
Skill
capacity_planning
assess Azure resource capacity and scaling
Description
Assess Azure resource capacity, quota utilization, and growth trends to prevent outages from resource exhaustion. Use when asked about capacity, quotas, scaling readiness, load testing prep, or growth projections.
SKILL.md
Capacity Planning
Purpose
Analyze current resource utilization, quota consumption, and growth trends to predict capacity risks and recommend scaling actions before limits are hit.
Procedure
Step 1: Quota utilization
az vm list-usage --location <region> -o table
az network list-usages --location <region> -o table
Check vCPU quotas (total and per-family), public IPs, load balancers, network interfaces, storage accounts per subscription, App Service plans per region, and AKS clusters. Flag resources > 70% utilized.
Step 2: Compute capacity
- VM utilization (last 14 days): average and P95 CPU/memory. Flag VMs > 80%.
- App Service plans:
az appservice plan list --query "[].{name:name, sku:sku.name, workers:numberOfWorkers}" -o table - AKS clusters:
az aks list --query "[].{name:name, nodeCount:agentPoolProfiles[0].count, maxCount:agentPoolProfiles[0].maxCount}" -o table
Step 3: Data layer capacity
Check SQL Database DTU/vCore utilization, Cosmos DB RU consumption and 429 rates, Redis Cache memory and server load, storage account transaction rates.
Step 4: Networking capacity
Check ExpressRoute/VPN Gateway bandwidth, Application Gateway/Front Door connections, NAT Gateway SNAT utilization.
Step 5: Growth projection
Apply linear projection to estimate when each resource hits 80% and 100%. If the user specified a growth factor, multiply current usage and check against limits.
Step 6: Quota increase requests
az rest --method patch \
--url "https://management.azure.com/subscriptions/<sub-id>/providers/Microsoft.Capacity/resourceProviders/Microsoft.Compute/locations/<region>/serviceLimits/<family>?api-version=2020-10-25" \
--body '{"properties":{"limit":{"limitObjectType":"LimitValue","value":<new-limit>}}}'
Scoring
| Risk | Utilization |
|---|---|
| 🟢 Low | < 70% |
| 🟡 Medium | 70-90% |
| 🔴 Critical | > 90% |
Sample output
| Field | Value |
|---|---|
| Subscription | contoso-prod-001 |
| Region(s) | East US, West Europe |
| Resources scanned | 47 |
| At risk (>70%) | 5 |
| Critical (>90%) | 2 |
| Resource | Current | At 2x Load | Action |
|---|---|---|---|
| vCPUs East US | 85/100 (85%) | 170 ❌ | Quota increase |
| SQL DTU | 78% avg | 156% ❌ | Scale up tier |
| AKS nodes | 7/10 | 14 ❌ | Increase max |
References
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