# Simplify and support your TorchServe workloads using Ray Serve Deep Learning Containers

DevFeed: [Simplify and support your TorchServe workloads using Ray Serve Deep Learning Containers](<https://devfeed.tech/articles/simplify-and-support-your-torchserve-workloads-using-ray-serve-deep-learning-containers-4741.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/machine-learning/simplify-and-support-your-torchserve-workloads-using-ray-serve-deep-learning-containers/>)

Author: Ananth Raghavendra

Published: 2026-09-09T15:51:29Z

Content type: tutorial

Language: en

Sources: [Artificial Intelligence](<https://devfeed.tech/sources/artificial-intelligence.md>)

Topics: [Inference](<https://devfeed.tech/topics/inference.md>), [model-deployment](<https://devfeed.tech/topics/model-deployment.md>), [Amazon Elastic Kubernetes Service](<https://devfeed.tech/topics/amazon-elastic-kubernetes-service.md>), [Containers](<https://devfeed.tech/topics/containers.md>), [vlm](<https://devfeed.tech/topics/vlm.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [PyTorch](<https://devfeed.tech/topics/pytorch.md>)

Tags: [amazon-eks](<https://devfeed.tech/tags/amazon-eks.md>), [containers](<https://devfeed.tech/tags/containers.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [inference](<https://devfeed.tech/tags/inference.md>), [intermediate-200](<https://devfeed.tech/tags/intermediate-200.md>), [pytorch](<https://devfeed.tech/tags/pytorch.md>), [technical-how-to](<https://devfeed.tech/tags/technical-how-to.md>), [vulnerabilities](<https://devfeed.tech/tags/vulnerabilities.md>)

## AI overview

The article introduces AWS Ray Serve Deep Learning Containers as a maintained, pre-tested inference option for teams moving from unmaintained TorchServe workloads. It demonstrates deploying a vision-language model on Amazon EKS using a single GPU node.

## Source excerpt

TorchServe is no longer maintained, leaving teams to own the entire GPU inference stack. The AWS Ray Serve Deep Learning Container is a supported, pre-tested container with the framework, GPU drivers, and serving layer already assembled. This post walks through deploying a vision-language model on Amazon EKS using the Ray Serve DLC on a single GPU node.