TRACKING_URI=http://localhost:5000
 ```
diff --git a/docker-compose.yml b/docker-compose.yml
index a9fd555..97f88cb 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -41,7 +41,7 @@ services:
           - AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID}
           - AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}
           - AWS_DEFAULT_REGION=${AWS_REGION}
-          - MLFLOW_S3_ENDPOINT_URL=http://localhost:9000
+          - MLFLOW_S3_ENDPOINT_URL=http://s3:9000
       networks:
           - A
       entrypoint: mlflow server --backend-store-uri mysql+pymysql://${MYSQL_USER}:${MYSQL_PASSWORD}@db:3306/${MYSQL_DATABASE} --default-artifact-root s3://${AWS_BUCKET_NAME}/ -h 0.0.0.0