https://github.com/dacort/jupyter-static-website
A way to continuously deploy Jupyter notebooks to a static website backed by S3.
https://github.com/dacort/jupyter-static-website
aws cdk codepipeline jupyter
Last synced: 2 months ago
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A way to continuously deploy Jupyter notebooks to a static website backed by S3.
- Host: GitHub
- URL: https://github.com/dacort/jupyter-static-website
- Owner: dacort
- Created: 2021-07-14T21:17:36.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2021-07-14T23:25:01.000Z (almost 5 years ago)
- Last Synced: 2025-04-12T21:09:47.740Z (about 1 year ago)
- Topics: aws, cdk, codepipeline, jupyter
- Language: Jupyter Notebook
- Homepage:
- Size: 581 KB
- Stars: 2
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Automatic Jupyter Notebook Deployer
After I re-joined the EMR team in Jan 2021, I've been doing a lot more work in Jupyter notebooks.
I wanted a simple, elegant, and low-effort way to share those notebooks with the world, so I put together a continuous deployment notebook pipeline that can publish notebooks in a git repository to an S3-backed static website.
## Overview
This solution is based entirely on AWS services including CodeCommit, CodePipeline, CodeBuild, CodeCeploy, and CloudFront. 😅
## Deploying
**Make sure you have CDK and Python >= 3.9 installed.**
This project is a two-phased deploy due to the fact that CloudFront certificates need to be in `us-east-1`. If you _do not_ need a custom domain, you can skip the first part.
### Part 1 - CloudFront Certificate
This project only supports using the default CloudFront certificate and a DNS-validated CNAME. In order to generate the certificate, you'll need to run the command below, go into the AWS console and make sure you follow the validation instructions.
```shell
cdk deploy CloudfrontCertificateStack -c domain_name=notebooks.example.com
```
One of the outputs from this stack will be `CloudfrontCertificateStack.certificatearn` - you'll need the value of this for the next phase.
### Part 2 - Jupyter CD Pipeline
_If you are not using a custom domain, you can omit both of the `-c` options below._
First, make sure you bootstrap your AWS environment.
```shell
cdk bootstrap aws://ACCOUNT-NUMBER-1/REGION-1
```
Once you do that, you can deploy the stack.
```shell
cdk deploy EmrStudioPublisherStack -c domain_name=notebooks.example.com -c certificate_arn=arn:aws:acm:us-east-1:012345678912:certificate/f07b01a4-3e8c-4639-8a22-b7a20a832de3
```
Once this stack finishes, you should have a CodeCommit repository you can make changes to, a CloudFront distribution (the URL of which can be found in the `EmrStudioPublisherStack.cloudfrontendpoint` output), and a publicly accessible URL that has a pre-populated example site.
## Usage
Usage is pretty straight-forward. `git clone` the repository, make a change, and push it back up!
Any new notebooks added in the `docs/notebooks/` directory will automatically be published.
You can add links to the notebooks by updating the `nav` section of the `mkdocs.yml` file.
### Advanced Usage
Note that not _all_ images or libraries render nicely when converting to HTML. This is why, for example, in my plotly example I had to use `fig.show(renderer="jupyterlab")`
## References
- https://medium.com/andy-le/building-a-dynamic-aws-pipeline-with-cdk-5d5426fc0493
- https://binarythinktank.com/blog/static-site-deployment-cdk-aws