The event-driven programming model has been proposed to efficiently process iterative applications and incremental applications. In clusters based the event-driven model, applications are structured as a series of triggers, each of which will be invoked when associate events are trigged. And framework assigns a newly submitted trigger to a node where the relevant datasets set. Unfortunately it may lead to load imbalance because associate events occur by chance. Numerous triggers in a node may be simultaneously invoked but other nodes have no triggers running. Jobs composed of short, sub-second triggers present a difficult balancing challenge. To the end, we design DLBer, a new dynamic load balancing algorithm for the event-driven clusters to maximize improve the utilization of node resources.