A global fintech uses GLM 5.2 for its coding assistant.
It handles spiky traffic that static planning cannot predict.
The workload peaks during engineering hours with high concurrency.
Earlier capacity planning failed to absorb these sharp bursts.
Teams waited on tickets instead of provisioning their own endpoints.
Prefill capacity ran out exactly when it mattered most.
Why it matters
Self-service scaling stops request queuing during critical work hours.
Engineers can now provision capacity without waiting for platform teams.
Programmatic observability lets teams diagnose issues instantly.
Live configuration changes fix problems with zero downtime.
The system uses dozens of B200 chips at 256K context.
