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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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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Software-as-a-service (SaaS) applications with tenant tiering SaaS applications are often architected to provide different pricing and experiences to a spectrum of customer profiles, referred to as tiers. The user prompt is then routed to the LLM associated with the task category of the reference prompt that has the closest match.

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Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning - AI

Amazon Bedrock Custom Model Import enables the import and use of your customized models alongside existing FMs through a single serverless, unified API. This serverless approach eliminates the need for infrastructure management while providing enterprise-grade security and scalability. 8B 128K model to 8 Units for a Llama 3.1

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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. In the following sections, we explain how to deploy this architecture.

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Extend large language models powered by Amazon SageMaker AI using Model Context Protocol

AWS Machine Learning - AI

We will deep dive into the MCP architecture later in this post. Using a client-server architecture (as illustrated in the following screenshot), MCP helps developers expose their data through lightweight MCP servers while building AI applications as MCP clients that connect to these servers.

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

AWS Machine Learning - AI

Shared components refer to the functionality and features shared by all tenants. API Gateway is serverless and hence automatically scales with traffic. The advantage of using Application Load Balancer is that it can seamlessly route the request to virtually any managed, serverless or self-hosted component and can also scale well.

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Boost productivity by using AI in cloud operational health management

AWS Machine Learning - AI

Event-driven operations management Operational events refer to occurrences within your organization’s cloud environment that might impact the performance, resilience, security, or cost of your workloads. The following diagram illustrates the solution architecture. The full code repository is available in the accompanying GitHub repo.

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