Domain 3 of 5 · Chapter 2 of 3

Deploy and Manage Foundation Models

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Included in this chapter:

  • Serverless API or managed compute
  • Deployment types: Standard, Provisioned, Batch
  • Spillover: draining a full PTU deployment
  • Runtime guardrails: filters and Prompt Shields
  • Choosing a model: class, leaderboard, router
  • Versioning, updates, and retirement
  • Exam-pattern recognition

Serving a pay-as-you-go model: Standard vs Provisioned vs Global Batch

Decision axisStandardProvisioned (PTU)Global Batch
Billing basisPay per tokenPer PTU per hour (reservation-discountable)Pay per token, 50% off Global Standard
CapacityBest-effort, sharedReserved, dedicatedSeparate async batch quota
LatencyVariable at high volumeLow and predictableAsync, up to 24-hour turnaround
Throughput guaranteeNone (TPM/RPM rate limit)Guaranteed by allocated PTUsNo real-time SLA
Best forVariable or bursty real-time trafficHigh, steady real-time volumeLarge offline, cost-minimizing jobs
Cost leverRebalance TPM or request an increaseProvisioned Throughput ReservationThe batch discount itself

Decision tree

Serverless (pay-as-you-go)API available?Managed computededicated VMs · compute quota · hourlyLarge async job,minimize cost?Global Batch50% off · up to 24h · no SLASteady high volume,guaranteed throughput?Provisioned (PTU)reserve capacity · reservation · spilloverStandard (Global Standard)pay per token · TPM/RPM quotaAlways: data must stay in one geography?Use the Data Zone (or Regional) variant.YesNoNoYesYesNo

Cheat sheet

  • Serverless API deployment bills per token and needs no compute quota
  • Managed compute uses dedicated VMs, needs compute quota, and bills hourly while running
  • Standard deployments are best-effort per-token; Provisioned reserve capacity
  • Global routes anywhere; Data Zone keeps processing within a geography
  • A deployment content filter tunes four harm categories and severity thresholds plus blocklists and Prompt Shields against direct jailbreak and indirect (XPIA) prompt injection
  • Standard deployments draw a per-deployment TPM quota from a region-subscription pool
  • Global Batch is the cost-optimal deployment type for high-volume asynchronous workloads
  • Protected-material text and code are output-only content filters, on by default, and separate from the ProtectedMaterial evaluator
  • Use the model leaderboard to compare quality, safety, cost, and throughput
  • The catalog spans many model providers
  • Match the model class to the workload before comparing individual models
  • Model router auto-selects the best underlying model per prompt
  • Three deployment version-upgrade options control model updates
  • Automatic updates apply to Standard only; Provisioned migrates manually
  • GA models get at least 60 days' retirement notice
  • PTUs reserve fixed capacity billed hourly regardless of tokens
  • Spillover routes overflowing PTU requests to a paired standard deployment
  • Provisioned Throughput Reservations discount committed PTUs for a fixed term

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References

  1. Microsoft Foundry Models overview (classic) - Microsoft Foundry (classic) portal
  2. Deploy models with managed compute (classic) - Microsoft Foundry (classic) portal
  3. Understanding deployment types in Microsoft Foundry Models - Microsoft Foundry
  4. Azure OpenAI in Microsoft Foundry Models Quotas and Limits - Microsoft Foundry
  5. Provisioned throughput for Foundry Models - Microsoft Foundry
  6. How to use global batch processing with Azure OpenAI in Microsoft Foundry Models - Microsoft Foundry
  7. Manage traffic with spillover for provisioned deployments - Microsoft Foundry
  8. Content filtering for Microsoft Foundry Models (classic) - Microsoft Foundry (classic) portal
  9. Harm categories and severity levels in Microsoft Foundry - Microsoft Foundry
  10. Prompt Shields in Microsoft Foundry - Microsoft Foundry
  11. Protected Material Detection Filter - Microsoft Foundry
  12. Compare models using the model leaderboard - Microsoft Foundry
  13. Model router for Microsoft Foundry concepts - Microsoft Foundry
  14. Model versioning in Microsoft Foundry Models (classic) - Microsoft Foundry (classic) portal
  15. Azure OpenAI in Microsoft Foundry Models working with models - Microsoft Foundry
  16. Foundry Models lifecycle and support policy - Microsoft Foundry