This is a sample template for botmakerd - Below is a brief explanation of what we have generated for you:
.
├── README.md <-- This instructions file
├── event.json <-- API Gateway Proxy Integration event payload
├── webhook <-- Source code for a lambda function
│ ├── __init__.py
│ ├── app.py <-- Lambda function code
│ ├── requirements.txt <-- Lambda function code
├── template.yaml <-- SAM Template
└── tests <-- Unit tests
└── unit
├── __init__.py
└── test_handler.py
- AWS CLI already configured with Administrator permission
- Python 3 installed
- Docker installed
Invoking function locally using a local sample payload
sam local invoke WebHookFunction --event event.json
Invoking function locally through local API Gateway
sam local start-api
If the previous command ran successfully you should now be able to hit the following local endpoint to invoke your function http://localhost:3000/webhook
SAM CLI is used to emulate both Lambda and API Gateway locally and uses our template.yaml
to understand how to bootstrap this environment (runtime, where the source code is, etc.) - The following excerpt is what the CLI will read in order to initialize an API and its routes:
...
Events:
WebHook:
Type: Api # More info about API Event Source: https://github.com/awslabs/serverless-application-model/blob/master/versions/2016-10-31.md#api
Properties:
Path: /webhook
Method: get
AWS Lambda Python runtime requires a flat folder with all dependencies including the application. SAM will use CodeUri
property to know where to look up for both application and dependencies:
...
WebHookFunction:
Type: AWS::Serverless::Function
Properties:
CodeUri: webhook/
...
Firstly, we need a S3 bucket
where we can upload our Lambda functions packaged as ZIP before we deploy anything - If you don't have a S3 bucket to store code artifacts then this is a good time to create one:
aws s3 mb s3://BUCKET_NAME
Next, run the following command to package our Lambda function to S3:
sam package \
--output-template-file packaged.yaml \
--s3-bucket REPLACE_THIS_WITH_YOUR_S3_BUCKET_NAME
Next, the following command will create a Cloudformation Stack and deploy your SAM resources.
sam deploy \
--template-file packaged.yaml \
--stack-name botmakerd \
--capabilities CAPABILITY_IAM
See Serverless Application Model (SAM) HOWTO Guide for more details in how to get started.
After deployment is complete you can run the following command to retrieve the API Gateway Endpoint URL:
aws cloudformation describe-stacks \
--stack-name botmakerd \
--query 'Stacks[].Outputs[?OutputKey==`WebHookApi`]' \
--output table
To simplify troubleshooting, SAM CLI has a command called sam logs. sam logs lets you fetch logs generated by your 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 WebHookFunction --stack-name botmakerd --tail
You can find more information and examples about filtering Lambda function logs in the SAM CLI Documentation.
Next, we install test dependencies and we run pytest
against our tests
folder to run our initial unit tests:
pip install pytest pytest-mock --user
python -m pytest tests/ -v
In order to delete our Serverless Application recently deployed you can use the following AWS CLI Command:
aws cloudformation delete-stack --stack-name botmakerd
Here are a few things you can try to get more acquainted with building serverless applications using SAM:
- Uncomment lines on
app.py
- Build the project with
sam build --use-container
- Invoke with
sam local invoke WebHookFunction --event event.json
- Update tests
- Create a catch all resource (e.g. /webhook/{proxy+}) and return the name requested through this new path
- Update tests
- Enable step-through debugging docs for supported runtimes
Next, you can use AWS Serverless Application Repository to deploy ready to use Apps that go beyond webhook world samples and learn how authors developed their applications: AWS Serverless Application Repository main page
AWS Lambda requires a flat folder with the application as well as its dependencies in deployment package. When you make changes to your source code or dependency manifest, run the following command to build your project local testing and deployment:
sam build
If your dependencies contain native modules that need to be compiled specifically for the operating system running on AWS Lambda, use this command to build inside a Lambda-like Docker container instead:
sam build --use-container
By default, this command writes built artifacts to .aws-sam/build
folder.
All commands used throughout this document
# Generate event.json via generate-event command
sam local generate-event apigateway aws-proxy > event.json
# Invoke function locally with event.json as an input
sam local invoke WebHookFunction --event event.json
# Run API Gateway locally
sam local start-api
# Create S3 bucket
aws s3 mb s3://BUCKET_NAME
# Package Lambda function defined locally and upload to S3 as an artifact
sam package \
--output-template-file packaged.yaml \
--s3-bucket REPLACE_THIS_WITH_YOUR_S3_BUCKET_NAME
# Deploy SAM template as a CloudFormation stack
sam deploy \
--template-file packaged.yaml \
--stack-name botmakerd \
--capabilities CAPABILITY_IAM
# Describe Output section of CloudFormation stack previously created
aws cloudformation describe-stacks \
--stack-name botmakerd \
--query 'Stacks[].Outputs[?OutputKey==`WebHookApi`]' \
--output table
# Tail Lambda function Logs using Logical name defined in SAM Template
sam logs -n WebHookFunction --stack-name botmakerd --tail