https://github.com/ronylpatil/cicd-aws

Built e2e ci/cd pipeline with GitHub Actions, Docker, DockerHub and, Amazon EC2.
https://github.com/ronylpatil/cicd-aws

aws cicd machine-learning mlflow mlops

Last synced: 1 day ago
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Built e2e ci/cd pipeline with GitHub Actions, Docker, DockerHub and, Amazon EC2.

• Host: GitHub
• URL: https://github.com/ronylpatil/cicd-aws
• Owner: ronylpatil
• License: mit
• Created: 2024-05-07T15:40:48.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-05-29T05:43:56.000Z (8 months ago)
• Last Synced: 2024-05-29T18:24:39.039Z (8 months ago)
• Topics: aws, cicd, machine-learning, mlflow, mlops
• Language: Python
• Homepage:
• Size: 1.01 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.Docker.md
  • License: LICENSE

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README

        
### Building and running your application

When you're ready, start your application by running:

`docker compose up --build`.

Your application will be available at http://localhost:8000.

### Deploying your application to the cloud

First, build your image, e.g.: `docker build -t myapp .`.

If your cloud uses a different CPU architecture than your development

machine (e.g., you are on a Mac M1 and your cloud provider is amd64),

you'll want to build the image for that platform, e.g.:

`docker build --platform=linux/amd64 -t myapp .`.

Then, push it to your registry, e.g. `docker push myregistry.com/myapp`.

Consult Docker's [getting started](https://docs.docker.com/go/get-started-sharing/)

docs for more detail on building and pushing.

### References

* [Docker's Python guide](https://docs.docker.com/language/python/)