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Expert guidance for Azure Data Science VMs: troubleshooting, configuration, deployment (Bicep/ARM), security, and integrations like MLflow and Key Vault.
Provides concise, action-oriented guidance for agents and engineers working with Azure Data Science Virtual Machines (DSVMs). Covers common troubleshooting, architecture and design patterns for team environments, security best practices (managed identities, Key Vault), configuration of preinstalled ML tools, and deployment using infrastructure-as-code. It points agents to Microsoft Learn references for deep dives.
Use when provisioning, troubleshooting, or migrating DSVMs, setting up GPU/Jupyter environments, integrating MLflow or Key Vault, or when creating IaC templates (Bicep/ARM) for DSVMs. Also helpful for agents that need quick documentation lookups from Microsoft Learn.
Agents with web-fetch or docs connectors (e.g., microsoftdocs fetchers, fetch_webpage, Claude/Copilot-like coding assistants) will get the most value.
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