Scale Job Triggering with Dapr's Distributed Scheduler

Imagine scheduling thousands or millions of jobs that are persisted and triggered timely and resilient to downtime.

Some jobs might be triggered every second while others need to reliably be triggered on the first day of the month. Achieving high throughput and reliability is critical for the performance and operational efficiency of modern distributed systems. How can traditional cron job scheduling be extended? How can distributed systems handle job scheduling with minimal downtime? What challenges arise when scaling job scheduling to thousands or millions of jobs? In this session, Artur and Cassie will delve into the design of Dapr’s distributed Scheduler and how users can start using it today. You will gain a comprehensive understanding of how Dapr’s Scheduler unblocks scalability of actors and workflows while also enabling new capabilities, like delayed pubsub and schedule job API.