# Spotlight on SIG Scheduling DevFeed: [Spotlight on SIG Scheduling]() Original publisher: [Read original article]() Author: The Kubernetes Authors Published: 2024-09-24T00:00:00Z Content type: article Language: en Sources: [Kubernetes Contributors Blog]() Topics: [Kubernetes](), [Scalability]() Tags: [kubernetes](), [scalability]() ## AI overview An interview with Kensei Nakada, an approver in Kubernetes SIG Scheduling, covering the group's role in maintaining kube-scheduler and related components. It discusses recent improvements to PodTopologySpread, the QueueingHint enhancement for scheduling throughput, scalability challenges, and the kube-scheduler-wasm-extension subproject. ## Source excerpt In this SIG Scheduling spotlight we talked with Kensei Nakada , an approver in SIG Scheduling. Introductions Arvind: Hello, thank you for the opportunity to learn more about SIG Scheduling! Would you like to introduce yourself and tell us a bit about your role, and how you got involved with Kubernetes? Kensei: Hi, thanks for the opportunity! I'm Kensei Nakada (@sanposhiho ), a software engineer at Tetrate.io . I have been contributing to Kubernetes in my free time for more than 3 years, and now I'm an approver of SIG Scheduling in Kubernetes. Also, I'm a founder/owner of two SIG subprojects, kube-scheduler-simulator and kube-scheduler-wasm-extension . About SIG Scheduling AP: That's awesome! You've been involved with the project since a long time. Can you provide a brief overview of SIG Scheduling and explain its role within the Kubernetes ecosystem? KN: As the name implies, our responsibility is to enhance scheduling within Kubernetes. Specifically, we develop the components that determine which Node is the best place for each Pod. In Kubernetes, our main focus is on maintaining the kube-scheduler , along with other scheduling-related components as part of our SIG subprojects. AP: I see, got it! That makes me curious-what recent innovations or developments has SIG Scheduling introduced to Kubernetes scheduling? KN: From a feature perspective, there have been several enhancements to PodTopologySpread recently. PodTopologySpread is a relatively new feature in the scheduler, and we are still in the process of gathering feedback and making improvements. Most recently, we have been focusing on a new internal enhancement called QueueingHint which aims to enhance scheduling throughput. Throughput is one of our crucial metrics in scheduling. Traditionally, we have primarily focused on optimizing the latency of each scheduling cycle. QueueingHint takes a different approach, optimizing when to retry scheduling, thereby reducing the likelihood of wasting scheduling cycles. A: