- Overview
- Infrastructure References Catalog
- AI Training Example Catalog
- Infrastructure Validation Catalog
- Utilities Catalog
- AI Infrastructure MCP Server
- Contributing
- Trademarks
- Contributors
This repository collects architectural guidance and AI training examples meant to run on Azure AI Infrastructure.
This includes infrastructure examples and real use case scenarios on Azure AI Infrastructure involving different orchestration solutions:
For each scenario and architecture, the repository will include storage recommendations among Azure Storage services (Azure Blob Storage, Azure Managed Lustre, Azure NetApp Files), monitoring and observability.
- Azure CycleCloud Slurm Workspace AI Cluster - Prototypes for the creation of Azure CycleCloud Slurm Workspace AI Clusters using CLI deployment
- Azure Kubernetes Service Cluster - Deployment script for AKS cluster
- MegatronLM GPT3-175B with Slimpajama 627B dataset - Example of an end-to-end training workflow based on MegatronLM, including data pre-processing from Slimpajama 627B dataset
- LLM Foundry MPT Training - Example of an end-to-end training workflow of Mosaic Pretrained Transformer (MPT) model on C4 dataset, based on LLM Foundry
- NCCL All-reduce - Testing distributed communication performance for multi-GPU training
- Node Health Checks - Automated system validation and monitoring for compute nodes
- Thermal Test - GPU thermal stress testing and monitoring
- FIO Storage Performance Testing - I/O performance testing with Azure Container Storage, blobfuse, and other storage types
- Node Labeler - Automatically labels nodes with host information and InfiniBand HCA GUIDs for network topology awareness
- Torset Labeler - Discovers and labels nodes with torset (InfiniBand switching domain) information using SHARP topology discovery
The AI Infrastructure MCP Server is a Model Context Protocol (MCP) server that provides tools for managing and monitoring Slurm-based HPC clusters. It enables AI assistants like GitHub Copilot to interact with cluster infrastructure through a standardized protocol, offering capabilities such as:
- Slurm job management - Query job status, accounting data, and cluster information
- System monitoring - Check systemd services and logs across cluster nodes
- File operations - Read and search files on the cluster
- Azure VM metadata - Retrieve physical hostnames and VMSS information
Currently targeting Slurm clusters with SSH-based connectivity. See the full documentation for setup and usage details.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.
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