azure-quotas

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SKILL.md (first lines)

# Azure Quotas

Plan quota headroom early so deployments and scale events do not fail unexpectedly.
Identify bottlenecks before they become crises.

## Use This Skill When

- The user sees quota or capacity errors in Azure (DeploymentQuotaExceeded, etc.)
- The user plans a new deployment in a constrained region or subscription
- The user needs preflight checks before scaling operations
- The user wants to verify available capacity before committing to architecture

## Context: Quota Management Maturity

**Immature**: Hit quota limits unexpectedly, manual increases, no planning  
**Developing**: Track some quotas, request increases reactively  
**Managed**: Automated quota tracking, capacity planning, reserved capacity → **Target**  
**Optimized**: Predictive quota management, auto-scaling to new regions, zero surprises

## Required Inputs

- **Subscription ID & region**: Where are you deploying?
- **Planned resources**: How many VMs? App Services? SQL databases?
- **Scale targets**: Current vs. planned capacity?
- **Timeline**: Immediate (next week)? Next quarter? Next year?
- **Compliance**: Any data residency or region-specific needs?

## Decision Tree

```
Where does this workload run?
├─ Single region (lowest complexity)
│  └─ Can fall back to alternative region if quota exceeded?
├─ Multi-region (higher complexity, but better resilience)
│  └─ Distribute across regions to avoid single-region limits
└─ Hybrid (on-premises + Azure)
   └─ Plan data transfer, bandwidth quotas

What's the expected scale?
├─ Small (< 10 VMs, < 100 GB data)
│  └─ Quota rarely an issue
├─ Medium (10-100 VMs, 100 GB - 1 TB data)
│  └─ Plan quotas for compute tier
└─ Large (> 100 VMs, > 1 TB data)
   └─ Request increases in advance, plan multi-region

Are quotas the risk, or SKU availability?
├─ Quota (limit per subscription) → Request increase
├─ SKU availability (no machines available) → Fallback to alternative SKU or region
└─ Cost (exceeding budget) → Use Reserved Instances to cap costs
```

## Workflow

### Phase 1: Identify Quota-Limited Services

1. **Compute quotas** (most common bottleneck):
   ```bash
   # Check vCPU quotas by family
   az vm list-usage --location "eastus" -o table
   
   # Output
   Name                       CurrentValue    Limit
   Standard D Family vCPUs    10              20    ← Can add 10 more
   Standard B Family vCPUs    5               20    ← Plenty available
   Standard E Family vCPUs    0               20    ← None used yet
   ```

2. **Storage quotas**:
   ```bash
   # Get current storage account usage
   az storage account list --query "[].{name:name, tier:sku.name, kind:kind}" -o table
   
   # Limit: 250 storage accounts per subscription
   # Each can be up to 5PB (petabytes)
   ```

3. **Database quotas**:
   ```bash
   # SQL Server quota (per region, per subscription)
   az sql server list --query "[].{name:name, region:location}" -o table
   
   # Limit: 15 servers per subscription, per region
   ```

4. **Networking quotas**:
   ```
   Network Security Groups: 100 per region
   VNets: 100 per subscription
   Public IPs: 60 per region
   Load Balancers: 1 per region (basic), 100 (standard)
   Application Gateways: 20 per subscription
   ```

5. **Other quota-limited services**:
   ```
   App Service Plans: 100 per resource group
   Batch Accounts: 1-3 per region
   Cognitive Services: Varies by service (Speech, Vision, etc.)
   Media Services: Limited slots per subscription
   Redis Cache: 50 per subscription
   Search Services: 15 per subscription
   ```

### Phase 2: Check Current Usage vs. Limits

1. **Get quota status**:
   ```bash
   # All quotas for a region
   az provider show --namespace Microsoft.Compute \
     --query "resourceTypes[?resourceType=='virtualMachines'].limits" -o table
   
   # Output
   limitName                  limitValue
   vCpuCountPerRegion         20
   vCpuCountPerVmFamily       20
   standardBFamilyvCpusCount  20
   standardDFamilyvCpusCount  20
   ```

From manu14357/zskills, MIT.

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