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Serverless API Deployments

📦 The Model Catalog 8 min 70 BASE XP⌨ HANDS-ON LAB

Pay-Per-Token Model Access

Serverless API deployments are the simplest way to use models. Microsoft hosts the infrastructure - you just call the endpoint.

Deployment Tiers

TierBillingBest ForData Processing
StandardPay-per-tokenDevelopment, variable workloadsGlobal (any region)
Provisioned (PTU)Reserved capacityProduction, predictable throughputSpecific region
Data ZonePay-per-tokenEU/US data residency complianceWithin zone (EU or US)
Batch50% discountAsync bulk processingNon-real-time

Creating a Serverless Deployment

// Via Azure CLI:
az cognitiveservices account deployment create \
  --name my-foundry \
  --resource-group my-rg \
  --deployment-name gpt4o-deploy \
  --model-name gpt-4o \
  --model-version "2024-11-20" \
  --sku-name "Standard" \
  --sku-capacity 10
🎯 Pro Tip: Start with Standard tier for development (you only pay for what you use). When you know your production load, switch to Provisioned (PTU) for guaranteed throughput and predictable costs.
⌨ HANDS-ON LABDeploy a Model from the CLI
⭐ +200 XP

Deploy a model onto your Foundry resource without touching the portal, then verify it's live.

1Create a model deployment with az cognitiveservices account deployment create (needs --model-name, --model-version and --model-format).
2List the deployments on your account to confirm it's live.
lab-sandbox — simulated environment
INFINITY LAB SANDBOX v2.6 — simulated shell
Type the command for the current objective. Helpers: "hint", "solution", "clear".
$
OBJECTIVE 1 / 2 — type "hint" if stuck
FOUNDRY VERIFICATION
QUERY 1 // 2
Which deployment tier offers a 50% cost discount for bulk processing?
Standard
Provisioned
Data Zone
Batch