API Management in the AI Era
summary
Describes using Azure API Management AI gateway to treat tokens as currency showing concrete measurements like ML 7B instruct using 110 tokens vs 17 prompt tokens and Deepseek R1 reasoning for 4.5 minutes consuming >1000 tokens. Explains emitting usage to Azure Monitor with emit token metrics, enforcing per‑consumer limits with a token per minute limit 500 policy that returns 429 after ~8 requests, reserving capacity via provisioned throughput units, and multi‑region failover across UK South, Sweden Central and France Central with retry and priority load balancing.
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chapters (10)
- 0:00API management in AI era
- 1:13Traditional API management fails for GenAI
- 3:41Tracking token usage
- 5:05Token-based rate limits
- 6:31Monitoring model utilization
- 8:18Token limits per consumer
- 9:41Token capacity at model level
- 10:44Failover and load balancing
- 13:15AI gateway capabilities
- 14:37Q&A
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