azure-compute

name	azure-compute
description	**ANALYSIS SKILL** — Recommend Azure VM sizes and VMSS for workload, performance, and budget. Uses public docs and the Azure Retail Prices API. WHEN: "recommend VM size", "choose Azure VM", "GPU VM", "compare VM sizes", "VMSS vs VM", "autoscale VMs". DO NOT USE FOR: provisioning VMs (azure-prepare), VM pricing for budgets (ARM MCP).
license	MIT
metadata	{"author":"Microsoft","version":"1.0.2"}

Azure Compute Skill

Recommend Azure VM sizes, VM Scale Sets (VMSS), and configurations by analyzing workload type, performance requirements, scaling needs, and budget. No Azure subscription required — all data comes from public Microsoft documentation and the unauthenticated Retail Prices API.

When to Use This Skill

• User asks which Azure VM or VMSS to choose for a workload
• User needs VM size recommendations for web, database, ML, batch, HPC, or other workloads
• User wants to compare VM families, sizes, or pricing tiers
• User asks about trade-offs between VM options (cost vs performance)
• User needs a cost estimate for Azure VMs without an Azure account
• User asks whether to use a single VM or a scale set
• User needs autoscaling, high availability, or load-balanced VM recommendations
• User asks about VMSS orchestration modes (Flexible vs Uniform)

Rules

• Always verify against live docs — call web_fetch against learn.microsoft.com before finalizing recommendations; warn the user when web_fetch fails
• Default to General Purpose D-series when workload type is unclear
• Default region follows the canonical declaration in copilot-instructions.md; prices vary by region
• Default to single VM when scaling needs are unclear; recommend VMSS only when autoscale, fleet, or mixed-size requirements are explicit
• VMSS pricing = VM pricing × instance count (no extra VMSS charge)
• Reservation pricing is recommended for long-lived production VMs (1y/3y commitments)
• No deployment — this skill recommends sizes; for provisioning use azure-prepare

Steps

The full 6-step procedure (with all decision tables, dichotomy tree, and web_fetch URLs) lives in references/recommendation-workflow.md. Load it on demand. Summary:

1. Gather requirements — workload type, vCPU/RAM, GPU, storage, budget, OS, region, instance count, scaling, HA, load balancing
2. Determine VM vs VMSS — VMSS for autoscale / fleet / mixed sizes (Flexible orchestration); VM for single long-lived servers, jumpboxes, AD DCs. Default to single VM when unsure
3. Select VM family — pick 2–3 candidates from vm-families.md, then verify specs via web_fetch against learn.microsoft.com
4. Look up pricing — Azure Retail Prices API per retail-prices-api.md; for VMSS multiply by instance count
5. Present 2–3 recommendations — include hosting model, VM size, vCPU/RAM, instance count, $/hr, fit, trade-off
6. Offer next steps — reservation pricing, Azure Pricing Calculator, VMSS autoscale + networking docs

Critical: always verify recommendations against live learn.microsoft.com docs via web_fetch. If web_fetch fails, proceed with reference-file guidance and warn the user data may be stale.

Error Handling

Scenario	Action
API returns empty results	Broaden filters — check armRegionName, serviceName, armSkuName spelling
User unsure of workload type	Ask clarifying questions; default to General Purpose D-series
Region not specified	Use the canonical default from copilot-instructions.md; prices vary by region
Unclear if VM or VMSS needed	Ask about scaling and instance count; default to single VM if unsure
User asks VMSS pricing directly	Use same VM pricing API — VMSS has no extra charge; multiply by instance count

References

• Recommendation Workflow — Full 6-step procedure with decision tables and web_fetch URLs
• VM Family Guide — Family-to-workload mapping and selection
• Retail Prices API Guide — Query patterns, filters, and examples
• VMSS Guide — When to use VMSS, orchestration modes, and autoscale patterns

Reference Index

Load these on demand — do NOT read all at once:

Reference	When to Load
references/recommendation-workflow.md	Full Steps 1–6 (decision tables, web_fetch URLs)
references/retail-prices-api.md	Pricing queries (Step 4)
references/vm-families.md	VM family selection (Step 3)
references/vmss-guide.md	VMSS vs VM decision (Step 2)