Expert knowledge for Azure Deployment Environments development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring ADE catalogs, RBAC/managed identities, Git/ARM catalogs, custom images, or CI/CD environment automation, and other Azure Deployment Environments related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Dev Box (use azure-dev-box), Azure Integration Environments (use azure-integration-environments), Azure Managed Applications (use azure-managed-applications).
npx skills add https://github.com/MicrosoftDocs/Agent-Skills --skill azure-deployment-environments
This skill provides expert guidance for Azure Deployment Environments. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
> 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), 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:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Lines | Description |
|----------|-------|-------------|
| Troubleshooting | L37-L41 | Diagnosing and resolving custom image deployment failures in Azure Deployment Environments, including common error patterns, logs to inspect, and remediation steps. |
| Best Practices | L42-L46 | Guidance on organizing and structuring Azure Deployment Environments catalogs, including repo layout, template grouping, naming, and governance for scalable, maintainable catalogs. |
| Decision Making | L47-L51 | Guidance on planning for Azure Deployment Environments entering maintenance mode, including impact, timelines, alternatives, and migration/transition considerations. |
| Architecture & Design Patterns | L52-L56 | Guidance on designing resilient, scalable Azure Deployment Environments architectures, including fault tolerance, high availability, redundancy, and best practices for robust environment design. |
| Limits & Quotas | L57-L61 | Requesting and managing quota increases for Azure Deployment Environments resource limits, including how to handle capacity constraints and raise support requests. |
| Security | L62-L69 | RBAC and identity setup for Deployment Environments: planning and assigning roles, configuring managed identities, and authenticating to the REST APIs. |
| Configuration | L70-L81 | Defining ADE environments and types, configuring Git catalogs and ARM provisioning, using the devcenter CLI, auto-deletion, and environment variables for custom images. |
| Integrations & Coding Patterns | L82-L88 | Using Azure Developer CLI and ADE CLI to create environments, build custom container images, and manage custom image workflows for Azure Deployment Environments |
| Deployment | L89-L93 | Using Azure Deployment Environments with CI/CD tools (Azure Pipelines, GitHub Actions) to automate environment creation, updates, and deployments from templates. |
| Topic | URL |
|-------|-----|
| Diagnose custom image deployment failures in Azure Deployment Environments | https://learn.microsoft.com/en-us/azure/deployment-environments/troubleshoot-custom-image-logs-errors |
| Topic | URL |
|-------|-----|
| Structure Azure Deployment Environments catalogs efficiently | https://learn.microsoft.com/en-us/azure/deployment-environments/best-practice-catalog-structure |
| Topic | URL |
|-------|-----|
| Plan for Azure Deployment Environments maintenance mode | https://learn.microsoft.com/en-us/azure/deployment-environments/maintenance-mode |
| Topic | URL |
|-------|-----|
| Design resilient Azure Deployment Environments architectures | https://learn.microsoft.com/en-us/azure/deployment-environments/concept-reliability-deployment-environments |
| Topic | URL |
|-------|-----|
| Request quota increases for ADE resource limits | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-request-quota-increase |
| Topic | URL |
|-------|-----|
| Plan Azure RBAC roles for Deployment Environments | https://learn.microsoft.com/en-us/azure/deployment-environments/concept-deployment-environments-role-based-access-control |
| Authenticate to Azure Deployment Environments REST APIs | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-authenticate |
| Configure managed identity for Azure Deployment Environments dev center | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-configure-managed-identity |
| Assign RBAC roles for Azure Deployment Environments access | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-manage-deployment-environments-access |
| Topic | URL |
|-------|-----|
| Define Azure Deployment Environments with environment.yaml schema | https://learn.microsoft.com/en-us/azure/deployment-environments/concept-environment-yaml |
| Configure Git-based catalogs for Azure Deployment Environments | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-configure-catalog |
| Configure dev center environment types in Azure Deployment Environments | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-configure-devcenter-environment-types |
| Configure project-level environment types in Azure Deployment Environments | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-configure-project-environment-types |
| Install and use the devcenter Azure CLI extension | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-install-devcenter-cli-extension |
| Configure automatic deletion for ADE environments | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-schedule-environment-deletion |
| Provision dev center and project via ARM template | https://learn.microsoft.com/en-us/azure/deployment-environments/quickstart-create-dev-center-project-azure-resource-manager |
| Reference ADE CLI environment variables for custom images | https://learn.microsoft.com/en-us/azure/deployment-environments/reference-deployment-environment-variables |
| Topic | URL |
|-------|-----|
| Create ADE environments using Azure Developer CLI | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-configure-azure-developer-cli-deployment-environments |
| Use custom container images with Azure Deployment Environments | https://learn.microsoft.com/en-us/azure/deployment-environments/how-to-configure-extensibility-model-custom-image |
| Use ADE CLI commands for custom image workflows | https://learn.microsoft.com/en-us/azure/deployment-environments/reference-deployment-environment-cli |
| Topic | URL |
|-------|-----|
| Integrate ADE with Azure Pipelines for CI/CD | https://learn.microsoft.com/en-us/azure/deployment-environments/tutorial-deploy-environments-in-cicd-azure-devops |
| Deploy Azure environments via GitHub CI/CD pipelines | https://learn.microsoft.com/en-us/azure/deployment-environments/tutorial-deploy-environments-in-cicd-github |
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Take microsoftdocs/azure-deployment-environments from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.