Skill

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).

npx claudepluginhub atc-net/atc-agentic-toolkit --plugin azure

Tool Access

This skill uses the workspace's default tool permissions.

Preview

This skill provides expert guidance for Azure Data Science VM. 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.

SKILL.md

Similar Skills

azure-ml-foundry-workspace

Provides deep-dive reference for Azure ML Workspace architecture, networking, private endpoints, compute clusters/instances, endpoints, managed identities, ACR/storage integration, az ml CLI/PowerShell commands, logs, debugging, and Terraform.

7 files

azure-master

azure-compute

902

Routes Azure VM/VMSS queries to workflows for recommendations, pricing, autoscale, orchestration, connectivity troubleshooting, capacity reservations, and Essential Machine Management.

20 files

azure

mlops-engineer

682

Builds ML pipelines, tracks experiments, and manages model registries with MLflow, Kubeflow, Airflow, SageMaker, and Azure ML. Automates training, deployment, monitoring for MLOps infrastructure.

rmyndharis-antigravity-skills

Stats

Parent Repo Stars1

Parent Repo Forks1

Last CommitApr 3, 2026

Actions

View Source View Plugin View on GitHub View README

Help us improve

Share bugs, ideas, or general feedback.

Azure Data Science VM Skill

How to Use This Skill

IMPORTANT for Agent: This file may be large. Use the Category Index below to locate relevant sections, then use read_file with specific line ranges (e.g., L136-L144) to read the sections needed for the user's question This skill requires network access to fetch documentation content. Use mcp_microsoftdocs:microsoft_docs_fetch to retrieve full articles.

Fallback: Use the built-in WebFetch tool if the Microsoft Learn MCP server is not available.

Category Index

Category	Lines	Description
Troubleshooting	L29-L32	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	L34-L37	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	L39-L43	Designing scalable DSVM-based analytics environments, including architecture patterns, shared VM pools, team workflows, and resource management for data science teams.
Security	L45-L49	Managing identities and credentials for Azure DSVMs, including shared identity setup, managed identities, and securing secrets with Azure Key Vault.
Configuration	L51-L63	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	L65-L68	Using MLflow on Azure DSVMs to track experiments, log metrics/artifacts, and integrate runs with Azure Machine Learning for centralized experiment management
Deployment	L70-L74	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
Review data platform tools on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-data-platforms?view=azureml-api-2
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