MLFlow on AWS EC2

• MLflow is organized into four components: Tracking, Projects, Models, and Model Registry. 
• Create AWS Free EC2 t2 micro ubuntu machine
• Follow the below steps to setup mlflow
• Install ngnix to route requests from external networks
• Run a few experiments, Visualize results

Steps

	#Customized for AWS EC2 - https://mlflow.org/docs/latest/tutorials-and-examples/tutorial.html
	Step 1 - Update packages
	sudo apt-get update
	Step 2 - Install pip
	sudo apt install -y python-pip nginx
	sudo apt install python3-pip
	sudo apt install python3-pip
	pip3 install scikit-learn
	pip3 install mlflow
	pip3 install mlflow[extras]
	Step 3 - Config file creation
	sudo vim /etc/nginx/sites-enabled/fastapi_nginx
	Step 4 - Contents
	server {
	listen 5000;
	server_name 54.245.141.171;
	location / {
	proxy_pass http://127.0.0.1:80;
	}
	}
	Step 5 - Restart Service
	sudo service nginx restart
	Step 6 - Download file
	wget https://gist.githubusercontent.com/siva2k16/c67bf8635ff89fd4d1baf43aacd7662e/raw/e5d9028964d80ab1c0afe66c56e0dc967190c4a7/mlflowdemo.py
	Step 7 - Run Experiment
	python3 mlflowdemo.py
	Step 9 - Allow inbound communication
	One more key step - Enable inbound on port 80 in security groups
	Step 10 - Link mlflow
	who, gets username ubuntu
	PATH=$PATH:/home/ubuntu/.local/bin
	Step 11 - Instantiate UI
	mlflow ui
	sudo fuser -k 5000/tcp
	mlflow ui
	mlflow ui --host 127.0.0.1
	mlflow server -h 0.0.0.0
	Step 10 - Check the report from public internet
	http://54.245.141.171:80

view raw mlflowsteps.txt hosted with ❤ by GitHub

References

Keep Exploring!!!