Expert knowledge for Azure Reliability development including best practices, decision making, architecture & design patterns, and limits & quotas. Use when designing multi-region Azure apps using zones, AKS, databases, networking, messaging, or Web PubSub, and other Azure Reliability related development tasks. Not for Azure Resiliency (use azure-resiliency), Azure Monitor (use azure-monitor), Azure Service Health (use azure-service-health), Azure Site Recovery (use azure-site-recovery).
npx skills add https://github.com/MicrosoftDocs/Agent-Skills --skill azure-reliability
This skill provides expert guidance for Azure Reliability. Covers best practices, decision making, architecture & design patterns, and limits & quotas. 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 |
|----------|-------|-------------|
| Best Practices | L32-L73 | Patterns and guidance for designing highly available, resilient, and disaster‑ready architectures across many Azure services (AKS, databases, networking, messaging, monitoring, and more). |
| Decision Making | L74-L83 | Guidance on choosing Azure regions and services (regional, zonal, multiregion, nonregional), using region pairs, and designing multi-region architectures for higher reliability. |
| Architecture & Design Patterns | L84-L89 | Designing Azure apps for high availability using zones and multi-region patterns, including zonal vs zone-redundant deployments, hardening strategies, and non-paired region failover. |
| Limits & Quotas | L90-L94 | Guidance on Azure Queue Storage message size limits and designing reliable, scalable Azure Web PubSub apps under service quotas and constraints |
| Topic | URL |
|-------|-----|
| Design resilient clusters in Azure Kubernetes Service | https://learn.microsoft.com/en-us/azure/reliability/reliability-aks |
| Configure reliability for Azure API Center | https://learn.microsoft.com/en-us/azure/reliability/reliability-api-center |
| Build resilient configurations with Azure App Configuration | https://learn.microsoft.com/en-us/azure/reliability/reliability-app-configuration |
| Build resilient configurations with Azure App Configuration | https://learn.microsoft.com/en-us/azure/reliability/reliability-app-configuration |
| Harden Azure App Service Environment reliability | https://learn.microsoft.com/en-us/azure/reliability/reliability-app-service-environment |
| Architect highly available Azure Application Gateway v2 | https://learn.microsoft.com/en-us/azure/reliability/reliability-application-gateway-v2 |
| Design resilient Azure Automation runbooks and recovery | https://learn.microsoft.com/en-us/azure/reliability/reliability-automation |
| Design resilient backup strategies with Azure Backup | https://learn.microsoft.com/en-us/azure/reliability/reliability-backup |
| Design resilient backup strategies with Azure Backup | https://learn.microsoft.com/en-us/azure/reliability/reliability-backup |
| Plan reliability for Azure Bot Service | https://learn.microsoft.com/en-us/azure/reliability/reliability-bot |
| Design resilient Azure Cosmos DB deployments | https://learn.microsoft.com/en-us/azure/reliability/reliability-cosmos-db |
| Design resilient Azure Cosmos DB deployments | https://learn.microsoft.com/en-us/azure/reliability/reliability-cosmos-db |
| Harden Azure Data Factory for outages | https://learn.microsoft.com/en-us/azure/reliability/reliability-data-factory |
| Design resilient Azure Database for MySQL deployments | https://learn.microsoft.com/en-us/azure/reliability/reliability-database-mysql |
| Design resilient Azure Database for MySQL deployments | https://learn.microsoft.com/en-us/azure/reliability/reliability-database-mysql |
| Implement resiliency for Azure Database for PostgreSQL | https://learn.microsoft.com/en-us/azure/reliability/reliability-database-postgresql |
| Implement resilient architectures in Azure Databricks | https://learn.microsoft.com/en-us/azure/reliability/reliability-databricks |
| Ensure reliability for Azure Device Registry metadata | https://learn.microsoft.com/en-us/azure/reliability/reliability-device-registry |
| Design resilient architectures for Azure DNS Private Resolver | https://learn.microsoft.com/en-us/azure/reliability/reliability-dns-private-resolver |
