AWS | REST API With FaunaDB

This example demonstrates how to setup a RESTful Web Service allowing you to create, list, get, update and delete Todos. FaunaDB is used to store the data.

Clone This Example

Step #1 - npm install serverless -g
Step #2 - serverless install -u https://github.com/serverless/examples/tree/master/aws-python-rest-api-with-faunadb -n  aws-python-rest-api-with-faunadb

Serverless REST API

This example demonstrates how to setup a RESTful Web Services allowing you to create, list, get, update and delete Todos. FaunaDB is used to store the data.

Structure

This service has a separate directory for all the todo operations. For each operation exactly one file exists e.g. todos/delete.py. In each of these files there is exactly one function defined.

The idea behind the todos directory is that in case you want to create a service containing multiple resources e.g. users, notes, comments you could do so in the same service. While this is certainly possible you might consider creating a separate service for each resource. It depends on the use-case and your preference.

Use-cases

  • API for a Web Application
  • API for a Mobile Application

FaunaDB Secret

Visit https://fauna.com/serverless-cloud-sign-up to obtain a FAUNADB_SECRET to use in serverless.yml.

Setup

With your FaunaDB Secret in hand, set it in serverless.yml

  environment:
    FAUNADB_SECRET: YOUR-SECRET-HERE

To avoid the error message DistutilsOptionError: must supply either home or prefix/exec-prefix -- not both first is necessary create a python virtual environment

virtualenv -p `which python` venv

source venv/bin/activate

In order to make it easy to package in this example we're using the node plugin serverless-python-requirements, so install it with

npm install

Deploy

In order to deploy the endpoint simply run

serverless deploy

The expected result should be similar to:

Serverless: Installing required Python packages...
Serverless: Linking required Python packages...
Serverless: Packaging service...
Serverless: Unlinking required Python packages...
Serverless: Uploading CloudFormation file to S3...
Serverless: Uploading service .zip file to S3 (2.33 MB)...
Serverless: Updating Stack...
Serverless: Checking Stack update progress...
......................................
Serverless: Stack update finished...
Serverless: Removing old service versions...
Service Information
service: serverless-rest-api-with-faunadb
stage: dev
region: us-east-1
api keys:
  None
endpoints:
  POST - https://bo19b9b32h.execute-api.us-east-1.amazonaws.com/dev/todos
  GET - https://bo19b9b32h.execute-api.us-east-1.amazonaws.com/dev/todos
  GET - https://bo19b9b32h.execute-api.us-east-1.amazonaws.com/dev/todos/{id}
  PUT - https://bo19b9b32h.execute-api.us-east-1.amazonaws.com/dev/todos/{id}
  DELETE - https://bo19b9b32h.execute-api.us-east-1.amazonaws.com/dev/todos/{id}
functions:
  create: serverless-rest-api-with-faunadb-dev-create
  list: serverless-rest-api-with-faunadb-dev-list
  get: serverless-rest-api-with-faunadb-dev-get
  update: serverless-rest-api-with-faunadb-dev-update
  delete: serverless-rest-api-with-faunadb-dev-delete

Setup schema

Before you execute any command, first you have to setup a FaunaDB schema with the command:

serverless invoke --function schema

Usage

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

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": "159546695821033477", "checked": true, "updatedAt": 1479139961304}, {"text": "Learn Serverless", "id": "159547069624745989", "createdAt": 1479139943241, "checked": false, "updatedAt": 1479139943241}]

Get one Todo

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

Example Result:

{"text": "Learn Serverless", "id": "159547069624745989", "createdAt": 1479138570824, "checked": false, "updatedAt": 1479138570824}

Update a Todo

# Replace the <id> part with a real id from your todos class
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": "159547069624745989", "createdAt": 1479138570824, "checked": true, "updatedAt": 1479138570824}

Delete a Todo

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

No output

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.

view on Github

Latest commit b2f54ec on Sep 24, 2017

New to serverless?

To get started, pop open your terminal & run:

npm install serverless -g