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azure-data-science-vm

Expert knowledge for Azure Data Science Virtual Machines development including troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when managing DSVM images/tools, IaC deployment (Bicep/ARM), Key Vault secrets, MLflow, or GPU/Jupyter issues, and other Azure Data Science Virtual Machines related development tasks. Not for Azure Virtual Machines (use azure-virtual-machines), Azure Machine Learning (use azure-machine-learning), Azure Databricks (use azure-databricks), Azure HDInsight (use azure-hdinsight).

MicrosoftDocs/Agent-Skills

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SKILL.md7.0 KB

SKILL.md（原文）

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Azure Data Science Virtual Machines Skill

This skill provides expert guidance for Azure Data Science Virtual Machines. Covers troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.

How to Use This Skill

IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g., L35-L120), use read_file with the specified lines. For categories with file links (e.g., [security.md](security.md)), use read_file on the linked reference file

IMPORTANT for Agent: If metadata.generated_at is more than 3 months old, suggest the user pull the latest version from the repository. If mcp_microsoftdocs tools are not available, suggest the user install it: Installation Guide

This skill requires network access to fetch documentation content:

Preferred: Use mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.
Fallback: Use fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.

Category Index

Category	Lines	Description
Troubleshooting	L35-L39	Diagnosing and resolving common Azure Data Science VM issues, including VM creation, package/environment errors, Jupyter access, GPU/driver problems, and performance or connectivity failures.
Decision Making	L40-L44	Guidance for upgrading Azure Data Science VMs from Ubuntu 18.04 to 20.04, including migration steps, compatibility considerations, and preserving tools/configurations.
Architecture & Design Patterns	L45-L50	Designing scalable DSVM-based analytics environments, including architecture patterns, shared VM pools, team workflows, and resource management for data science teams.
Security	L51-L56	Managing identities and credentials for Azure DSVMs, including shared identity setup, managed identities, and securing secrets with Azure Key Vault.
Configuration	L57-L69	Details of all preinstalled tools, frameworks, languages, and images on Azure DSVMs, including ML/deep learning, data ingestion, dev/productivity tools, and release/version info.
Integrations & Coding Patterns	L70-L74	Using MLflow on Azure DSVMs to track experiments, log metrics/artifacts, and integrate runs with Azure Machine Learning for centralized experiment management
Deployment	L75-L79	How to deploy Azure Data Science VMs using infrastructure-as-code, including Bicep and ARM templates, parameters, and configuration best practices.

Troubleshooting

Topic	URL
Troubleshoot known issues on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/reference-known-issues?view=azureml-api-2

Decision Making

Topic	URL
Migrate DSVM from Ubuntu 18.04 to 20.04	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/ubuntu-upgrade?view=azureml-api-2

Architecture & Design Patterns

Topic	URL
Design team analytics environments with DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-enterprise-overview?view=azureml-api-2
Architect shared DSVM pools for analytics teams	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-pools?view=azureml-api-2

Security

Topic	URL
Configure common identity for multiple DSVMs	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-common-identity?view=azureml-api-2
Secure DSVM credentials with managed identities and Key Vault	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-secure-access-keys?view=azureml-api-2

Configuration

Topic	URL
Use preinstalled ML tools on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-data-science?view=azureml-api-2
Check deep learning frameworks on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-deep-learning-frameworks?view=azureml-api-2
Identify development tools available on DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-development?view=azureml-api-2
Use data ingestion tools on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-ingestion?view=azureml-api-2
Review programming languages preinstalled on DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-languages?view=azureml-api-2
Leverage productivity tools on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-productivity?view=azureml-api-2
Reference tools installed on Ubuntu DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/reference-ubuntu-vm?view=azureml-api-2
Review Azure DSVM release changes and versions	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/release-notes?view=azureml-api-2
Review preinstalled tools on Azure DSVM images	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/tools-included?view=azureml-api-2

Integrations & Coding Patterns

Topic	URL
Track DSVM experiments with MLflow and Azure ML	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/how-to-track-experiments?view=azureml-api-2

Deployment

Topic	URL
Deploy Azure DSVM using Bicep templates	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tutorial-bicep?view=azureml-api-2
Deploy Azure DSVM with ARM templates	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tutorial-resource-manager?view=azureml-api-2

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azure-active-directory-b2c

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Expert knowledge for Azure Active Directory B2C development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building B2C user flows/custom policies, configuring IdPs/MFA, securing APIs, automating CI/CD, or monitoring with Sentinel, and other Azure Active Directory B2C related development tasks. Not for Azure Role-based access control (use azure-rbac), Azure Information Protection (use azure-information-protection), Azure Security (use azure-security), Azure Sentinel (use azure-sentinel).

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