# Kubernetes at LinkedIn, with Ahmet Alp Balkan and Ronak Nathani

Page: https://stenobird.com/podcast/kubernetes-podcast-from-google/kubernetes-at-linkedin-with-ahmet-alp-balkan-and-ronak-nathani
Text version: https://stenobird.com/podcast/kubernetes-podcast-from-google/kubernetes-at-linkedin-with-ahmet-alp-balkan-and-ronak-nathani.md
Podcast: [Kubernetes Podcast from Google](https://stenobird.com/podcast/kubernetes-podcast-from-google)
Published: 2025-03-25T16:06:00+00:00
Episode link: https://e780d51f-f115-44a6-8252-aed9216bb521.libsyn.com/kubernetes-at-linkedin-with-ahmet-alp-balkan-and-ronak-nathani
Audio file: https://traffic.libsyn.com/secure/e780d51f-f115-44a6-8252-aed9216bb521/KPod249.mp3?dest-id=3486674
Processing state: processed
JSON: https://stenobird.com/v1/public/podcasts/kubernetes-podcast-from-google/episodes/kubernetes-at-linkedin-with-ahmet-alp-balkan-and-ronak-nathani
Duration seconds: 2522

## Resource

LinkedIn engineers reveal how they manage massive Kubernetes clusters on bare metal, focusing on handling latency-sensitive workloads and hardware fragmentation. The discussion explores the complexities of building an opinionated platform that abstracts infrastructure for developers while maintaining high performance.

## Highlights
- Main idea: LinkedIn uses a custom, opinionated platform on bare metal to manage hardware generations and prevent fragmentation
- Practical takeaway: Use node profiles and specific pools to isolate latency-sensitive applications from older hardware generations
- Failure mode: Large-scale clusters can cause controller informers to fail to sync, potentially leading to catastrophic state loss like label clearing
- Main idea: Kubernetes can be adapted for stateful workloads if you control the full stack from bare metal to disk attachment
- Practical takeaway: Abstracting Kubernetes complexity via custom APIs helps developers focus on resources like CPU and memory rather than low-level networking

## Topics

Kubernetes, Bare Metal, Infrastructure at Scale, Cloud Native, Custom Controllers, LinkedIn Engineering, Site Reliability Engineering, Container Orchestration

## Chapters
- 1:00 — Kubernetes Ecosystem News: Updates on CubeFS graduation to CNCF and Canonical's announcement regarding 12-year Kubernetes Long Term Support.
- 4:10 — Running Kubernetes on Bare Metal: An exploration of LinkedIn's transition from legacy containerization to a large-scale Kubernetes implementation on bare metal.
- 10:25 — Networking and Flat Data Center Architectures: Discussion on bypassing standard CNI plugins like Flannel in favor of a flat, routable data center network.
- 16:40 — Managing Hardware Skews and Fragmentation: How to handle different CPU generations and the challenges of preventing resource fragmentation in multi-tenant pools.
- 22:50 — The Power of Custom Controllers: The necessity and reality of developing custom Kubernetes controllers and CRDs to extend platform functionality.
- 32:15 — Abstracting Complexity for Developers: Providing an opinionated interface that allows engineers to specify compute resources without managing low-level Kubernetes primitives.
- 38:45 — Lessons from Large-Scale Failures: A deep dive into how controller informer timeouts in massive clusters can lead to unintended side effects like mass label deletion.

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## Transcript

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