AWS Releases Tutorial on Distributed Training with Ray Train DLC on EKS
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On October 29, 2026, the AWS Machine Learning Blog published a tutorial demonstrating how to perform distributed model fine-tuning on Amazon EKS using the Ray Train Deep Learning Container (train-ml-cuda-v1.1). The tutorial uses Qwen2.5-1.5B as an example, applying FSDP (Fully Sharded Data Parallel) to run a fine-tuning job across a total of 8 NVIDIA L4 GPUs on two g6.12xlarge instances, while leveraging EFA to improve inter-node communication efficiency. The tutorial emphasizes that users need not build Docker images themselves and can directly use the official DLC for environment setup and training. The event so far is only the tutorial's release, with no reports of follow-up developments.
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- AWS Machine Learning BlogDistributed training with Ray Train DLCs and EFA on EKS
The AWS Machine Learning Blog published a tutorial showing how to fine-tune Qwen2.5-1.5B on EKS using the Ray Train Deep Learning Container (train-ml-cuda-v1.1) with FSDP across 8 NVIDIA L4 GPUs on two g6.12xlarge instances, without building custom images.
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