# Scaling ML Training on Kubernetes with JobSet

DevFeed: [Scaling ML Training on Kubernetes with JobSet](<https://devfeed.tech/articles/scaling-ml-training-on-kubernetes-with-jobset-60.md>)

Original publisher: [Read original article](<https://blog.abhimanyu-saharan.com/posts/scaling-ml-training-on-kubernetes-with-jobset>)

Author: Abhimanyu Saharan

Published: 2025-05-05T00:00:00Z

Content type: article

Language: en

Sources: [Abhimanyu Saharan](<https://devfeed.tech/sources/abhimanyu-s-blog.md>)

Topics: [Kubernetes](<https://devfeed.tech/topics/kubernetes.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [API](<https://devfeed.tech/topics/api.md>), [jobs](<https://devfeed.tech/topics/jobs.md>)

Tags: [api](<https://devfeed.tech/tags/api.md>), [distributed](<https://devfeed.tech/tags/distributed.md>), [hpc](<https://devfeed.tech/tags/hpc.md>), [jobs](<https://devfeed.tech/tags/jobs.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [ml](<https://devfeed.tech/tags/ml.md>), [training](<https://devfeed.tech/tags/training.md>)

## AI overview

The article introduces JobSet, a Kubernetes-native API for managing distributed machine learning and high-performance computing jobs. It highlights multi-role pods, topology-aware placement, and scaling capabilities.

## Source excerpt

JobSet is a Kubernetes-native API for managing distributed ML and HPC jobs with support for multi-role pods, topology-aware placement, and scaling.