Remove Applications Remove Authentication Remove Lambda
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Cross-Stack RDS User Provisioning and Schema Migrations with AWS Lambda

Xebia

However, other databases like MySQL also have an internal authentication method. Since we dont want to use the root credentials, we need a user to access the database through our application. For this, we can use a provisioner lambda function. This lambda function creates the local users in the database.

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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

The workflow includes the following steps: The process begins when a user sends a message through Google Chat, either in a direct message or in a chat space where the application is installed. Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Building generative AI applications presents significant challenges for organizations: they require specialized ML expertise, complex infrastructure management, and careful orchestration of multiple services. Building a generative AI application SageMaker Unified Studio offers tools to discover and build with generative AI.

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Securing S3 Downloads with ALB and Cognito Authentication

Xebia

For this, you will need authentication and authorization. Authentication vs Authorization Authentication is all about identifying who you are. I am using an Application Load Balancer to invoke a Lambda function. In this case, we can use the native Cognito integration of the application load balancer.

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

AWS Machine Learning - AI

Recognizing this need, we have developed a Chrome extension that harnesses the power of AWS AI and generative AI services, including Amazon Bedrock , an AWS managed service to build and scale generative AI applications with foundation models (FMs). The following diagram illustrates the architecture of the application.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

Large-scale data ingestion is crucial for applications such as document analysis, summarization, research, and knowledge management. The service users permissions are authenticated using IAM Identity Center, an AWS solution that connects workforce users to AWS managed applications like Amazon Q Business.

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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

It integrates with existing applications and includes key Amazon Bedrock features like foundation models (FMs), prompts, knowledge bases, agents, flows, evaluation, and guardrails. Solution overview Amazon Bedrock provides a governed collaborative environment to build and share generative AI applications within SageMaker Unified Studio.