restful_aurora

Stand up an API to get data from an Aurora database. Commands here are tested on macOS, but should work fine on Linux and should be ok for Windows with adjustments. We'll also deploy a sample employee database, load some data, and connect it to our API.

Get started with Python and Chalice

Setup a Python virtual environment and activate it

virtualenv `which python3` venv
source venv/bin/activate

Install AWS Chalice

Chalice is a microframework for writing serverless apps in python. It allows you to quickly create and deploy applications that use AWS Lambda. It provides:

• A command line tool for creating, deploying, and managing your app
• A decorator based API for integrating with Amazon API Gateway, Amazon S3, Amazon SNS, Amazon SQS, and other AWS services.
• Automatic IAM policy generation

Run this command from the restful_aurora directory

pip install -r requirements.txt

Now, create a new API

chalice new-project restful_aurora_api

enter the restful_aurora_api directory, and issue the following command to deploy the API locally:

chalice local

This will start a basic web server on your local machine and start serving the RESTful endpoint from localhost:8000

Open a new terminal window and use curl to issue a GET request:

curl -x GET http://localhost:8000

Now, you can deploy the API to AWS API Gateway and Lambda with the following command:

chalice deploy

You should see the following when deployment completes successfully:

Creating deployment package.
Creating IAM role: restful_aurora_api-dev
Creating lambda function: restful_aurora_api-dev
Creating Rest API
Resources deployed:
  - Lambda ARN: arn:aws:lambda:us-east-1:477157386854:function:restful_aurora_api-dev
  - Rest API URL: https://3nel6hbk0e.execute-api.us-east-1.amazonaws.com/api/

Now you can test the API with curl:

curl -X GET https://3nel6hbk0e.execute-api.us-east-1.amazonaws.com/api/ 

If all is well, you should see something like this:

{"hello": "world"}

Boom! You deployed API Gateway, Lambda, IAM roles, and all of the configuration to serve a basic RESTful API. Now lets do something more interesting, like accessing a database with that API.

Create an Aurora database called "employees"

Use the AWS Console to create an Aurora-mysql database called "employees."

Create a simple database and load some data

Browse to http://www.jackdb.com and create an account. Jackdb is an online SQL client that we'll use to connect to the employees database. Use Jackdb to establish a connection to the Aurora database and do the following:

1. Use create_employees_table.sql to create a new table
2. Import employees.csv into the table

Adjust your API to connect to the database

You can reference the code in app.py.txt to modify app.py in your restful_aurora_api directory to return a list of employees. Note that you'll have to create several Systems Manager Parameter Store values ahead of time. See https://docs.aws.amazon.com/systems-manager/latest/userguide/systems-manager-paramstore.html or aws ssm help to create values for the database, username, password, etc. per the code in app.py.txt.

Test your API locally

Run chalice local and use the curl command to get a listing of employees in the database. For this to work, you will have to open the security group for your employees database so that you local machine can issue queries against it.

Deploy to API Gateway and Lambda

If your API worked locally, then issue chalice deploy to deploy the new code to your RESTful endpoint. This will update your Lambda function and API Gateway to return the right results.