How To Deploy ML Models With Google Cloud Run
Learn how to deploy Machine Learning models with Google Cloud Run.
Learn how to deploy Machine Learning / Deep Learning models with Google Cloud Run. We build a simple app with TensorFlow and Flask, containerize it with Docker, and deploy it to Google Cloud Run.
You can find the code on GitHub: https://github.com/patrickloeber/ml-deployment.
1. Write App (Flask, TensorFlow)¶
- The code to build, train, and save the model is in the
- Implement the app in
2. Setup Google Cloud¶
- Create new project
- Activate Cloud Run API and Cloud Build API
3. Install and init Google Cloud SDK¶
4. Dockerfile, requirements.txt, .dockerignore¶
5. Cloud build & deploy¶
gcloud builds submit --tag gcr.io/<project_id>/<function_name> gcloud run deploy --image gcr.io/<project_id>/<function_name> --platform managed
- Test the code with
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