diff --git a/Makefile b/Makefile
index 162c2a6..c7fdcfc 100644
--- a/Makefile
+++ b/Makefile
@@ -26,6 +26,7 @@ dependencies: test_environment
 	$(PYTHON_INTERPRETER) -m pip install -r requirements.minimal
 	sudo curl -o ./assets/hadoop-aws-3.3.4.jar https://repo1.maven.org/maven2/org/apache/hadoop/hadoop-aws/3.3.4/hadoop-aws-3.3.4.jar
 	sudo curl -o ./assets/aws-java-sdk-bundle-1.12.506.jar https://repo1.maven.org/maven2/com/amazonaws/aws-java-sdk-bundle/1.12.506/aws-java-sdk-bundle-1.12.506.jar
+	sudo curl -o ./assets/aws-java-sdk-core-1.12.506.jar https://repo1.maven.org/maven2/com/amazonaws/aws-java-sdk-core/1.12.506/aws-java-sdk-core-1.12.506.jar
 	sudo curl -o ./assets/hadoop-common-3.3.4.jar https://repo1.maven.org/maven2/org/apache/hadoop/hadoop-common/3.3.4/hadoop-common-3.3.4.jar
 	sudo curl -o ./assets/postgresql-42.6.0.jar https://jdbc.postgresql.org/download/postgresql-42.6.0.jar
 	#cp ./assets/hadoop-aws-3.3.4.jar ~/$(CONDA_FOLDER_NAME)/envs/next-watch/lib/python3.10/site-packages/pyspark/jars/
@@ -56,6 +57,7 @@ run:
 
 ## Populate Databse with Users from production datasets
 users:
+	docker compose exec dev-spark bash -c "python3.9 src/main.py -p 'de'"
 	docker compose exec dev-spark bash -c "python3.9 src/scripts/populate_db_with_users.py"
 
 ## Run DE pipelines
diff --git a/README.md b/README.md
index 1a77ad1..98106a5 100644
--- a/README.md
+++ b/README.md
@@ -28,31 +28,45 @@ git clone https://github.com/brnaguiar/mlops-next-watch.git
 make env
 ```
 
-3. Install requirements / dependencies and assets
+3. Activate conda env
+```sh
+source activate nwenv
+```
+
+4. Install requirements / dependencies and assets
 ```sh
 make dependencies
 ```
 
-4. Pull the datasets
+5. Pull the datasets
 ```sh
 make datasets
 ```
 
-5. Configure containers and secrets
+6. Configure containers and secrets
 ```sh
 make init
 ```
 
-6. Run Docker Compose
+7. Run Docker Compose
 ```sh
 make run
 ```
 
-7. Populate production Database with users
+8. Populate production Database with users
 ```sh
 make users
 ```
 
+## Useful Service Endpoints
+```
+- Jupyter `http://localhost:8888`
+- Minio `http://localhost:9001`
+- MLFlow `http://localhost:5000`
+- FastAPI `http://localhost:8086/`
+- Streamlit UI `http://localhost:8501`
+- Grafana Dashboard `http://localhost:3000`
+```
 ## Architecture
 <img src="./images/project_diagram.jpg">
 <!-- #4. Create a `.env` file (`.env` sample below)#
diff --git a/src/conf/params.py b/src/conf/params.py
index 2e68373..ee49f84 100644
--- a/src/conf/params.py
+++ b/src/conf/params.py
@@ -83,11 +83,11 @@ class Airflow:
     postgres_conn_config: dict = {
         "conn_id": "postgres_connection",
         "conn_type": "postgres",
-        "host": f"{os.getenv('postgres_ip')}",
-        "login": f"{os.getenv('pguser')}",
-        "password": f"{os.getenv('pgpassword')}",
-        "port": f"{os.getenv('postgres_port')}",
-        "schema": f"{os.getenv('postgres_app_database')}",
+        "host": f"{os.getenv('POSTGRES_IP')}",
+        "login": f"{os.getenv('PGUSER')}",
+        "password": f"{os.getenv('PGPASSWORD')}",
+        "port": f"{os.getenv('POSTGRES_PORT')}",
+        "schema": f"{os.getenv('POSTGRES_APP_DATABASE')}",
     }
     aws_conn_config: dict = {
         "conn_id": "aws_connection",