Andreluizfc / tdc-21-your-first-ml-deploy

Your first ML app deploy ☁️👨‍💻

Your First ML App Deploy

1 RUN LOCALLY

Requirements

1. Python
2. Virtual Environment

Configure a new Python Virtual Environment and Run

Create New Virtual Environment (Venv) and Install Dependencies

python3 -m venv name_of_your_venv
source name_of_your_venv/bin/activate
pip install -U pip
python -m pip install --upgrade setuptools
pip install -r requirements.txt -U

Call the app initialization

cd app/
python3 web_server.py

2 RUN LOCALLY WITH DOCKER

Requirements

1. Docker Desktop

Build Docker Image

The file named Dockerfile contains all the instructions to build a Docker image. Navigate to root of the project and run:

docker build -t ml_model:1.0 .

Then run the docker image on port 8080:

docker run -p 8080:8080 ml_model:1.0

3 RUN ON CLOUD WITH HEROKU

Requiriments

1. Heroku CLI

Deploy to Heroku

1. Install heroku Comand Line Interface (CLI).
2. Login to Heroku. heroku login -i
3. Update to beta. heroku update beta
4. Install plugin-manifest. heroku plugins:install @heroku-cli/plugin-manifest
5. Create your app heroku create YOUR-APP-NAME --manifest
6. Check if app has been created. Your app should be listed. heroku apps
7. Update Remote heroku git:remote -a YOUR-APP-NAME
8. Publish your app. git push heroku main
9. Check app status. heroku logs -a YOUR-APP-NAME

Now you can visit you deployed app in the URL Heroku made for you. https://YOUR-APP-NAME.herokuapp.com/