[Slides]

Scheduler is one of the most frequently customized components in Kubernetes, owing to its expandability. However, too many schedulers lead to decision paralysis among users, which has been discussed extensively in the past KubeCons. To help mitigate the confusion of users, four maintainers from various community (Godel-Scheduler, Koordinator, Kubernetes SIG-Scheduling and Volcano) are invited to profile the background and usecases behind these projects.

He’s a handsome boy now.

San Siro.

Hiking to Harder Kulm, the top of Interlaken.

[Slides] [Project]

Kube-scheduler is a critical component to Kubernetes, responsible for placing the pod to the most suitable node. But how it works, can we customize it for advanced usage, what’s the best practice in large clusters. To answer these progressive questions, we’ll divide this session into two parts. If you’re a newbie to kube-scheduler, you may interest with the Intro part, if you’re a senior one, you can join our Deep Dive.

Parc des Princes.

New family member.

Stats

Coding

[Slides] [Project]

Compute demands for machine learning are growing rapidly nowadays. Ray, a unified computing framework, allows ML engineers to scale their workloads effortlessly without building complex computing infrastructures.

[Slides] [Project]

Kube-scheduler is a critical component to Kubernetes, responsible for placing the pod to the most suitable node. But how it works, can we customize it for advanced usage, what’s the best practice in large clusters. To answer these progressive questions, we’ll divide this session into two parts. If you’re a newbie to kube-scheduler, you may interest with the Intro part, if you’re a senior one, you can join our Deep Dive.