| Design high availability for Azure DocumentDB | https://learn.microsoft.com/en-us/azure/reliability/reliability-documentdb |
| Implement resilient architectures with Azure Elastic SAN | https://learn.microsoft.com/en-us/azure/reliability/reliability-elastic-san |
| Implement resilient architectures with Azure Elastic SAN | https://learn.microsoft.com/en-us/azure/reliability/reliability-elastic-san |
| Build resilient architectures with Azure Event Grid | https://learn.microsoft.com/en-us/azure/reliability/reliability-event-grid |
| Increase reliability of Azure Event Hubs streaming | https://learn.microsoft.com/en-us/azure/reliability/reliability-event-hubs |
| Design reliable and resilient Azure Functions workloads | https://learn.microsoft.com/en-us/azure/reliability/reliability-functions |
| Design reliable and resilient Azure Functions workloads | https://learn.microsoft.com/en-us/azure/reliability/reliability-functions |
| Implement disaster recovery for Azure Image Builder | https://learn.microsoft.com/en-us/azure/reliability/reliability-image-builder |
| Design resilient architectures with Azure Load Balancer | https://learn.microsoft.com/en-us/azure/reliability/reliability-load-balancer |
| Design resilient architectures with Azure Load Balancer | https://learn.microsoft.com/en-us/azure/reliability/reliability-load-balancer |
| Design resilient workflows with Azure Logic Apps | https://learn.microsoft.com/en-us/azure/reliability/reliability-logic-apps |
| Improve reliability of Azure Managed Grafana workspaces | https://learn.microsoft.com/en-us/azure/reliability/reliability-managed-grafana |
| Increase reliability of Azure Managed Redis caches | https://learn.microsoft.com/en-us/azure/reliability/reliability-managed-redis |
| Design resilient Azure Monitor Logs workspaces | https://learn.microsoft.com/en-us/azure/reliability/reliability-monitor-logs |
| Improve reliability of Azure Notification Hubs | https://learn.microsoft.com/en-us/azure/reliability/reliability-notification-hubs |
| Harden Azure Private Link Service for high reliability | https://learn.microsoft.com/en-us/azure/reliability/reliability-private-link-service |
| Increase reliability of Azure Stream Analytics jobs | https://learn.microsoft.com/en-us/azure/reliability/reliability-stream-analytics |
| Design resilient architectures with Azure Traffic Manager | https://learn.microsoft.com/en-us/azure/reliability/reliability-traffic-manager |
| Design resilient workloads on Azure VMware Solution | https://learn.microsoft.com/en-us/azure/reliability/reliability-vmware-solution |
| Topic | URL |
|-------|-----|
| Choose Azure services by region type and category | https://learn.microsoft.com/en-us/azure/reliability/availability-service-by-category |
| Choose Azure services with availability zone support | https://learn.microsoft.com/en-us/azure/reliability/availability-zones-service-support |
| Select Azure regions with geography and pairing data | https://learn.microsoft.com/en-us/azure/reliability/regions-list |
| Design multi-region solutions in nonpaired Azure regions | https://learn.microsoft.com/en-us/azure/reliability/regions-multi-region-nonpaired |
| Select Azure services with built-in multiregion support | https://learn.microsoft.com/en-us/azure/reliability/regions-multiregion-support |
| Select and understand Azure nonregional services | https://learn.microsoft.com/en-us/azure/reliability/regions-nonregional-services |
| Topic | URL |
|-------|-----|
| Enable and plan zone-resilient Azure workloads | https://learn.microsoft.com/en-us/azure/reliability/availability-zones-enable-zone-resiliency |
| Design and harden zonal Azure resource deployments | https://learn.microsoft.com/en-us/azure/reliability/availability-zones-zonal-resource-resiliency |
| Topic | URL |
|-------|-----|
| Understand Azure Queue Storage message size limits | https://learn.microsoft.com/en-us/azure/reliability/reliability-storage-queue |
| Plan reliability and scale for Azure Web PubSub | https://learn.microsoft.com/en-us/azure/reliability/reliability-web-pubsub |
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.
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