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.
This solution is based entirely on AWS services including CodeCommit, CodePipeline, CodeBuild, CodeCeploy, and CloudFront. 😅
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.
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.
cdk deploy CloudfrontCertificateStack -c domain_name=notebooks.example.comOne of the outputs from this stack will be CloudfrontCertificateStack.certificatearn - you'll need the value of this for the next phase.
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.
cdk bootstrap aws://ACCOUNT-NUMBER-1/REGION-1Once you do that, you can deploy the stack.
cdk deploy EmrStudioPublisherStack -c domain_name=notebooks.example.com -c certificate_arn=arn:aws:acm:us-east-1:012345678912:certificate/f07b01a4-3e8c-4639-8a22-b7a20a832de3Once 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 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.
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")