AWS DevOps & Developer Productivity Blog

Expanded resource awareness in Amazon Q Developer

Recently, Amazon Q Developer announced expanded support for account resource awareness with Amazon Q in the AWS Management Console  and the AWS Mobile Application. This is coupled with the general availability of Amazon Q Developer in AWS Chatbot, enabling you to ask questions from Microsoft Teams or Slack. Additionally, Amazon Q will now provide context-aware assistance for your questions about resources in your account depending on where you are in the console. Amazon Q in the console gives you the ability to use natural language with the Amazon Q Developer chat capability to list resources in your AWS account, get specific resource details, and ask about related resources, launched in preview on April 30, 2024.

In this blog, I will highlight the new expanded functionality of this feature in Amazon Q Developer including understanding relationships between account resources, context-awareness, integrations with the AWS Mobile Application, and the general availability of the AWS Chatbot integration with Microsoft Teams and Slack.

Deeper insights into RDS, Lambda, and ECS with Amazon Q Developer

Prior to the launch of the expanded support, you could ask Amazon Q Developer to list resources in your AWS Account with prompts such as “List all my EC2 instances in us-east-1” and the service would list all your Amazon Elastic Compute Cloud (Amazon EC2) instances. Now, with the expanded support, Q now has insights into, specifically, RDS clusters with updates available, SNS topics that invoke a Lambda, and ECS cluster statuses. I will show a use cases in this section.

Let’s start with finding RDS clusters with updates available. Imagine that you’re a developer who is responsible for maintaining code as a part of the software development lifecycle (SDLC) and you frequently use AWS Lambda for development and Amazon Relational Database Service (RDS) in the backend as a part of your development process. With this new update, a developer could open a new Q chat in the AWS Management Console, and enter a prompt such as: “Which RDS clusters are due for an update?”

User entering prompt Amazon Q Developer chat in the AWS management console about listing all RDS clusters that need updates in their account and Amazon Q listing those Databases.

Figure 1: Amazon Q Developer listing RDS clusters needing an update

As a result, the Amazon Q Developer console chat will return a list of all your Amazon RDS clusters that have available updates as shown in Figure 1 above.

Now, for a use case around the Lambda enhancements. Lets you want to update any Lambda functions in your AWS account that had a Simple Notification Service (SNS) topic as a trigger due to moving to a new SNS topic you recently created. To identify which SNS topics are still being used, you could enter a prompt such as “List all the SNS topics that trigger a lambda function.”

User entering prompt Amazon Q Developer chat in the AWS management console about listing all SNS topics that trigger a lambda function and Amazon Q listing the SNS topics as an output.

Figure 2: Amazon Q listing SNS topics that are lambda triggers

As shown in the prior example, Amazon Q Developer was able to identify any SNS topics in the form of Amazon resource name (ARN) that was set to trigger a lambda function in the AWS account as intended.

Additionally, you can ask a follow up question in the same chat to investigate more. You can send a prompt such as “Which lambda function uses the arn:aws:sns:us-east-1:76859XXXX:FailoverHealthcheck SNS topic?”

User entering prompting Amazon Q Developer chat with a follow up question in the AWS management console about which Lambda is associated with an SNS topic.

Figure 3: Asking Q Developer a follow up question about a resource

From Figure 3 above, you can see that there is a Lambda function/endpoint associated with the SNS topic resource that Amazon Q Developer was able to identify.

In addition to the above use cases, you can also ask the following about your ECS clusters:

– “Do I have any ECS clusters with pending tasks?”

– “Are there any ECS clusters in my account with services in DRAINING status?”

Amazon Q Developer understands where you are in the console

Amazon Q Developer in the AWS Management Console now provides context-aware assistance for your questions about resources in your account. This feature allows you to ask questions directly related to the console page you’re viewing, eliminating the need to specify the service or resource in your query. Q Developer uses the current page as additional context to provide more accurate and relevant responses, streamlining your interaction with AWS services and resources.

Prior to the update, a user would have to prompt, “What is the public IPv4 address of my instance i-08ccXXXXXX?”  Now, if you are viewing an EC2 instance in the console and prompt Amazon Q, “What is the public IPv4 address of my instance?” you will not need to specify the instance you are referring to.

User entering prompt Amazon Q Developer chat in the AWS management console about what the IP address is of the instance on the page.

Figure 4: Asking Amazon Q about an EC2 instance being viewed

In figure 4 above, Amazon Q’s console chat was able to use its context-awareness to pick up on what the IPv4 address was on the console page where I was currently working, despite me not specifying which instance I was referring to.

AWS ChatBot can now answer questions about AWS resources in Microsoft Teams and Slack

Recently, we announced the general availability of Amazon Q Developer in AWS Chatbot, which provides answers to customers’ AWS resource related queries in Microsoft Teams and Slack. This gives teams the ability to quickly find relevant resources to troubleshoot issues using natural language queries in the chat channels of Microsoft Teams or Slack.

For a use case with Slack, you could integrate the AWS Chatbot Service with Amazon Q Developer to allow you to enter a prompt in Slack such as “@aws show EC2 instances in running state in us-east-1”.

User entering prompt in slack to ask the AWS Chatbot about EC2 resources and Amazon Q responding

Figure 5: Amazon Q listing all EC2 resources in Slack

As shown in figure 5 above, Amazon Q was able to list all the EC2 resources and place them into a slack channel showing an example of the functionality in action.

Integration of Amazon Q Developer with the AWS Mobile Application

AWS customers using the AWS Console Mobile App (for iOS or Android) can use Amazon Q, ask questions about AWS services, and receive concise, reliable answers in a mobile-friendly user interface with voice input and output capabilities. Similar to the previous use cases above, customers can also chat with Amazon Q about their AWS account resources like asking Q to “List my EC2 instances” on their mobile devices from anywhere.

User asking the AWS mobile application to list their instance

Figure 6: Amazon Q listing all EC2 resources in the AWS Mobile application

As shown above in figure 6, prompting Amazon Q from the AWS mobile application will allow users to get insights similar to use cases shown previously.

Conclusion

Amazon Q Developer has enhanced its cloud resource management capabilities, enabling more intuitive and intelligent interactions with AWS resources. The new features allow developers to ask complex, context-aware questions about their cloud infrastructure directly through the AWS Management Console, AWS Mobile Application, Microsoft Teams, and Slack. Users can now easily discover new details about specific resources with natural language queries that provide precise, contextual information. These improvements represent a significant step forward in simplifying cloud resource management, making it faster and more user-friendly for development teams to understand, track, and maintain their AWS environments. To learn more about chatting with your AWS resources, check out Console documentation and AWS Chatbot documentation.

About the authors

Brendan Jenkins

Brendan Jenkins is a Tech Lead Solutions Architect at Amazon Web Services (AWS) working with Enterprise AWS customers providing them with technical guidance and helping achieve their business goals. He has an area of specialization in DevOps and Machine Learning technology.