Due to traffic engineering, topology changes, and VM migrations, today's networks undergo a variety of large updates that concurrently affect many switches. Big updates are time consuming because the available switches have low rule installation rates. In this paper, we observe that a large network update may consist of a set of sub-updates that are independent and can be installed in parallel in any order. We treat update installation as a scheduling problem and design ESPRES, a runtime mechanism that rate-limits and reorders updates to fully utilize switches without overloading them. Our early results show that compared to using no scheduler, our simple scheduler yields 4 times quicker sub-update completion time for 20th percentile of sub-updates and 40% quicker for 50th percentile.