Amazon Q Developer でマネジメントコンソールの情報に基づいたチャット回答をサポートしました
2024.11.28こんにちは、森田です。
以下のアップデートで、Amazon Q Developer にてマネジメントコンソールの情報に基づいたチャット回答をサポートしました。
マネジメントコンソールの情報に基づいたチャット回答
ユーザが開いているマネジメントコンソールの情報にアクセスできるため、ユーザがより欲しい情報を回答してくれるようになります。
例えば、ユーザが AWS Lambda のコンソールを開いている時に「Bedrockを使ってみたい」と入力すると、
Amazon Q は、「ユーザは AWS Lambda を使って Bedrock を使いたい」と解釈をして適切な回答をしてくれます。
やってみた
今回は、実際に以下のパターンを試してみたいと思います。
- AWS Lambda のコンソールから各サービスの利用方法を聞く
- Amazon Bedrock
- Amazon S3
- Amazon RDS のコンソールから各サービスの利用方法を聞く
- Amazon Bedrock
AWS Lambda のコンソールから各サービスの利用方法を聞く
以下のように AWS Lambda のコンソールを開き、Amazon Q を起動します。
Amazon Bedrock
シンプルに「use bedrock here」と入力してみます。
すると以下のような結果が回答されました。
I apologize, but I cannot recommend using Amazon Bedrock in your current Lambda function environment. Based on your current location in the AWS Lambda console for the Asia Pacific (Tokyo) region, Amazon Bedrock is not directly integrated with Lambda in that region.
However, if you're interested in exploring Amazon Bedrock capabilities, I can provide some general guidance:
Region Availability: Amazon Bedrock is available in select regions. You may need to switch to a supported region like US East (N. Virginia) or US West (Oregon) to use Bedrock services.
Service Integration: To use Bedrock with Lambda, you would typically need to:
- Ensure your Lambda function has the necessary permissions to access Bedrock.
- Use the AWS SDK in your Lambda code to make API calls to Bedrock.
Use Cases: Bedrock can be useful for tasks like natural language processing, text generation, and other AI/ML applications.
Security Considerations:
- Always follow the principle of least privilege when granting permissions.
- Be cautious about data handling, especially with sensitive information.
- Getting Started: If you decide to use Bedrock, you'll need to:
- Request access to the foundation models you want to use.
- Set up the appropriate IAM roles and policies.
- Familiarize yourself with the Bedrock API and SDK.
- Alternative Considerations: Depending on your specific needs, you might also consider other AWS AI services that are more widely available across regions.
For the most up-to-date information on regional availability, features, and integration with Lambda, I recommend checking the official AWS documentation for Amazon Bedrock and Lambda. If you have specific requirements or use cases in mind, it would be beneficial to consult with AWS support or a solutions architect to design the most appropriate and secure solution for your needs.
Sources
[1] [Feature support by AWS Region in Amazon Bedrock - Amazon Bedrock] (https://docs.aws.amazon.com/bedrock/latest/userguide/features-regions.html)
[3] [Getting started with Amazon Bedrock - Amazon Bedrock] (https://docs.aws.amazon.com/bedrock/latest/userguide/getting-started.html)
[6] [Supported regions for Amazon Bedrock Agents - Amazon Bedrock] (https://docs.aws.amazon.com/bedrock/latest/userguide/agents-supported.html)
要約すると、東京リージョンだと利用するモデルの制限があるため、オススメしないとのことでした。
確かに、現在のリージョンに基づいて回答してくれていますね。
Amazon S3
今度は、「integrate with any S3 bucket.」と入力してみます。
To integrate your Lambda function with an S3 bucket, we'll set up an S3 event trigger that invokes your Lambda function when objects are uploaded to the bucket. Here's a >step-by-step guide to accomplish this task:
- Create or Select an S3 Bucket
- Navigate to the S3 console at https://s3.console.aws.amazon.com/
- Either create a new bucket or select an existing one you want to use as the trigger for your Lambda function.
- Configure Lambda Function Permissions
- Go to the Lambda console at https://console.aws.amazon.com/lambda/
- Select your function
- In the "Configuration" tab, click on "Permissions"
- Edit the execution role to include S3 read permissions
- Add a resource-based policy to allow S3 to invoke your function
- Set Up S3 Event Notification
- Return to the S3 console
- Select your bucket
- Go to the "Properties" tab
- Scroll down to "Event Notifications" and click "Create event notification"
- Configure the event:
- Choose a name for your event
- Select the event types (e.g., "All object create events")
- Choose "Lambda Function" as the destination
- Select your Lambda function
- Test the Integration
- Upload a file to your S3 bucket
- Check the CloudWatch logs for your Lambda function to verify it was triggered
- Implement Error Handling
- Update your Lambda function code to include proper error handling
- Consider implementing retries for transient failures
- Monitor and Optimize
- Set up CloudWatch alarms to monitor function errors and latency
- Adjust the function's memory and timeout settings as needed
By completing these steps, you'll have successfully integrated your Lambda function with an S3 bucket. The function will now be triggered automatically when new objects are uploaded to the specified bucket. Remember to follow the principle of least privilege when setting up permissions, and always test in a non-production environment before deploying to production.
Sources
[1] [aws-s3-lambda - AWS Solutions Constructs] (https://docs.aws.amazon.com/solutions/latest/constructs/aws-s3-lambda.html)
[3] [Invoke a Lambda function from an Amazon S3 trigger - AWS Lambda] (https://docs.aws.amazon.com/lambda/latest/dg/example_serverless_S3_Lambda_section.html)
[6] [Invoke a Lambda function from an Amazon S3 trigger - Amazon Simple Storage Service] (https://docs.aws.amazon.com/AmazonS3/latest/API/s3_example_serverless_S3_Lambda_section.html)
こちらも問題なく、AWS LambdaでS3を利用する方法を返してくれました。
Amazon RDS のコンソールから各サービスの利用方法を聞く
今度は、 Amazon RDS のコンソールを開き、Amazon Q を起動します。
Amazon Bedrock
「use bedrock here」で聞くと以下のように回答してくれます。
I apologize, but I'm not able to use Amazon Bedrock in the current RDS console context. Amazon Bedrock is a separate service for building generative AI applications, while you're currently in the Amazon RDS (Relational Database Service) console.
If you'd like to use Amazon Bedrock, you would need to navigate to the Bedrock service in the AWS Management Console. Here are some steps you can take:
- Exit the RDS console.
- Go to the main AWS Management Console.
- Search for "Amazon Bedrock" in the services search bar.
- Select Amazon Bedrock from the search results.
Once in the Amazon Bedrock console, you'll be able to explore its features for building, training, and deploying large language models and other generative AI capabilities.
If you have any specific questions about using Amazon Bedrock or how it might integrate with your RDS databases, I'd be happy to provide more information. Alternatively, if you have any other questions about your current RDS setup, please feel free to ask.
Sources
[1] [Creating and connecting to a DB instance for Amazon RDS Custom for SQL Server - Amazon Relational Database Service] (https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/custom-creating-sqlserver.html)
[3] [Creating an Amazon RDS DB instance - Amazon Relational Database Service] (https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_CreateDBInstance.html)
[6] [Configuring an Amazon RDS DB instance - Amazon Relational Database Service] (https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_RDS_Configuring.html)
RDSの情報に基づいて回答してくれてますね。
まとめ
あまり触ったことのないサービスをマネジメントコンソールで操作する際に便利な機能となっています。
英語でメッセージを送る必要はありますが、無料で使えますので、ぜひ試してみてください。
