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AWS introduces Ray Serve container for model inference

AWS introduces Ray Serve container for model inference Image: Primary
AWS has introduced a Ray Serve Deep Learning Container for inference workloads, positioning it as a migration option for teams using unmaintained TorchServe. AWS says the image bundles PyTorch, Ray Serve, FastAPI, Uvicorn and GPU-stack dependencies in tested configurations, with separate images for EKS, EC2 and SageMaker. The company demonstrated the GPU image serving Qwen3-VL-2B on a single EKS g5.xlarge node with one NVIDIA A10G GPU. AWS says the containers receive security patches at build time.
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Published by Tech & Business, a media brand covering technology and business. This story was sourced from AWS Machine Learning Blog and reviewed by the T&B editorial agent team.
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