Search Results for "batch"

Volcano is a batch system built on Kubernetes. It provides a suite of mechanisms that are commonly required by many classes of batch & elastic workload including machine learning/deep learning, bioinformatics/genomics, and other "big data" applications. These types of applications typically run on generalized domain frameworks like TensorFlow, Spark, Ray, PyTorch, MPI, etc, which Volcano integrates with.

...It is a job-level manager that decides when a job should be admitted to start (as in pods can be created) and when it should stop (as in active pods should be deleted). Use Kueue to build a multi-tenant batch service with quotas and a hierarchy for sharing resources among teams in your organization. Based on the available quotas, Kueue decides when jobs should wait and when and where they should run. Kueue works in combination with standard kube-scheduler, cluster-autoscaler, and the rest of the Kubernetes ecosystem. This combination allows Kueue to run both on-prem and in the cloud, where resources can be heterogeneous, fungible, and dynamically provisioned.

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...It groups containers that make up an application into logical units for easy management and discovery. The first unified container-management system developed at Google was the system we internally call Borg. It was built to manage both long-running services and batch jobs, which had previously been handled by two separate systems: Babysitter and the Global Work Queue. The latter’s architecture strongly influenced Borg, but was focused on batch jobs; both predated Linux control groups. Kubernetes is known to be a descendant of Google's system BORG. The awesome-Kubernetes will now soon be available in the form of different releases and package bundles, It means that you can download the awesome Kubernetes release up to a certain period of time. ...

kube-batch is a batch scheduler for Kubernetes, providing mechanisms for applications which would like to run batch jobs leveraging Kubernetes. It builds upon a decade and a half of experience on running batch workloads at scale using several systems, combined with best-of-breed ideas and practices from the open source community.