Recently, Amazon Q Developer announced expanded support for account resource awareness with Amazon Q in the AWS Management Console along 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, and the general availability of the AWS Chatbot integration with Microsoft Teams and Slack.
Expanded account resource awareness 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, you can ask more complex questions about your AWS account resources. I will show a few examples in this section of this post.
For our first example, 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?”
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 another example, 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.”
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?”
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.
Outside of the examples above, here are some other prompts/examples that can be explored for the expanded support:
– “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.
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 example, 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”.
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.
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, 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.
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