Segmind Vs KubeFlow

KubeFlow is an open source project that provides tools to run your ML workflows on Kubernetes. It helps engineers build pipelines that are inherently scalable and portable.

Although Segmind also provides you tools to run your ML Workflows on K8s, there are a few key diffrences, making it a higher level platform. Key differentiating points are shared below:

Time to setup & configure

It takes Segmind < 10 mins to configure your cluster and get your started with your MLOps with the right security configuration. On the other hand, it might take over 2 weeks to get started with Kubeflow.

Rich toolset

MLFlow, Datastore, Jupyter IDE, VS Code IDE and more such best-of-breed open-source systems come out-of-the-box. Without these basic toolsets, it becomes very hard to manage your experiments.

Cost monitoring tools

When running a K8s cluster, multiple resources are created all the time. Segmind's cost monitoring setup helps you monitor costs closely. Get reports based on project-wise, user-wise and more such insights.

Updated 10 Jan 2022
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