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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

For instance, consider an AI-driven legal document analysis system designed for businesses of varying sizes, offering two primary subscription tiers: Basic and Pro. It also allows for a flexible and modular design, where new LLMs can be quickly plugged into or swapped out from a UI component without disrupting the overall system.

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Introducing AWS MCP Servers for code assistants (Part 1)

AWS Machine Learning - AI

Were excited to announce the open source release of AWS MCP Servers for code assistants a suite of specialized Model Context Protocol (MCP) servers that bring Amazon Web Services (AWS) best practices directly to your development workflow. This post is the first in a series covering AWS MCP Servers.

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Breaking AWS Lambda: Chaos Engineering for Serverless Devs

Dzone - DevOps

Our "serverless" order processing system built on AWS Lambda and API Gateway was humming along, handling 1,000 transactions/minute. A sudden spike in traffic caused Lambda timeouts, API Gateway threw 5xx errors, and customers started tweeting, Why cant I check out?! Then, disaster struck.

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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. You can use AWS services such as Application Load Balancer to implement this approach. API Gateway also provides a WebSocket API. These components are illustrated in the following diagram.

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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. This allows teams to focus more on implementing improvements and optimizing AWS infrastructure. This systematic approach leads to more reliable and standardized evaluations.

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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

Companies of all sizes face mounting pressure to operate efficiently as they manage growing volumes of data, systems, and customer interactions. Users can access these AI capabilities through their organizations single sign-on (SSO), collaborate with team members, and refine AI applications without needing AWS Management Console access.