pygeoapi/aws-lambda

Using pygeoapi on AWS Lambda Serverless

Overview

AWS Lambda Serverless is a service from Amazon that enables publishing code which is executed as on demand functions. The value is here is that the server is only working when requests are made, resulting in more efficient use of server resources as well as managing costs.

pygeoapi provides a couple of ways to publish to AWS Lambda depending on your environment: zappa and node/serverless.

zappa

zappa provides Python tooling to interact with AWS lambda. Ensure the environment variables AWS_ACCESS_KEY and AWS_SECRET_ACCESS_KEY are set and available.

# install zappa
pip install zappa

# set environment variables
export AWS_ACCESS_KEY_ID=foo
export AWS_SECRET_ACCESS_KEY=bar

# deploy pygeoapi to AWS Lambda
zappa deploy -s zappa_settings.json

# update
zappa update -s zappa_settings.json

# undeploy
zappa undeploy -s zappa_settings.json

node/serverless

The included serverless.yml and pygeoapi-serverless-config.yml can be used to deploy pygeoapi on AWS Lambda Serverless Environment.

This requires Amazon Credentials and the Serverless deployment tool.

AWS Credentials can be created following the instructions at https://serverless.com/framework/docs/providers/aws/guide/credentials/

Move serverless configs to root directory:

mv serverless.yml ..
mv pygeoapi-config.yml ..
cd ..

To install the Serverless environment

npm install serverless

The following serverless plugins are also used

serverless plugin install -n serverless-python-requirements
serverless plugin install -n serverless-wsgi

To test the application as a lambda locally:

serverless wsgi serve

To deploy to AWS Lambda:

serverless deploy

Once deployed, if you only need to update the code and not anything in the serverless configuration, you can update the function using:

serverless deploy function -f app

When deployed, the output will show the URL the app has been deployed to.

node/serverless lambda container

In the case where your pygeoapi instance is too large to deploy as a lambda function (250MB) you can build and deploy a docker image of pygeoapi with the lamda runtime interface installed.

Move serverless configs to root directory:

mv container/serverless.yml ../..
mv container/DockerFile ../..

*note the files below come from the serverless-wsgi node plugin, and ideally this should be part of a build process

cd container/
npm install serverless
serverless plugin install -n serverless-wsgi
mv node_modules/serverless-wsgi/serverless-wsgi.py ../..
mv node_modules/serverless-wsgi/wsgi_handler.py ../..
mv container/wsgi.py ../..
mv container/.serverless-wsgi ../..
rm -rf container/node_modules
cd ../..

to build docker container

docker build -t pygeo-lambda-container .

Once built, you need to deploy to ECR. This can also be accomplished with a change to the serverless configuration. Depending on environment permissions, you may need to create a ECR repo with appropriate policies first.

AWS_PROFILE=<profile name> aws ecr get-login-password --region <region> | docker login --username AWS --password-stdin <ECR repo url>
docker tag pygeo-lambda-container:latest <ECR repo url>:latest
docker push <ECR repo url>:latest

Deploy stack using serverless.

AWS_PROFILE=<profile name> sls deploy -s <stage name>