---
title: Blog posts tagged "AI Factory"
description: Canonical makes open source secure, reliable and easy to use, providing
  support for Ubuntu and a portfolio of enterprise-grade technologies. Founded in
  2004, Canonical operates globally with team members in over 80 countries.
url: https://canonical.com/blog/tag/ai-factory
---

# Blog posts tagged "AI Factory"

#### [From raw data to intelligent actions: inside our next-gen AI analytics data lake stack](https://canonical.com/blog/inside-our-next-gen-ai-analytics-data-lake-stack)

At Canonical, we believe organisations should be able to unlock the full value of their data without giving up control. That principle is at the heart of our next-generation enterprise data lake stack. It’s designed for organizations that need to build advanced analytics and AI capabilities while maintaining control over their data, infra

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AI

#### [What is RDMA over Converged Ethernet (RoCE)?](https://canonical.com/blog/what-is-rdma-over-converged-ethernet-roce)

Previous articles walked through RDMA (Remote Direct Memory Access) as a programming model and InfiniBand as the fabric that was built around it. Both led to the same conclusion, even if it was never stated outright: moving data, not compute, becomes the bottleneck once systems scale. So what happens when you want RDMA, but you’re

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AI

#### [What is InfiniBand?](https://canonical.com/blog/what-is-infiniband)

When distributed workloads stall because nodes cannot exchange small messages quickly and consistently, the network is the limiting factor. How do you solve that problem? InfiniBand offers one solution. InfiniBand is an interconnect, meaning the end-to-end communication system that links compute, storage, and accelerator nodes. It is impl

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AI

#### [The bare metal problem in AI Factories](https://canonical.com/blog/the-bare-metal-problem-in-ai-factories)

As AI platforms grow into large-scale “AI Factories,” the real bottleneck shifts from model design to operational complexity. With expensive GPU accelerators, hardware failures and inconsistent configurations lead directly to lost throughput and reduced return on investment. While Kubernetes orchestrates workloads, it cannot fix broken ph

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MAAS