notes.txt

### 1 - Deploying product

## Local work
# Build the docker file
docker build --build-arg HF_TOKEN=$HF_TOKEN -t mlops-cs3 .

# run the docker image locally
docker run -p 7860:7860 mlops-cs3

# tag the docker image to docker hub repository
docker tag mlops-cs3 venkateshroshan/mlops-cs3:latest

# push the docker image to docker hub repository
sudo docker push venkateshroshan/mlops-cs3:latest

## VM Server
# login to vm server via ssh
ssh -p 2222 [email protected]

# pull the docker image
docker pull venkateshroshan/mlops-cs3:latest

# run the docker image
docker run -d -p 7860:7860 venkateshroshan/mlops-cs3

# access the application in localhost via ssh tunneling
ssh -L 7860:localhost:7860 -p 2222 [email protected]
http://localhost:7860

-> explanation : Forwards local machine’s port 7860 to port 7860 on the VM and the ssh server is listening on port 2222.

### 2 - Monitoring product
# add prometheus-node-exporter in dockerfile and rebuild the docker image
RUN apt-get install -y prometheus-node-exporter

# exposing ports 
# Prometheus Node Exporter metrics
EXPOSE 25561
# Prometheus Python app metrics
EXPOSE 25562

# Run both the Node Exporter and the Gradio application
CMD ["sh", "-c", "prometheus-node-exporter & python app.py"]

# run docker
docker run -d -p 25560:7860 -p 25561:9100 -p 25562:8000 venkateshroshan/mlops-cs3:latest3 

# access the application in localhost via ssh tunneling
ssh -L 25560:localhost:25560 -L 25561:localhost:25561 -L 25562:localhost:25562 -p 2222 [email protected]

Gradio application at http://localhost:25560
Prometheus monitoring at http://localhost:25561
Prometheus metrics endpoint at http://localhost:25562

### 3 - Expose your product using ngrok (or a similar service) 
* Expose your service globally
# add authtoken of ngrok
ngrok authtoken YOUR_AUTH_TOKEN

# expose the port
ngrok http 25560 -> this gives public URL

ngrok http 25561

ngrok http 25562