Originally published on Substack.
Part 3 of my Azure AI landing zone series is about FinOps for AI workloads. Tokens are the AI bill most teams actually get, so the post covers:
- Picking the deployment type first: Global Standard, Data Zone, Batch and Flex (preview)
- Why quota isn't billing, and why
max_tokenseats your TPM - PTU vs pay-as-you-go, and when hourly PTU actually pays off
- Sizing PTU with Microsoft's formula, and how prompt caching helps
- Spillover: PTU for the baseline, pay-per-token for the peaks
- Showback per team with
llm-token-limitandllm-emit-token-metricin API Management - Cost Management: group by meter, tag your deployments, and remember budgets only alert
Read the full article on Substack: https://gisli78.substack.com/p/finops-for-ai-workloads-on-azure
Bicep sample: https://github.com/gislig/azure-ai-landing-zone/tree/main/examples/ai-finops
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