Skip to main content
  1. Blog
  2. Article

Canonical
on 1 August 2017

Ubuntu Foundations Development Summary: August 1, 2017


This newsletter is here to provide a status update from the Ubuntu Foundations Team. There will also be highlights provided for any interesting subjects the team may be working on. If you would like to reach the Foundations team, you can find us at the #ubuntu-devel channel on freenode.

Highlights

The State of the Archive

  • The ocaml 4.04 transition is done
  • Ubuntu 16.10 is now EOL
  • python3.6 is now the default in artful
  • The perl 5.26 transition has started in artful-proposed; expect delays in package migrations while the autopkgtest runners work through the backlog of related tests.
  • The transition to gcc 7 as default will begin in early August. https://lists.ubuntu.com/archives/ubuntu-devel/2017-July/039924.html

Upcoming Ubuntu Dates

Weekly Meeting

Related posts


Canonical
16 March 2026

Meet Canonical at NVIDIA GTC 2026: NVIDIA CUDA and NVIDIA Vera Rubin NVL72 support in Ubuntu 26.04 LTS

Ubuntu Article

Previewing at NVIDIA GTC 2026: NVIDIA CUDA support in Ubuntu 26.04 LTS, NVIDIA Vera Rubin NVL72 architecture support in Ubuntu 26.04, Canonical’s official Ubuntu image for NVIDIA Jetson Thor, upcoming support for NVIDIA DGX Station and NVIDIA DOCA-OFED, and NVIDIA RTX PRO 4500 support. NVIDIA GTC 2026 is here, bringing together the techno ...


Luci Stanescu
12 March 2026

AppArmor vulnerability fixes available

Ubuntu Article

Qualys discovered several vulnerabilities in the AppArmor code of the Linux kernel. These are being referred to as CrackArmor, while CVE IDs have not been assigned yet. All of the vulnerabilities require unprivileged local user access. The impact of these vulnerabilities ranges from denial of service to kernel memory information leak, rem ...


David Beamonte
11 March 2026

The bare metal problem in AI Factories

MAAS MAAS

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 ...