parallel-dispatch

To execute parallel tasks in a DAG concurrently, you dispatch ready groups by spawning worker agents and coordinating their execution. This orchestration manages dispatch, monitoring, aggregation, and failure recovery.

The best way to monitor worker agents and handle failures in a DAG workflow is using heartbeat monitoring and a message bus. These coordinate execution, track progress, and trigger safe fallback or recovery strategies.

Yes, you need an agent factory and a message bus to orchestrate parallel DAG workflows. These components, along with heartbeat monitoring, are required to ensure timely completion and safe fallback.

Yes, you can scale to multiple concurrent worker agents while enforcing safety limits. The orchestration process manages dispatching parallel task groups and coordinates execution up to your defined limits.

DAG task aggregation works by monitoring the spawned parallel worker agents until completion and then collecting their results. The coordination mechanism tracks progress and handles any failures with recovery strategies.

Parallel DAG task dispatch requires heartbeat monitoring to ensure timely completion and safe fallback. It tracks the health of spawned worker agents during concurrent execution and triggers failure recovery when needed.