volcano VS kube-batch

Compare volcano vs kube-batch and see what are their differences.

volcano

A Cloud Native Batch System (Project under CNCF) (by volcano-sh)

kube-batch

A batch scheduler of kubernetes for high performance workload, e.g. AI/ML, BigData, HPC (by kubernetes-sigs)
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volcano kube-batch
1 1
2,390 953
5.2% 1.9%
9.3 0.0
5 days ago 6 months ago
Go Go
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

volcano

Posts with mentions or reviews of volcano. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-12.
  • My Journey With Spark On Kubernetes... In Python (1/3)
    4 projects | dev.to | 12 Apr 2021
    For our experiments, we will use Volcano which is a batch scheduler for Kubernetes, well-suited for scheduling Spark applications pods with a better efficiency than the default kube-scheduler. The main reason is that Volcano allows "group scheduling" or "gang scheduling": while the default scheduler of Kubernetes schedules containers one by one, Volcano ensures that a gang of related containers (here, the Spark driver and its executors) can be scheduled at the same time. If for any reason it is not possible to deploy all the containers in a gang, Volcano will not schedule that gang. This article explains in more detail the reasons for using Volcano.

kube-batch

Posts with mentions or reviews of kube-batch. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-01-25.

What are some alternatives?

When comparing volcano and kube-batch you can also consider the following projects:

spark-on-k8s-operator - Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.

argo - Workflow engine for Kubernetes

mpi-operator - Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.)

warewulf - Warewulf is a stateless and diskless container operating system provisioning system for large clusters of bare metal and/or virtual systems.

singularity-cri - The Singularity implementation of the Kubernetes Container Runtime Interface

sidekick - High Performance HTTP Sidecar Load Balancer

sarus - OCI-compatible engine to deploy Linux containers on HPC environments.

kube-scheduler-simulator - A web-based simulator for the Kubernetes scheduler

descheduler - Descheduler for Kubernetes [Moved to: https://github.com/kubernetes-sigs/descheduler]

charts - ⚠️(OBSOLETE) Curated applications for Kubernetes

kubernetes-operator-roiergasias - 'Roiergasias' kubernetes operator is meant to address a fundamental requirement of any data science / machine learning project running their pipelines on Kubernetes - which is to quickly provision a declarative data pipeline (on demand) for their various project needs using simple kubectl commands. Basically, implementing the concept of No Ops. The fundamental principle is to utilise best of docker, kubernetes and programming language features to run a workflow with minimal workflow definition syntax. It is a Go based workflow running on command line or Kubernetes with the help of a custom operator for a quick and automated data pipeline for your machine learning projects (a flavor of MLOps).