Amazon EKS
PulseAugur coverage of Amazon EKS — every cluster mentioning Amazon EKS across labs, papers, and developer communities, ranked by signal.
- used by Amazon SageMaker HyperPod 90%
- instance of Amazon Elastic Kubernetes Service 90%
- used by Ray 90%
- affiliated with Amazon SageMaker HyperPod 70%
- used by Traefik Proxy 70%
- affiliated with Ray 70%
- used by AWS Load Balancer Controller 70%
- used by SageMaker HyperPod 70%
- affiliated with SageMaker HyperPod 50%
11 day(s) with sentiment data
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AWS Bedrock AgentCore adds Web Answer for synthesized, cited search results
AWS has introduced Web Answer on Amazon Bedrock AgentCore, a new feature that synthesizes answers to natural language questions and provides cited source URLs in a single tool call. This managed connector simplifies the…
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CloudPouch 2.0 released to cut AWS costs via resource cleanup
A new version of the CloudPouch tool, CloudPouch 2.0, has been released to help users identify and reduce unnecessary AWS spending. The tool focuses on cleaning up unused or oversized resources, such as unattached EBS v…
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DevOps engineer builds self-hosted ChatGPT platform on laptop
A DevOps engineer has developed a self-hosted AI platform named OzAI, designed to run open-weight LLMs on a laptop. The platform utilizes Ollama for model execution, LiteLLM as an API gateway with features like virtual …
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MLOps Series Explores Productionizing Machine Learning Systems
This series of articles delves into the intricacies of MLOps, focusing on the art of moving machine learning systems into production. The content covers various aspects, including MLOps maturity models, advanced techniq…
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NVIDIA Nemotron 3.5 Super VL model available on AWS for agentic AI
NVIDIA has released its Nemotron 3.5 Super VL model, a 120 billion parameter mixture-of-experts model designed for agentic AI applications. This model combines reasoning, tool use, and multimodal understanding capabilit…
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AWS boosts AI agent capabilities with new integrations and model access · 3 sources tracked
AWS is enhancing its machine learning offerings to support agentic AI development. MoEngage has integrated over 400 APIs into agent tools using AgentCore Gateway, leveraging AWS services. Additionally, NVIDIA's Nemotron…
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NVIDIA Nemotron 3.5 Super VL model deployed on AWS for agentic AI
NVIDIA has released its Nemotron 3.5 Super VL model, a 120B-parameter mixture-of-experts model capable of multimodal understanding and agentic workflows. This model integrates reasoning and tool use with text, image, do…
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AWS simplifies distributed AI training with new Ray Train DLCs on EKS
AWS has released new Deep Learning Containers (DLCs) for Ray Train, simplifying distributed AI model training on Amazon Elastic Kubernetes Service (EKS). These pre-built containers integrate essential components like Py…
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AWS SageMaker AI introduces Multi-Turn Reinforcement Learning for sequential tasks
Amazon SageMaker AI now supports Multi-Turn Reinforcement Learning (MTRL), a method for training models on tasks requiring sequential actions. This approach uses the overall success or failure of a task as the training …
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49 Cloud and AI Deadlines Through 2026 Detailed in New List
A comprehensive list outlines 49 cloud and AI-related deadlines extending through 2026. The compilation includes critical dates for major AI models like OpenAI and Gemini, alongside updates for cloud services such as AW…
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Deploy FastMCP Server to AWS EKS for Claude Code Integration
This tutorial details how to deploy a Python-based Model Context Protocol (MCP) server, built with FastMCP, onto Amazon Elastic Kubernetes Service (EKS). The process involves building a Docker image, pushing it to Amazo…
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Deploying MCP Servers on Kubernetes with Streamable HTTP
This article details how to deploy MCP servers on Kubernetes, focusing on adapting servers that initially use stdio for communication to a networked environment. It explains that the key is to change the server's transp…
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Ray LLM Containers Simplify Dual-GPU Node LLM Deployment on Amazon EKS
Ray LLM Deep Learning Containers offer a new way to deploy large language models across two GPU nodes on Amazon EKS. This setup separates prefill and decode nodes while presenting them behind a single OpenAI-compatible …
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LLM inference efficiency explored via quantization, memory, parallelism, and scheduling
Researchers are exploring various methods to enhance the efficiency and scalability of Large Language Model (LLM) inference. One approach focuses on energy efficiency through quantization techniques, demonstrating signi…
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Terraform simplifies AWS infrastructure for complex AI applications
This article explores how HashiCorp Terraform can be used to provision and manage scalable AI infrastructure on AWS. It highlights the complexity of setting up AI systems, which often require GPU compute, data pipelines…
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RAG platform scaling solution uses event-driven queues and Spot Compute
This article details an event-driven architecture for scaling Retrieval-Augmented Generation (RAG) platforms, particularly for handling large volumes of enterprise documents. The proposed solution uses decoupled asynchr…
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AWS SageMaker HyperPod enables shared GPU cluster access for AI teams
AWS has introduced Amazon SageMaker HyperPod, a new service designed to help organizations manage large-scale GPU clusters for generative AI workloads. This service addresses the challenge of multiple teams needing shar…
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Argus system predicts cloud spot interruptions to save training progress
Researchers have developed Argus, a Kubernetes operator designed to mitigate data loss during training on cloud computing platforms like Amazon EKS. The system aims to predict and handle interruptions in services such a…
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AWS and NVIDIA enhance AI agent memory with S3 Vectors integration
AWS and NVIDIA have collaborated to enhance AI agent memory capabilities. The NVIDIA NeMo Agent Toolkit (NAT) can now integrate with Amazon S3 Vectors, a feature of Amazon Simple Storage Service, to provide persistent a…
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AWS details multi-environment access for Anthropic's Claude Platform
Amazon Web Services (AWS) has detailed a method for implementing multi-environment access to the Claude Platform on AWS (CPonAWS). This approach allows for inference from production workloads on AWS, developer laptops f…