---
title: "Migrating Large-Scale Interactive Compute Workloads to Kubernetes Without Disruption"
url: https://daily.dev/posts/migrating-large-scale-interactive-compute-workloads-to-kubernetes-without-disruption-ojejszl4g
source_url: https://www.uber.com/blog/migrating-large-scale-compute-workloads-to-kubernetes/
type: article
source: "Uber Engineering"
published: 2025-05-08T15:04:01.250Z
updated: 2025-05-08T15:04:19.509Z
tags: ["machine-learning", "cloud", "data-science", "devops", "kubernetes"]
reading_time: 12
upvotes: 1
comments: 0
language: en
---

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# Migrating Large-Scale Interactive Compute Workloads to Kubernetes Without Disruption

**[Uber Engineering](https://daily.dev/sources/uber)** · 12 min read · 1 upvotes · 0 comments

## Summary

Uber shares insights into migrating large-scale interactive workloads from Peloton to Kubernetes. The process involved migrating 3,500 Jupyter and RStudio sessions with minimal disruption, leveraging Kubernetes features like Jobs and Federation for improved efficiency. Challenges included managing interactive sessions, NFS support, and maintaining user-installed packages across platform transitions. This migration unlocked better resource sharing and cloud integration for the company.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.uber.com/blog/migrating-large-scale-compute-workloads-to-kubernetes/>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#cloud](https://daily.dev/tags/cloud), [#data-science](https://daily.dev/tags/data-science), [#devops](https://daily.dev/tags/devops), [#kubernetes](https://daily.dev/tags/kubernetes)

[View this post on daily.dev](https://daily.dev/posts/migrating-large-scale-interactive-compute-workloads-to-kubernetes-without-disruption-ojejszl4g)