AWS DevOps Blog

Five ways Amazon Q simplifies AWS CloudFormation development


As a builder, AWS CloudFormation provides a reliable way for you to model, provision, and manage AWS and third-party resources by treating infrastructure as code. First-time and experienced users of CloudFormation can often encounter some challenges when it comes to development of templates and stacks. CloudFormation offers a vast library of over 1,250 resource types covering AWS services, and supports numerous features and functionalities in both the construction of a template, as well as the deployment of a stack using that template. The broad array of options at one’s disposal provides a broad landscape to navigate.

In 2023, AWS introduced a new generative AI-powered assistant, Amazon Q. Amazon Q is the most capable generative AI-powered assistant for accelerating software development and leveraging companies’ internal data. Amazon Q Developer can answer questions about AWS architecture, best practices, documentation, support, and more. When used in an integrated development environment (IDE), Amazon Q Developer additionally provides software development assistance, including code explanation, code generation, and code improvements such as debugging and optimization.

In this blog post, we will show you five ways Amazon Q Developer can help you work with CloudFormation for template code generation, querying CloudFormation resource requirements, explaining existing template code, understanding deployment options and issues, and querying CloudFormation documentation.


Amazon Q can be interacted with in different ways. The first way is native integration within the AWS Console. When logged into the console, you will see a “Q” logo. Click on it to open a chat window, and then you can begin asking questions to Amazon Q without any setup.

You can also interact with Amazon Q Developer after following these instructions to set it up in your Interactive Development Environment (IDE).

1. Template Code Generation

The foundational element of any CloudFormation stack begins with a template that describes your infrastructure as code, in either a JSON or YML format. The anatomy of what comprises a stack can be found here. Creating a template requires knowledge of the template format, as well as the proper structure of each CloudFormation resource that you include in the ‘Resources’ section.

With Amazon Q, you can generate a template from natural language without having to look up the particular definition of each resource.

Template code Generation using Amazon Q

Figure 1: Template code Generation using Amazon Q

In Figure 1 above, I asked Amazon Q if it could provide me with a CloudFormation template with Lambda code in python to list all EBS volumes in a region. It generated sample code that provides the minimum template I would need to create it. It also added the IAM role needed to execute the Lambda code. Finally, it included documentation links that can be reference for further usage.

With a single message to Amazon Q, I am off and running in seconds, ready to deploy my first CloudFormation stack.

2. Understanding CloudFormation Resource Properties

Another area where Q can help if you are already familiar with the structure of a resource, is by informing you of resource properties and their significance.

In the next use case, I encountered an issue with my template where certain properties were missing that are required for the resource. With Amazon Q, I can quickly understand the required property, and what it defines for my resource.

Stack Events & Q information on Required Parameters

Stack Events & Q information on Required Parameters

Figure 2: Stack Events & Q information on Required Parameters

Since the CloudFormation Events tab indicated that the error was a missing resource property, I asked Amazon Q to help me understand why the property was required, and what it defines. Now, without having to dig through documentation, I can make sure that my template code includes DefaultCacheBehavior and what that will define for my resource.

3. Explaining Existing Template Code

A benefit of Amazon CloudFormation and Infrastructure as Code is that templates allow developers to share and distribute both snippets and entire stacks as pre-defined JSON or YML files. Template reusability can help with the development of new systems, or the augmentation of existing ones – without needing to do any of the template development yourself.

In this example, I have borrowed a template snippet from the AWS documentation for a DynamoDB table. I have copied and pasted this template into my IDE.

In my IDE, I have integrated Amazon Q. As shown in Figure 3, I can highlight a specified section of my template code, and then ask Amazon Q to explain what it is doing for us.

Explaining CloudFormation code by Amazon Q

Figure 3: Explaining CloudFormation code by Amazon Q

After asking Amazon Q to ‘Explain selected code’, I am given a detailed description of my highlighted template snippet. Q tells me that this is an Auto Scaling policy for a DynamoDB Table write capacity. It informs me what resource type it is (AWS::ApplicationAutoScaling::ScalingPolicy), and also describes what the function of that resource is, in the context of my DynamoDB Table. Next, it gives me detailed bullet points explaining all of the parameters of the resource definition, and how that impacts my table as well. It then concludes with a summary of the highlighted code that is easily digestible and understandable to the reader, and even offers to provide more information if needed.

In just one simple question to Amazon Q, I have quickly gone from copy and pasting existing code to now understanding its usage and functionality.

4. Understanding Deployment Issues

Sometimes developers may encounter issues when creating, updating or deleting CloudFormation stacks. When you come across errors with your AWS CloudFormation stack, you can ask Amazon Q to help you find the source of the problems.

Reasoning stack failures by Amazon Q
Figure 4: Reasoning stack failures by Amazon Q

Amazon Q answered why my CloudFormation stack failed to deploy and gave me different ways to check and fix the issues before trying again.

5. Querying CloudFormation Documentation & Functionality

Sometimes developers need to query CloudFormation documentation and functionality to build templates for their use case. Amazon Q can help with these requests straight from IDE. One such example is where developers ask Amazon Q to explain how to make sure my database is not deleted when a CloudFormation stack is deleted. In Figure 5, Amazon Q recommends few ways to make sure the RDS database is not deleted.

Query Amazon Q for CloudFormation documentation

Figure 5: Query Amazon Q for CloudFormation documentation

Sometimes developers need deploy the CloudFormation stack across regions and accounts which can be achieved by using StackSets. In the following example, I asked it for help to understand this feature.

Query Amazon Q for CloudFormation StackSets functionality
Figure 6: Query Amazon Q for CloudFormation StackSets functionality

It is also possible to ask Amazon Q for help with the prompts themselves. In the example below, I ask it to provide some hints on what kinds of questions I could ask about CloudFormation.
CloudFormation functionality prompts

Figure 7: CloudFormation functionality prompts

In the example below, I ask one of those questions to dive into stack dependencies.

CloudFormation stack dependencies
Figure 8: CloudFormation stack dependencies


Utilizing Amazon Q allows developers and builders to be more efficient. As a builder you can use Amazon Q in your IDE to create CloudFormation templates and improve existing CloudFormation templates. If you have inherited an existing CloudFormation template, you can use Amazon Q to understand it. Reducing template and stack development time is one exciting way that Amazon Q and Generative AI are enabling customers to move faster.

Ryan Kiel

Ryan Kiel

Ryan Kiel is a Senior Solutions Architect for AWS based out of Virginia. As part of AWS Sports, he helps leagues and franchises with their cloud journey on AWS by leveraging best practices and the newest technology. Outside of work, Ryan is a hockey, golf, and motorsports enthusiast.

Aneesh Varghese

Aneesh Varghese

Aneesh Varghese is a Senior Technical Account Manager at AWS with more than 17 years of Information Technology industry experience. Aneesh supports enterprise customers in cost optimization strategies, providing advocacy and strategic technical guidance to help plan and build solutions using AWS best practices. Outside of work, Aneesh likes to spend time with family, play Basketball and Badminton.

Karthik Chemudupati

Karthik Chemudupati

Karthik Chemudupati is a Principal Technical Account Manager (TAM) with AWS, focused on helping customers achieve cost optimization and operational excellence. He has 20 years of IT experience in software engineering, cloud operations and automations. Karthik joined AWS in 2016 as a TAM and worked with more than dozen Enterprise Customers across US-West. Outside of work, he enjoys spending time with his family.