customize Examples
Example 1: Basic Deployment with Defaults
Scenario: Deploy gpt-4o accepting all defaults for quick setup.
Config: gpt-4o / GlobalStandard / 10K TPM / Dynamic Quota enabled
Result: Deployment gpt-4o created in ~2-3 min with auto-upgrade enabled.
Example 2: Production Deployment with Custom Capacity
Scenario: Deploy gpt-4o for production with high throughput.
Config: gpt-4o / GlobalStandard / 50K TPM / Dynamic Quota / Name: gpt-4o-production
Result: 50K TPM (500 req/10s). Suitable for moderate-to-high traffic production apps.
Example 3: PTU Deployment for High-Volume Workload
Scenario: Deploy gpt-4o with reserved capacity (PTU) for predictable workload. Config: gpt-4o / ProvisionedManaged / 200 PTU (min 50, max 1000) / Priority Processing enabled PTU sizing: 40K input + 20K output tokens/min → ~100 PTU estimated → 200 PTU recommended (2x headroom) Result: Guaranteed throughput, fixed monthly cost. Use case: customer service bots, document pipelines.
Example 4: Development Deployment with Standard SKU
Scenario: Deploy gpt-4o-mini for dev/testing with minimal cost.
Config: gpt-4o-mini / Standard / 1K TPM / Name: gpt-4o-mini-dev
Result: 1K TPM, 10 req/10s. Minimal pay-per-use cost for development and prototyping.
Example 5: Spillover Configuration
Scenario: Deploy gpt-4o with spillover to handle peak load overflow.
Config: gpt-4o / GlobalStandard / 20K TPM / Dynamic Quota / Spillover → gpt-4o-backup
Result: Primary handles up to 20K TPM; overflow auto-redirects to backup deployment.
Example 6: Anthropic Model Deployment (claude-sonnet-4-6)
Scenario: Deploy claude-sonnet-4-6 with customized settings.
Config: claude-sonnet-4-6 / GlobalStandard / capacity 1 (MaaS) / Industry: Healthcare / No RAI policy (Anthropic manages content filtering)
Result: User selected "Healthcare" as industry → tenant country code (US) and org name fetched automatically → deployed via ARM REST API with modelProviderData in ~2 min.
Comparison Matrix
| Scenario | Model | SKU | Capacity | Dynamic Quota | Priority | Spillover | Use Case |
|---|---|---|---|---|---|---|---|
| Ex 1 | gpt-4o | GlobalStandard | 10K TPM | ✓ | - | - | Quick setup |
| Ex 2 | gpt-4o | GlobalStandard | 50K TPM | ✓ | - | - | Production |
| Ex 3 | gpt-4o | ProvisionedManaged | 200 PTU | - | ✓ | - | Predictable workload |
| Ex 4 | gpt-4o-mini | Standard | 1K TPM | - | - | - | Dev/testing |
| Ex 5 | gpt-4o | GlobalStandard | 20K TPM | ✓ | - | ✓ | Peak load |
| Ex 6 | claude-sonnet-4-6 | GlobalStandard | 1 (MaaS) | - | - | - | Anthropic model |
Common Patterns
Dev → Staging → Production
| Stage | Model | SKU | Capacity | Extras |
|---|---|---|---|---|
| Dev | gpt-4o-mini | Standard | 1K TPM | — |
| Staging | gpt-4o | GlobalStandard | 10K TPM | — |
| Production | gpt-4o | GlobalStandard | 50K TPM | Dynamic Quota + Spillover |
Cost Optimization
- High priority: gpt-4o, ProvisionedManaged, 100 PTU, Priority Processing
- Low priority: gpt-4o-mini, Standard, 5K TPM
Tips and Best Practices
Capacity: Start conservative → monitor with Azure Monitor → scale gradually → use spillover for peaks.
SKU Selection: Standard for dev → GlobalStandard + dynamic quota for variable production → ProvisionedManaged (PTU) for predictable load.
Cost: Right-size capacity; use gpt-4o-mini where possible (80-90% accuracy at lower cost); enable dynamic quota; consider PTU for consistent high-volume.
Versions: Auto-upgrade recommended; test new versions in staging first; pin only if compatibility requires it.
Content Filtering: Start with DefaultV2; use custom policies only for specific needs; monitor filtered requests.
Troubleshooting
| Problem | Solution |
|---|---|
QuotaExceeded |
Check usage with az cognitiveservices usage list, reduce capacity, try different SKU, check other regions, or use the quota skill to request an increase |
| Version not available for SKU | Check az cognitiveservices account list-models --query "[?name=='gpt-4o'].version", use latest |
| Deployment name exists | Skill auto-generates unique name (e.g., gpt-4o-2), or specify custom name |