spark-on-k8s-operator VS volcano

Compare spark-on-k8s-operator vs volcano and see what are their differences.

spark-on-k8s-operator

Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes. (by GoogleCloudPlatform)

volcano

A Cloud Native Batch System (Project under CNCF) (by volcano-sh)
Our great sponsors
  • Scout APM - A developer's best friend. Try free for 14-days
  • Nanos - Run Linux Software Faster and Safer than Linux with Unikernels
  • SaaSHub - Software Alternatives and Reviews
spark-on-k8s-operator volcano
5 1
1,748 2,063
2.7% 2.1%
7.4 9.4
1 day ago 5 days 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.

spark-on-k8s-operator

Posts with mentions or reviews of spark-on-k8s-operator. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-12.

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.

What are some alternatives?

When comparing spark-on-k8s-operator and volcano you can also consider the following projects:

enhancements - Enhancements tracking repo for Kubernetes

helm-operator - Successor: https://github.com/fluxcd/helm-controller — The Flux Helm Operator, once upon a time a solution for declarative Helming.

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

kubebuilder - Kubebuilder - SDK for building Kubernetes APIs using CRDs

kube-batch - A batch scheduler of kubernetes for high performance workload, e.g. AI/ML, BigData, HPC

github-actions-runner-operator - K8S operator for scheduling github actions runner pods

charts - ⚠️(OBSOLETE) Curated applications for Kubernetes

mysql-operator - Asynchronous MySQL Replication on Kubernetes using Percona Server and Openark's Orchestrator.

velero - Backup and migrate Kubernetes applications and their persistent volumes

cortex - A horizontally scalable, highly available, multi-tenant, long term Prometheus.

lakeFS - Git-like capabilities for your object storage