1---2name: azure-data-science-vm3description: 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).4---5# Azure Data Science Virtual Machines Skill67This 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.89## How to Use This Skill1011> **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 file1213This skill requires **network access** to fetch documentation content:14- **Preferred**: Use `mcp_microsoftdocs:microsoft_docs_fetch`. Returns Markdown.15- **Fallback**: Use `WebFetch`. Returns Markdown.1617## Category Index1819| Category | Lines | Description |20|----------|-------|-------------|21| Troubleshooting | L31-L35 | 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. |22| Decision Making | L36-L40 | Guidance for upgrading Azure Data Science VMs from Ubuntu 18.04 to 20.04, including migration steps, compatibility considerations, and preserving tools/configurations. |23| Architecture & Design Patterns | L41-L46 | Designing scalable DSVM-based analytics environments, including architecture patterns, shared VM pools, team workflows, and resource management for data science teams. |24| Security | L47-L52 | Managing identities and credentials for Azure DSVMs, including shared identity setup, managed identities, and securing secrets with Azure Key Vault. |25| Configuration | L53-L65 | 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. |26| Integrations & Coding Patterns | L66-L70 | Using MLflow on Azure DSVMs to track experiments, log metrics/artifacts, and integrate runs with Azure Machine Learning for centralized experiment management |27| Deployment | L71-L75 | How to deploy Azure Data Science VMs using infrastructure-as-code, including Bicep and ARM templates, parameters, and configuration best practices. |2829### Troubleshooting30| Topic | URL |31|-------|-----|32| 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 |3334### Decision Making35| Topic | URL |36|-------|-----|37| 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 |3839### Architecture & Design Patterns40| Topic | URL |41|-------|-----|42| 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 |43| 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 |4445### Security46| Topic | URL |47|-------|-----|48| 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 |49| 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 |5051### Configuration52| Topic | URL |53|-------|-----|54| 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 |55| 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 |56| 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 |57| 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 |58| 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 |59| 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 |60| 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 |61| 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 |62| 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 |6364### Integrations & Coding Patterns65| Topic | URL |66|-------|-----|67| 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 |6869### Deployment70| Topic | URL |71|-------|-----|72| 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 |73| 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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