--- title: "Building Blocks for Foundation Model Training and Inference on AWS" url: https://daily.dev/posts/building-blocks-for-foundation-model-training-and-inference-on-aws-e3dmqot6y source_url: https://huggingface.co/blog/amazon/foundation-model-building-blocks type: article source: "Hugging Face" published: 2026-05-11T23:20:17.889Z updated: 2026-05-11T23:20:56.019Z tags: ["ai", "aws", "kubernetes", "pytorch"] reading_time: 21 upvotes: 1 comments: 0 language: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Building Blocks for Foundation Model Training and Inference on AWS **[Hugging Face](https://daily.dev/sources/huggingface)** · 21 min read · 1 upvotes · 0 comments ## Summary A technical deep-dive into the AWS infrastructure stack for foundation model training and inference, covering four layers: compute infrastructure (EC2 P-instances with NVIDIA H100/H200/Blackwell GPUs, EFA networking, tiered storage), resource orchestration (Slurm and Kubernetes via SageMaker HyperPod), the ML software stack (CUDA, NCCL, PyTorch, vLLM, SGLang, Megatron), and observability (Prometheus, Grafana, DCGM-Exporter). The post explains how scaling has evolved beyond pre-training to include post-training and test-time compute, and how all three regimes share the same infrastructure requirements. It details NVLink/EFA bandwidth specs across GPU generations, UltraCluster and UltraServer architectures, gang scheduling challenges in Kubernetes, and GPU health monitoring patterns. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Powering innovation at scale: How AWS is tackling AI infrastructure challenges](https://daily.dev/posts/powering-innovation-at-scale-how-aws-is-tackling-ai-infrastructure-challenges-vlbr4rjyk) · AWS · 1 upvotes · 0 comments --- Tags: [#ai](https://daily.dev/tags/ai), [#aws](https://daily.dev/tags/aws), [#kubernetes](https://daily.dev/tags/kubernetes), [#pytorch](https://daily.dev/tags/pytorch) [View this post on daily.dev](https://daily.dev/posts/building-blocks-for-foundation-model-training-and-inference-on-aws-e3dmqot6y)