Apache YuniKorn Core

Clone this repo:
  1. 1bfc579 [YUNIKORN-1337] Application state stuck in Accepted when placeholders are running and the job is deleted (#438) by Peter Bacsko · 14 days ago master
  2. d7d718e Expose reservation info in application rest endpoints (#437) by Ryan Lo · 3 weeks ago
  3. f7b1d52 [YUNIKORN-1086] expose reservation in node rest response (#436) by Ryan Lo · 3 weeks ago
  4. 3e6942f [YUNIKORN-1288] check for pseudo version (#434) by Wilfred Spiegelenburg · 6 weeks ago
  5. 46777b2 [YUNIKORN-1287] fix go.mod references (#433) by Wilfred Spiegelenburg · 6 weeks ago

Apache YuniKorn - A Universal Scheduler

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Apache YuniKorn is a light-weight, universal resource scheduler for container orchestrator systems. It is created to achieve fine-grained resource sharing for various workloads efficiently on a large scale, multi-tenant, and cloud-native environment. YuniKorn brings a unified, cross-platform, scheduling experience for mixed workloads that consist of stateless batch workloads and stateful services.

YuniKorn now supports K8s and can be deployed as a custom K8s scheduler. YuniKorn's architecture design also allows adding different shim layer and adopt to different ResourceManager implementation including Apache Hadoop YARN, or any other systems.

Get Started

See how to get started with running YuniKorn on Kubernetes, please read the documentation on yunikorn.apache.org.

Want to know more about the value of the YuniKorn project, and what YuniKorn can do? Here is some session recordings and demos.

Get Involved

Please read get involved document if you want to discuss issues, contribute your ideas, explore use cases, or participate the development.

If you want to contribute code to this repo, please read the developer doc. All the design docs are available here.

Code Structure

Apache YuniKorn project has the following git repositories:

The yunikorn-core is the brain of the scheduler, which makes placement decisions (allocate container X on node Y) according to the builtin rich scheduling policies. Scheduler core implementation is agnostic to the underneath resource manager system.