Skip to main content
  1. Blog
  2. Article

Jane Silber
on 8 December 2010

Thanks and good luck to Matt Asay


Matt Asay joined Canonical in February this year and quickly proved instrumental in aligning strategic goals and operational activities. Unfortunately for us, Matt will be leaving Canonical December 17 for the lure of an early-stage start-up. While his time here has been relatively short, we all appreciate the positive impact he has had in many areas and I will personally be very sorry to see him go.

Matt is joining Strobe, an early stage start-up at the nexus of open source and the open web, much like Matt himself. He will be taking a senior business development position, and that opportunity provides an irresistible forum for him to exercise his skills in a customer-facing role at a small start-up.

While we will miss Matt, Canonical operations remain strong. We will recruit to replace Matt, hoping to find someone who carries on his love of Dilbert cartoons and The Smiths! We all wish Matt well in his new adventure.

Related posts


estelacarmona
11 June 2026

The next era of telco clouds: get open infrastructure choice with Sylva and Canonical Kubernetes

5G Article

Achieving vendor neutrality in telco clouds requires an infrastructure layer that respects open standards, without wrapping them in rigid platform layers. By combining upstream alignment with up to 15 years of support longevity, Canonical’s approach to Sylva is built around a requirement that matters deeply to telcos: follow upstream clou ...


Benjamin Ryzman
9 June 2026

What is RDMA over Converged Ethernet (RoCE)?

AI Networking

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 ...


Freyja Cooper
5 June 2026

Beyond tokens per watt – using Ubuntu 26.04 LTS for AI

AI Article

Tokens per watt (TpW) – the measure of useful AI work produced per watt of energy consumed – is the metric at top of mind for CEOs, heads of AI, and infrastructure teams alike. With the tremendous cost of GPU clusters, extracting as much value as possible from the expense is critical. But in the ...