awssam-s3-pyplot

This project contains source code and supporting files for a serverless application that you can deploy with the SAM CLI. It includes the following files and folders.

• python_plotter - Code for the application's Lambda function.
• layers - supporting layers for the above application.
• static - any static resources to be hosted on s3.
• events - Invocation events that you can use to invoke the function.
• tests - Unit tests for the application code.
• template.yaml - A template that defines the application's AWS resources.

The application uses several AWS resources, including Lambda functions and an API Gateway API. These resources are defined in the template.yaml file in this project. You can update the template to add AWS resources through the same deployment process that updates your application code.

If you prefer to use an integrated development environment (IDE) to build and test your application, you can use the AWS Toolkit.
The AWS Toolkit is an open source plug-in for popular IDEs that uses the SAM CLI to build and deploy serverless applications on AWS. The AWS Toolkit also adds a simplified step-through debugging experience for Lambda function code. See the following links to get started.

• PyCharm
• IntelliJ
• VS Code
• Visual Studio

Before getting too invested in AWS SAM, take a look at what the Serverless Framework can do.

https://sanderknape.com/2018/02/comparing-aws-sam-with-serverless-framework/

Deploy the sample application

The Serverless Application Model Command Line Interface (SAM CLI) is an extension of the AWS CLI that adds functionality for building and testing Lambda applications. It uses Docker to run your functions in an Amazon Linux environment that matches Lambda. It can also emulate your application's build environment and API.

To use the SAM CLI, you need the following tools.

• Python 3 installed
• Docker (if you would like to run local tests) - Install Docker community edition
• AWS & AWS SAM CLIs (configured with your credentials) - https://github.com/ayoung012/awscli-sam-venv

You must create access keys for use with the awscli.

The SAM CLI uses an Amazon S3 bucket to store your application's deployment artifacts. If you don't have a bucket suitable for this purpose, create one. Replace BUCKET_NAME in the commands in this section with a unique bucket name.

aws s3 mb s3://BUCKET_NAME

Configure the CloudFormation

First update the ImageBucketName in template.yaml to a unique, AWS wide name.

Take a look through the template to understand the resources it will deploy.

Take a look at some articles to get a clearer picture of what this template is doing. https://medium.com/carsales-dev/api-gateway-with-aws-sam-template-c05afdd9cafe

The Serverless Application Model is helpful, but hardly complete.

A more complete reference is the Resource and Property Type Reference in the CloudFormation User Guide

Firstly, we must build the Lambda layers, as sam does not support this yet, and is not actively being worked on.

./build_layers.sh

This process is built on the premise of this single layer creation technique. https://github.com/ayoung012/awslambda-matplotlib-layer

Packaging and Deployment

Then to prepare the application for deployment, use the sam package command.

sam package \
    --output-template-file packaged.yaml \
    --s3-bucket BUCKET_NAME

The SAM CLI creates deployment packages, uploads them to the S3 bucket, and creates a new version of the template that refers to the artifacts in the bucket.

To deploy the application, use the sam deploy command.

sam deploy \
    --template-file packaged.yaml \
    --region ap-southeast-2 \
    --stack-name awssam-s3-pyplot \
    --capabilities CAPABILITY_IAM

After deployment is complete you can run the following command to retrieve the API Gateway Endpoint URL:

aws cloudformation describe-stacks \
    --stack-name awssam-s3-pyplot \
    --query 'Stacks[].Outputs' \
    --output table

To deploy static resources like index.html to the hosted public bucket, use the aws s3 cli.

aws s3 cp static/* s3://<ImageBucketName here>/

Use the SAM CLI to build and test locally with Docker

Build your application with the sam build command.

sam build

The SAM CLI installs dependencies defined in python_plotter/requirements.txt, creates a deployment package, and saves it in the .aws-sam/build folder.

Test a single function by invoking it directly with a test event. An event is a JSON document that represents the input that the function receives from the event source. Test events are included in the events folder in this project.

Run functions locally and invoke them with the sam local invoke command.

sam local invoke PythonPlotterFunction --event events/event.json

The SAM CLI can also emulate your application's API. Use the sam local start-api to run the API locally on port 3000.

sam local start-api
curl http://localhost:3000/

The SAM CLI reads the application template to determine the API's routes and the functions that they invoke. The Events property on each function's definition includes the route and method for each path.

      Events:
        PythonPlotter:
          Type: Api
          Properties:
            Path: /generate_plot
            Method: get

Add a resource to your application

The application template uses AWS Serverless Application Model (AWS SAM) to define application resources. AWS SAM is an extension of AWS CloudFormation with a simpler syntax for configuring common serverless application resources such as functions, triggers, and APIs. For resources not included in the SAM specification, you can use standard AWS CloudFormation resource types.

Fetch, tail, and filter Lambda function logs

To simplify troubleshooting, SAM CLI has a command called sam logs. sam logs lets you fetch logs generated by your deployed Lambda function from the command line. In addition to printing the logs on the terminal, this command has several nifty features to help you quickly find the bug.

NOTE: This command works for all AWS Lambda functions; not just the ones you deploy using SAM.

sam logs -n HelloWorldFunction --stack-name awssam-s3-pyplot --tail

You can find more information and examples about filtering Lambda function logs in the SAM CLI Documentation.

Unit tests

Tests are defined in the tests folder in this project. Use PIP to install the pytest and run unit tests.

pip install pytest pytest-mock --user
python -m pytest tests/ -v

Cleanup

To delete the sample application and the bucket that you created, use the AWS CLI.

aws cloudformation delete-stack --stack-name awssam-s3-pyplot
aws s3 rb s3://BUCKET_NAME

Resources

See the AWS SAM developer guide for an introduction to SAM specification, the SAM CLI, and serverless application concepts.

Next, you can use AWS Serverless Application Repository to deploy ready to use Apps that go beyond hello world samples and learn how authors developed their applications: AWS Serverless Application Repository main page