Peloton - A Unified Scheduler for Web-scale Workloads on Mesos & Kubernetes
Efficient use of cluster resources is important for web-scale companies like Uber. Those companies require large-scale clusters for stateless, stateful and batch jobs. Today, web-scale companies have …
| Talk Title | Peloton - A Unified Scheduler for Web-scale Workloads on Mesos & Kubernetes |
| Speakers | Nitin Bahadur (Head Compute Cluster Infrastructure, Uber), Min Cai (Sr. Staff Engineer, Uber) |
| Conference | KubeCon + CloudNativeCon North America |
| Conf Tag | |
| Location | Seattle, WA, USA |
| Date | Dec 9-14, 2018 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Efficient use of cluster resources is important for web-scale companies like Uber. Those companies require large-scale clusters for stateless, stateful and batch jobs. Today, web-scale companies have built custom schedulers on top of Mesos due to lack of viable open-source solutions. Kubernetes has gained lots of momentum in recent years but lacks the scale and efficiency needed by web-scale companies. This talk introduces Peloton - A unified scheduler for mixed workloads that is horizontally scalable to 10K+ nodes and millions of containers. It has an extensible architecture and supports both Mesos and Kubernetes. Peloton manages compute resources more efficiently and guarantees hierarchical max-min fairness for different teams. It provides a seamless path for companies on Mesos to adopt Kubernetes. Peloton is also cloud agnostic and can be run on-prem or in any public Cloud.
