Function-as-a-Service (FaaS) is becoming increasingly prevalent, and the number of daily service requests in our system ByteDance has even reached 49.6 billion. These requests exhibit “3H” characteristics:high concurrency,high burstiness, andhigh fluctuation, causing the instance scheduling system to face severe bottlenecks even earlier than the data plane.In this paper, inspired by the idea of on-demand scaling of FaaS applications, we proposeGalaxy, a highly scalable instance scheduling system for FaaS platforms.Galaxydecouples the instance scheduling system into functions and introduces a top controller to dynamically adjust the number of instances for each function based on the request load, effectively eliminating bottlenecks under high concurrent requests. We evaluateGalaxywith real-world workloads and the experimental results show thatGalaxycan complete the scaling of over 89,935 instances within 1 second, excluding cold start overhead.Galaxyincreases the scheduling throughput by 8.6 ~ 12.7× compared to the existing control plane.