Durable Execution
What operational overhead comes with durable execution compared to a simple queue-based system?
Durable execution requires managing workflow state storage, replay determinism, and idempotency for side effects. Queues have simpler operational models but lack recovery guarantees. Catalyst reduces overhead by providing managed state persistence and replay, but you still must design activities to be safely retryable. Start with queues for stateless tasks, add durable execution for complex agents.
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- Durable Execution
What is durable execution in AI agent workflows?
Durable execution means an AI agent workflow can keep its progress even when a process crashes, a tool call fails, or the system restarts.
- Durable Execution
Why do production AI agents need durable workflows?
Production AI agents need durable workflows because real agent tasks rarely finish in a single clean request.
- Durable Execution
Is checkpointing enough for production AI agents?
Checkpointing helps, but it is usually not enough by itself for production AI agents. It explains the production reliability impact for AI agent workflows.