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AWS Open Source Observability: Visualization and Security Auditing with CloudMapper (Part 1)

Xebia

When it comes to Cloud Observability, several Open Source and proprietary tools have been available over the years. Customer support and available manuals/documentation (current, and on-request). More sophisticated methods of detection, reporting, integrations… But what is the value of Open Source solutions on this topic?

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Netflix OSS and Spring Boot?—?Coming Full Circle

Netflix Tech

Ribbon for load balancing, Eureka for service discovery, and Hystrix for fault tolerance. All of these Netflix libraries and systems were open-sourced around 2012 and are still used by the community to this day. Over time this has become the preferred way for the community to adopt Netflix’s Open Source software.

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

AWS Machine Learning - AI

Load balancer – Another option is to use a load balancer that exposes an HTTPS endpoint and routes the request to the orchestrator. You can use AWS services such as Application Load Balancer to implement this approach. API Gateway also provides a WebSocket API. This logic sits in a hybrid search component.

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Why enterprise CIOs need to plan for Microsoft gen AI

CIO

Generative AI and the specific workloads needed for inference introduce more complexity to their supply chain and how they load balance compute and inference workloads across data center regions and different geographies,” says distinguished VP analyst at Gartner Jason Wong. That’s an industry-wide problem. This isn’t a new issue.

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Build a custom UI for Amazon Q Business

AWS Machine Learning - AI

The workflow includes the following steps: The user accesses the chatbot application, which is hosted behind an Application Load Balancer. Amazon Q returns the response as a JSON object (detailed in the Amazon Q documentation ). sourceAttributions – The source documents used to generate the conversation response.

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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning - AI

With the advancements being made with LLMs like the Mixtral-8x7B Instruct , derivative of architectures such as the mixture of experts (MoE) , customers are continuously looking for ways to improve the performance and accuracy of generative AI applications while allowing them to effectively use a wider range of closed and open source models.

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Enhance conversational AI with advanced routing techniques with Amazon Bedrock

AWS Machine Learning - AI

This post assesses two primary approaches for developing AI assistants: using managed services such as Agents for Amazon Bedrock , and employing open source technologies like LangChain. It is hosted on Amazon Elastic Container Service (Amazon ECS) with AWS Fargate , and it is accessed using an Application Load Balancer.