Capacity Management in Agent Networks: Rate Limiting, Priority Queues, and Backpressure

May 17, 2026

Agent ensembles that run as long-lived services on a network will, at some point, receive more work than they can handle. The question is what happens next.

Without capacity management, the answer is usually one of: unbounded queue growth (OOM), random request dropping, or cascade failures where an overloaded ensemble backs up its callers.

The capacity problem in agent networks

Agent workloads have properties that make capacity management harder than in traditional request/response systems:

Variable execution time. A simple analysis task might take 5 seconds. A complex coding task might take 5 minutes.
Variable cost. Each agent iteration consumes LLM tokens. An overloaded system burns money faster.
Fan-out amplification. One incoming request to a coordinator might fan out to 5 different ensembles.

Three layers of capacity management

1. Reactive: Rate limits and backpressure

Concurrency limits protect ensembles from overload. When the limit is reached, requests queue. When the queue is full, backpressure signals propagate upstream.

2. Priority: Queues with aging

PriorityRequestQueue adds priority levels with aging to prevent starvation. Requests waiting beyond the aging interval get promoted, guaranteeing every request is eventually processed.

3. Proactive: Operational profiles

NetworkProfile bundles per-ensemble capacity targets and shared memory pre-load directives into deployable units. Apply via schedule, directive system, or manual trigger.

NetworkProfile weekendProfile = NetworkProfile.builder()
    .name("sporting-event-weekend")
    .ensemble("front-desk", Capacity.replicas(4).maxConcurrent(50))
    .ensemble("kitchen", Capacity.replicas(3).maxConcurrent(100))
    .preload("kitchen", "inventory", "Extra beer and ice stocked")
    .build();

The design principle

Each layer addresses a different time horizon: seconds (rate limits), minutes (priority queues), and hours/days (operational profiles). Together, they give operators the tools to keep an agent network running under variable load.

Capacity management is part of AgentEnsemble. The rate limiting guide, operational profiles guide, and scheduled tasks guide cover the full APIs.