azure-data-science-vm
Provides expert knowledge on managing, configuring, and deploying Azure Data Science VMs.
Install
mkdir -p .claude/skills/azure-data-science-vm && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/11666" && unzip -o skill.zip -d .claude/skills/azure-data-science-vm && rm skill.zipInstalls to .claude/skills/azure-data-science-vm
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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).Key capabilities
- →Troubleshoot common Azure Data Science VM issues
- →Receive guidance for upgrading Azure Data Science VMs
- →Design scalable DSVM-based analytics environments
- →Manage identities and credentials for Azure DSVMs
- →Deploy Azure Data Science VMs using infrastructure-as-code
- →Integrate MLflow on Azure DSVMs for experiment tracking
How it works
The skill provides expert guidance for Azure Data Science Virtual Machines development by combining local quick-reference content with remote documentation fetching capabilities.
Inputs & outputs
When to use azure-data-science-vm
- →Troubleshooting DSVM environments
- →Deploying DSVM via Bicep
- →Configuring MLflow on DSVM
About this skill
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), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: If
metadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools 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_fetchwith query stringfrom=learn-agent-skill. Returns Markdown. - Fallback: Use
fetch_webpagewith query stringfrom=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
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 |
When not to use it
- →For Azure Virtual Machines
- →For Azure Machine Learning
- →For Azure Databricks
Limitations
- →Not for Azure HDInsight
- →Guidance is specific to Azure Data Science Virtual Machines
How it compares
This skill centralizes expert knowledge and documentation fetching for Azure Data Science Virtual Machines, offering specific guidance for various development tasks.
Compared to similar skills
azure-data-science-vm side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| azure-data-science-vm (this skill) | 0 | 4mo | No flags | Advanced |
| cost-optimization | 1 | 5mo | No flags | Intermediate |
| cfo | 0 | 7mo | Review | Advanced |
| cloud-cost-management | 7 | 5mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
More by MicrosoftDocs
View all by MicrosoftDocs →You might also like
cost-optimization
wshobson
Optimize cloud costs through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.
cfo
brencon
> A PhD-grade financial analyst specializing in cloud infrastructure costs, FinOps, and strategic financial planning for software projects.
cloud-cost-management
aj-geddes
Optimize and manage cloud costs across AWS, Azure, and GCP using reserved instances, spot pricing, and cost monitoring tools.
azure-functions
aj-geddes
Create serverless functions on Azure with triggers, bindings, authentication, and monitoring. Use for event-driven computing without managing infrastructure.
cloud-architect
sickn33
Expert cloud architect specializing in AWS/Azure/GCP multi-cloud infrastructure design, advanced IaC (Terraform/OpenTofu/CDK), FinOps cost optimization, and modern architectural patterns. Masters serverless, microservices, security, compliance, and disaster recovery. Use PROACTIVELY for cloud architecture, cost optimization, migration planning, or multi-cloud strategies.
azure-deployment-preflight
github
Performs comprehensive preflight validation of Bicep deployments to Azure, including template syntax validation, what-if analysis, and permission checks. Use this skill before any deployment to Azure to preview changes, identify potential issues, and ensure the deployment will succeed. Activate when users mention deploying to Azure, validating Bicep files, checking deployment permissions, previewing infrastructure changes, running what-if, or preparing for azd provision.