Dockerize Flask API application with Dockerfile and Docker Compose
This video explain how to:
- Test your Python API application to make predictions with ML model endpoint with Postman.
- Create and set-up Dockerfile (with clear explanation).
- Prepare Docker compose (docker-compose.yml) file to orchestrate services need to run your Flask application (for example, a database).
- Build and run a Docker image from Docker compose file.
You will also learn what are the differences between docker compose build and docker compose up commands. With that you will get a clear explanation how Dockerfile works, and what is the logic behind. So, you will quickly dive into Dockerhub - the big library of Docker images which can be used for your unique Docker containers. This is what exactly we are doing in this tutorial.
By using this approach you will be able to Dockerize any Flask based API app, whether it is ML classifier/model or a simple API. In this example I used a predefined model.joblib ML classifier previously.
The content of the video:
0:00 - Test Flask API application locally with Postman
2:57 - Explain Dockerizing and setup Dockerfile
9:57 - Setup Docker Compose file
13:54 - How to setup Docker Compose for multiple Services
15:25 - Build and Run a Docker Image
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#docker #flask #dockerfile
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