Decentralized workflow systems offer an alternative to centralized ones by eliminating the need for a central orchestrator, with each server executing workflows independently while coordinating through a shared data store. This approach simplifies adoption and operation, as it does not require dedicated workflow servers and avoids creating a single point of failure. However, challenges arise in ensuring efficient execution and coordination among servers, such as resolving duplicate workflow executions, managing cron scheduling without causing spikes in database contention, and efficiently dequeuing workflows. Solutions include employing database integrity constraints to detect and prevent duplicate executions, introducing randomness to reduce cron scheduling contention, and using database locking clauses to manage workflow queues. These strategies help decentralized workflows operate effectively at scale, although they require careful implementation to maintain performance and reliability.