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:
- Gather requirements — workload type, vCPU/RAM, GPU, storage, budget, OS, region, instance count, scaling, HA, load balancing
- 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
- Select VM family — pick 2–3 candidates from vm-families.md, then verify specs via
web_fetch against learn.microsoft.com
- Look up pricing — Azure Retail Prices API per retail-prices-api.md; for VMSS multiply by instance count
- Present 2–3 recommendations — include hosting model, VM size, vCPU/RAM, instance count, $/hr, fit, trade-off
- 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) |
1---2name: azure-compute3description: **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).4license: MIT5---67# Azure Compute Skill89Recommend 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.1011## When to Use This Skill1213- User asks which Azure VM or VMSS to choose for a workload14- User needs VM size recommendations for web, database, ML, batch, HPC, or other workloads15- User wants to compare VM families, sizes, or pricing tiers16- User asks about trade-offs between VM options (cost vs performance)17- User needs a cost estimate for Azure VMs without an Azure account18- User asks whether to use a single VM or a scale set19- User needs autoscaling, high availability, or load-balanced VM recommendations20- User asks about VMSS orchestration modes (Flexible vs Uniform)2122## Rules2324- **Always verify against live docs** — call `web_fetch` against `learn.microsoft.com` before finalizing recommendations; warn the user when `web_fetch` fails25- **Default to General Purpose D-series** when workload type is unclear26- **Default region** follows the canonical declaration in [copilot-instructions.md](../../copilot-instructions.md#azure-defaults-canonical); prices vary by region27- **Default to single VM** when scaling needs are unclear; recommend VMSS only when autoscale, fleet, or mixed-size requirements are explicit28- **VMSS pricing** = VM pricing × instance count (no extra VMSS charge)29- **Reservation pricing** is recommended for long-lived production VMs (1y/3y commitments)30- **No deployment** — this skill recommends sizes; for provisioning use `azure-prepare`3132## Steps3334The full 6-step procedure (with all decision tables, dichotomy tree, and `web_fetch` URLs) lives in **[references/recommendation-workflow.md](references/recommendation-workflow.md)**. Load it on demand. Summary:35361. **Gather requirements** — workload type, vCPU/RAM, GPU, storage, budget, OS, region, instance count, scaling, HA, load balancing372. **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 unsure383. **Select VM family** — pick 2–3 candidates from [vm-families.md](references/vm-families.md), then verify specs via `web_fetch` against `learn.microsoft.com`394. **Look up pricing** — Azure Retail Prices API per [retail-prices-api.md](references/retail-prices-api.md); for VMSS multiply by instance count405. **Present 2–3 recommendations** — include hosting model, VM size, vCPU/RAM, instance count, $/hr, fit, trade-off416. **Offer next steps** — reservation pricing, [Azure Pricing Calculator](https://azure.microsoft.com/pricing/calculator/), VMSS autoscale + networking docs4243> **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.4445## Error Handling4647| Scenario | Action |48| ------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |49| API returns empty results | Broaden filters — check `armRegionName`, `serviceName`, `armSkuName` spelling |50| User unsure of workload type | Ask clarifying questions; default to General Purpose D-series |51| Region not specified | Use the canonical default from [copilot-instructions.md](../../copilot-instructions.md#azure-defaults-canonical); prices vary by region |52| Unclear if VM or VMSS needed | Ask about scaling and instance count; default to single VM if unsure |53| User asks VMSS pricing directly | Use same VM pricing API — VMSS has no extra charge; multiply by instance count |5455## References5657- [Recommendation Workflow](references/recommendation-workflow.md) — Full 6-step procedure with decision tables and `web_fetch` URLs58- [VM Family Guide](references/vm-families.md) — Family-to-workload mapping and selection59- [Retail Prices API Guide](references/retail-prices-api.md) — Query patterns, filters, and examples60- [VMSS Guide](references/vmss-guide.md) — When to use VMSS, orchestration modes, and autoscale patterns6162## Reference Index6364Load these on demand — do NOT read all at once:6566| Reference | When to Load |67| --------------------------------------- | ------------------------------------------------ |68| `references/recommendation-workflow.md` | Full Steps 1–6 (decision tables, web_fetch URLs) |69| `references/retail-prices-api.md` | Pricing queries (Step 4) |70| `references/vm-families.md` | VM family selection (Step 3) |71| `references/vmss-guide.md` | VMSS vs VM decision (Step 2) |
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