serverless-workshop: A Python repository from sejalv

Serverless REST + DDB Workshop

1. Initial Setup

Quick Setup (prereq: npm)

npm install -g serverless

Detailed Setup Instructions here

2. Hello World Tutorial

Basic project setup, test and deployment

3. Todos app

A CRUD application with a dockerized environment to test AWS services locally. Python for services and DynamoDB for database.

Project Structure:

Mono-repo style, i.e. service + IaaC

├──app/
    ├── __init__.py
    ├── create.py
    ├── delete.py
    ├── get.py
    ├── list.py
    ├── update.py
    ├── tests
    │   ├── __init__.py
    │   ├── conftest.py
    │   └── test_create.py
    └── utils
        ├── __init__.py
        ├── config.py
        └── helpers.py
├──.env
├──Dockerfile
├──docker-compose.yml
├──requirements.txt
├──serverless.yml

app/: Each CRUD function (create, retrieve/get, update, delete) is executed by AWS Lambda, and associated with an API endpoint.
app/tests/: Tests for Lambda handlers. Also includes conftest.py for pytest fixtures, that help in mocking or configuring your environment.
app/utils/: Helpers functions
serverless.yml: Serverless configuration for the service (or app). Includes IaaC to generate AWS components (resources), and attach functions for Lambda handlers, among other things.
docker-compose.yml: includes
- the default template from LocalStack, an open-source framework that mimics AWS enviroment closely on your local setup
- the build using lambci's Docker image to run and test the service locally.

4. Starting the Dev environment

docker-compose build

docker-compose up

NOTE: Build only if there's any change.

5. Tests

docker-compose run app pytest tests/ -s -vv

On the container for app, all the tests located within the app/tests/ directory will run. This will also generate the AWS resources locally, via app/tests/conftest.py (eg. ddb_tbl fixture creates the DDB table serverless-workshop-rest-ddb-test).

aws --endpoint-url=http://localhost:4566 ddb select serverless-workshop-rest-ddb-test

Querying locally to check if the table is created. Also, creates an entry from the test_create.py test.

6. Deploy

Optional Setup:

aws sso login --profile <profile-name>

yawsso

In order to deploy the endpoint simply run

serverless deploy --stage <dev/stg>

This converts your serverless.yml config to a CloudFormation stack, and packages your service and dependencies The expected result should be similar to:

Serverless: Packaging service…
Serverless: Uploading CloudFormation file to S3…
Serverless: Uploading service .zip file to S3…
Serverless: Updating Stack…
Serverless: Checking Stack update progress…
Serverless: Stack update finished…

Service Information
service: serverless-rest-api-with-dynamodb
stage: dev
region: eu-central-1
api keys:
  None
endpoints:
  POST - https://XXXXXXX.execute-api.us-east-1.amazonaws.com/dev/todos
  GET - https://XXXXXXX.execute-api.us-east-1.amazonaws.com/dev/todos
  GET - https://XXXXXXX.execute-api.us-east-1.amazonaws.com/dev/todos/{id}
  PUT - https://XXXXXXX.execute-api.us-east-1.amazonaws.com/dev/todos/{id}
  DELETE - https://XXXXXXX.execute-api.us-east-1.amazonaws.com/dev/todos/{id}
functions:
  serverless-rest-api-with-dynamodb-dev-update: arn:aws:lambda:eu-central-1:XXXXXXX:function:serverless-rest-api-with-dynamodb-dev-update
  serverless-rest-api-with-dynamodb-dev-get: arn:aws:lambda:eu-central-1:XXXXXXX:function:serverless-rest-api-with-dynamodb-dev-get
  serverless-rest-api-with-dynamodb-dev-list: arn:aws:lambda:eu-central-1:XXXXXXX:function:serverless-rest-api-with-dynamodb-dev-list
  serverless-rest-api-with-dynamodb-dev-create: arn:aws:lambda:eu-central-1:XXXXXXX:function:serverless-rest-api-with-dynamodb-dev-create
  serverless-rest-api-with-dynamodb-dev-delete: arn:aws:lambda:eu-central-1:XXXXXXX:function:serverless-rest-api-with-dynamodb-dev-delete

7. Usage (Post-Deployment)

You can create, retrieve, update, or delete todos with the following commands:

via API Endpoints:

Create a Todo

curl -X POST https://XXXXXXX.execute-api.us-east-1.amazonaws.com/dev/todos --data '{ "text": "Learn Serverless" }'

No output

List all Todos

curl https://XXXXXXX.execute-api.us-east-1.amazonaws.com/dev/todos

Example output:

[{"text":"Deploy my first service","id":"ac90feaa11e6-9ede-afdfa051af86","checked":true,"updatedAt":},{"text":"Learn Serverless","id":"206793aa11e6-9ede-afdfa051af86","createdAt":,"checked":false,"updatedAt":}]%

Get one Todo

# Replace the <id> part with a real id from your todos table
curl https://XXXXXXX.execute-api.us-east-1.amazonaws.com/dev/todos/<id>

Example Result:

{"text":"Learn Serverless","id":"ee6490d0-aa11e6-9ede-afdfa051af86","createdAt":,"checked":false,"updatedAt":}%

Update a Todo

# Replace the <id> part with a real id from your todos table
curl -X PUT https://XXXXXXX.execute-api.us-east-1.amazonaws.com/dev/todos/<id> --data '{ "text": "Learn Serverless", "checked": true }'

Example Result:

{"text":"Learn Serverless","id":"ee6490d0-aa11e6-9ede-afdfa051af86","createdAt":,"checked":true,"updatedAt":}%

Delete a Todo

# Replace the <id> part with a real id from your todos table
curl -X DELETE https://XXXXXXX.execute-api.us-east-1.amazonaws.com/dev/todos/<id>

via local CLI:

serverless invoke --function create --stage dev

No output

8. Finally, destroy

Don't forget to remove the app from your AWS environment. Here's a clean way to do it with serverless

serverless destroy --stage <dev/stg>

Further Enhancements

Scaling

AWS Lambda

By default, AWS Lambda limits the total concurrent executions across all functions within a given region to 100. The default limit is a safety limit that protects you from costs due to potential runaway or recursive functions during initial development and testing. To increase this limit above the default, follow the steps in To request a limit increase for concurrent executions.

DynamoDB

When you create a table, you specify how much provisioned throughput capacity you want to reserve for reads and writes. DynamoDB will reserve the necessary resources to meet your throughput needs while ensuring consistent, low-latency performance. You can change the provisioned throughput and increasing or decreasing capacity as needed.

This is can be done via settings in the serverless.yml.

  ProvisionedThroughput:
    ReadCapacityUnits: 1
    WriteCapacityUnits: 1

In case you expect a lot of traffic fluctuation we recommend to checkout this guide on how to auto scale DynamoDB https://aws.amazon.com/blogs/aws/auto-scale-dynamodb-with-dynamic-dynamodb/

sejalv/serverless-workshop