Remove Architecture Remove Authentication Remove Lambda
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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

By implementing this architectural pattern, organizations that use Google Workspace can empower their workforce to access groundbreaking AI solutions powered by Amazon Web Services (AWS) and make informed decisions without leaving their collaboration tool. This request contains the user’s message and relevant metadata.

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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning - AI

The solution also uses Amazon Cognito user pools and identity pools for managing authentication and authorization of users, Amazon API Gateway REST APIs, AWS Lambda functions, and an Amazon Simple Storage Service (Amazon S3) bucket. The following diagram illustrates the architecture of the application.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. It contains services used to onboard, manage, and operate the environment, for example, to onboard and off-board tenants, users, and models, assign quotas to different tenants, and authentication and authorization microservices.

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Serverless, it can help you brew beer

Xebia

This allows you to use a Lambda function to use business logic to decide whether the call can be performed. The documentation clearly states that you should not use the usage plans for authentication. Based on those questions, you might pivot your solution’s architecture. Another other option would be a custom authorizer.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. The solution incorporates the following key features: Using a Retrieval Augmented Generation (RAG) architecture, the system generates a context-aware detailed assessment.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

Solution overview The following architecture diagram represents the high-level design of a solution proven effective in production environments for AWS Support Engineering. It enables end-user authentication and streamlines access management. The Process Data Lambda function redacts sensitive data through Amazon Comprehend.

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Create generative AI agents that interact with your companies’ systems in a few clicks using Amazon Bedrock in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Lets look at an example solution for implementing a customer management agent: An agentic chat can be built with Amazon Bedrock chat applications, and integrated with functions that can be quickly built with other AWS services such as AWS Lambda and Amazon API Gateway. For Authentication method , choose API Keys (Max.