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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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Implementing a Version Control System for AWS QuickSight

Xebia

Introduction In today’s data-driven world, business intelligence tools are indispensable for organizations aiming to make informed decisions. Implementing a version control system for AWS QuickSight can significantly enhance collaboration, streamline development processes, and improve the overall governance of BI projects.

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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

Traditionally, building frontend and backend applications has required knowledge of web development frameworks and infrastructure management, which can be daunting for those with expertise primarily in data science and machine learning. Choose the us-east-1 AWS Region from the top right corner. Choose Manage model access.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

Building cloud infrastructure based on proven best practices promotes security, reliability and cost efficiency. To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. This systematic approach leads to more reliable and standardized evaluations.

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Software infrastructure 2.0: a wishlist

Erik Bernhardsson

Software infrastructure (by which I include everything ending with *aaS, or anything remotely similar to it) is an exciting field, in particular because (despite what the neo-luddites may say) it keeps getting better every year! Anyway, I feel like this applies to like 90% of software infrastructure products. Ephemeral resources.

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Discover, Protect and Respond with AWS and Prisma Cloud

Prisma Clud

Organizations are increasingly turning to cloud providers, like Amazon Web Services (AWS), to address these challenges and power their digital transformation initiatives. However, the vastness of AWS environments and the ease of spinning up new resources and services can lead to cloud sprawl and ongoing security risks.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

For example, an AI-powered productivity tool for an ecommerce company might feature dedicated interfaces for different roles, such as content marketers and business analysts. Before migrating any of the provided solutions to production, we recommend following the AWS Well-Architected Framework. seconds.