A distributed system consists of multiple processes or machines that communicate over a network and work toward a shared result. Each component has only part of the state, messages can be delayed or duplicated, and one component can fail while others continue running.
Background AI workflows inherit these ordinary systems problems when schedules, models, queues, tools and storage operate independently. Durable event records, idempotency, retries and explicit boundaries help prevent duplicate work, lost inputs and uncertain execution history.
ELI5
A distributed system is a service made from several computers or processes that communicate over a network. Each part knows only some of the current state, and one part can fail while others continue.
For example, an AI workflow might use one service for scheduling, another for model calls, and another for storage. Durable records and safe retries keep a delayed message or restarted worker from losing work or creating the same result twice.
Why is an AI agent runtime a distributed system?
It often coordinates schedulers, models, tools, queues, databases and external services that communicate and fail independently.
What failures are common in distributed systems?
Common failures include delayed or duplicate messages, partial outages, inconsistent state, lost work and retries that repeat an action.
