Secure API Gateway Endpoints with Custom Authorizers

Lab Steps

Logging in to the Amazon Web Services Console
Custom Authorizer Use Cases
Creating a Simple API Gateway Endpoint
Implementing Authorization Logic in Lambda
Creating a new Custom Authorizer
Enabling the API Gateway Custom Authorizer
Testing the Secured Endpoint
Validate AWS Lab

The hands-on lab is part of these learning paths

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Ready for the real environment experience?

Time Limit1h 30m
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Lab Overview

Amazon API Gateway offers several native authorization mechanisms, such as managed API keys, IAM Roles, and custom authorizers. API Keys (with the help of Usage Plans) can help manage custom throttling and quotas for your API consumers. IAM is a good choice when your consumers require access to AWS resources and you need to manage permissions on a per-user basis. However, custom authorizers give you much more flexibility. With custom authorizers, you can implement any 3rd-party integration and generate very granular authorization policies.

In this Lab, we will learn how to implement a custom authorizer in AWS Lambda to secure your API Gateway Resources.

Lab Objectives

Upon completion of this Lab you will be able to:

  • Understand API Gateway request authorization
  • Explain the advantages of using custom authorizers in API Gateway
  • Create Lambda functions to implement custom authorizers using AWS Lambda blueprints
  • Test custom authorizers using methods appropriate at each stage of deployment

Lab Prerequisites

You should be familiar with:

  • AWS Lambda basics
  • API Gateway basics

The following content can be used to fulfill the prerequisites: 


January 10th, 2019 - Added a validation Lab Step to check the work you perform in the Lab

Nov. 15th, 2018 - Lab completely updated including easier to follow instructions, screenshots to match the latest experience, and removal of security warnings in the AWS Console.

Environment before
Environment after

About the Author

Alex is an Italian Software Engineer with a great passion for web technologies and music.

He spent the last 5 years building web products and deepening his knowledge on full stack web development and software design, with a main focus on frontend and UX.

Despite being a passionate coder, Alex worked hard on his software and sound engineering background, which provides him the tools to deal with multimedia, signal processing, machine learning, AI and many interesting topics related to math and data science.

Indeed, he had the opportunity to study and live in a very young and motivating environment in Bologna and Milan, two of the biggest and oldest Italian Universities. These experiences lead him to work on several projects involving robotics, machine intelligence, music semantic analysis and modern web development.

Alex is currently a Senior Software Engineer at Cloud Academy, a position that gave him the possibility to discover the Cloud world and exploit its potential as a web developer and data scientist.