Volcano vs Yunikorn vs Knative

This page summarizes the projects mentioned and recommended in the original post on /r/kubernetes

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  • scheduler-plugins

    Repository for out-of-tree scheduler plugins based on scheduler framework.

    tldr; Knative Batch Job provider should support the respective coscheduling and kube-batch support. We had developed an in-house one for KubeFlow, from scratch. We had added Apache Arrow support into knative-serving with the respective CloudEvents interop layer, natively (i.e. secure shmem via IPC namespace, instead of message passing on the same host). We use it as a direct replacement for Apache Arrow Ballista, and had planned researching further DataFusion compat layer. Almost any modern ETL is pretty dubious without Apache Arrow.

  • kube-batch

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

    tldr; Knative Batch Job provider should support the respective coscheduling and kube-batch support. We had developed an in-house one for KubeFlow, from scratch. We had added Apache Arrow support into knative-serving with the respective CloudEvents interop layer, natively (i.e. secure shmem via IPC namespace, instead of message passing on the same host). We use it as a direct replacement for Apache Arrow Ballista, and had planned researching further DataFusion compat layer. Almost any modern ETL is pretty dubious without Apache Arrow.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  • PaddlePaddle

    PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

    Volcano is a batch scheduler on top of Kube-batch targetting spark-operator, plain old MPI, chinesium paddlepaddle, and Kromwell HPC.

  • cromwell

    Scientific workflow engine designed for simplicity & scalability. Trivially transition between one off use cases to massive scale production environments

    Volcano is a batch scheduler on top of Kube-batch targetting spark-operator, plain old MPI, chinesium paddlepaddle, and Kromwell HPC.

  • arena

    A CLI for Kubeflow. (by kubeflow)

    tldr; you should start with KubeFlow 99% of the time. The respective job scheduling workflows (including volano) can be managed with Kubeflow Arena. Vulcano is ok, but I personally prefer Nvidia's Merlin + Triton inference on top of ONNX and MS ONNX Runtime. I do like to train with GPU's on Merlin in GKE (TabularNV and HugeCTR's tbe), and run TFKeras ReLu models on CPU's with OpenVino on AWS EKS, to optimize costs a bit. I do use Kubeflow on top of TektonCD for OpenShift, while some folks do prefer Argo Workflows and Apache Airflow, in the end - it's all DAG pipelines, so doesn't really matter.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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