BlueBear Insights · Agent Operations · 5 min read

AI Agent Capacity Planning: Concurrency, Queues, Models, and Tools

BlueBear evidence ladder connecting governed agent decisions with execution and outcome records
Operational evidence should connect every agent decision to its authority, execution, and accepted outcome.

One user request can create many model, retrieval, and tool operations. Capacity planning must model amplification and external quotas, not only frontend requests per second.

Capacity worksheet

For each workflow record arrival rate, concurrent sessions, steps per session, model calls per step, tool calls, token volume, service time, retries, approval wait, and terminal-state rate. Segment by tenant and priority.

Find the real bottleneck

BoundarySignalControl
Modelrate/token quota, latency, fallbackadmission, routing, batch, reserved quota
ToolAPI limit, lock, downstream saturationper-tool concurrency and circuit breaker
RuntimeCPU, memory, pod startup, queue depthautoscaling and selective pre-warm
Humanapproval age and exception backlogrisk routing, staffing, expiry

Safe overload

Prioritize critical workflows, reject early with a visible reason, cap retries, preserve idempotency, and prevent one tenant from consuming shared capacity. Test model slowdown, tool outage, burst traffic, and approval backlog together.

Connect the capacity model to infrastructure cost controls.

Primary sources