To ensure real-time streaming, it is often necessary to limit the number of inference requests that a model is processing concurrently. To support this, Rime’s Arcana model images return a Open Request Cost Aggregation (ORCA) header to inform a load balancer based on the number of concurrent requests.
The full set of ORCA headers are returned by Arcana model containers since the 20260115 release.

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HTTP ORCA header

The ORCA header in HTTP responses looks like: 
endpoint-load-metrics: TEXT application_utilization=0.5, cpu_utilization=0.3128, mem_utilization=0.2453, rps_fractional=0.0000, eps=0.0000

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Max concurrency

The application_utilization metric is calculated by dividing the number of concurrent inference requests by a preconfigured max concurrency. You can override the max concurrency after parameter tuning by setting the INFERENCE_CONCURRENCY_CAPACITY to the desired max concurrency.
The INFERENCE_CONCURRENCY_CAPACITY variable is only used to calculate the utilization to inform the load balancer. Setting it does not reject or queue overflowing requests.