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

Xebia

Use identity and access management (AWS IAM). You can compare these credentials with the root credentials of a Linux system or the root account for your AWS account. You could use AWS IAM, and this will give us the ability to be more least privileged. For this, we can use a provisioner lambda function.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. This strategy results in more robust, versatile, and efficient applications that better serve diverse user needs and business objectives. In this post, we provide an overview of common multi-LLM applications.

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AWS Lambda Enhances Local IDE Experience With AI Support

Dzone - DevOps

AWS Lambda is enhancing the local IDE experience to make developing Lambda-based applications more efficient. These new features enable developers to author, build, debug, test, and deploy Lambda applications seamlessly within their local IDE using Visual Studio Code (VS Code).

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Building Resilient Public Networking on AWS: Part 4

Xebia

Region Evacuation with static anycast IP approach Welcome back to our comprehensive "Building Resilient Public Networking on AWS" blog series, where we delve into advanced networking strategies for regional evacuation, failover, and robust disaster recovery. Find the detailed guide here.

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

AWS Machine Learning - AI

AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. The following figure illustrates the high-level design of the solution.

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

AWS Machine Learning - AI

While organizations continue to discover the powerful applications of generative AI , adoption is often slowed down by team silos and bespoke workflows. It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker.