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How on-demand Android environments lay the foundation for Android engineering Software engineering has evolved dramatically over the last decade. Development environments that once depended on dedicated hardware have become resources that can be provisioned, configured, and removed on demand. Infrastructure is now expected to be reproducible, automated, and integrated into continuous development workflows. However, Android has largely remained an exception.

A decade ago, Canonical launched Ubuntu 16.04 LTS (codenamed “Xenial Xerus”). As a Long-Term Support (LTS) release, it comes with 5 years of standard security coverage, which is doubled to a total of 10 years through Expanded Security Maintenance (ESM) for users with an Ubuntu Pro subscription. As of April 30, 2026, the 10-year ESM coverage for Ubuntu 16.04 LTS, under Ubuntu Pro, has officially reached its end of support.

For Independent Software Vendors (ISVs), delivering containerized applications to enterprise clients often means navigating a difficult trade-off between minimal image size and accurate security visibility. Traditional approaches can leave development teams battling severe CVE noise or, conversely, missing critical vulnerabilities entirely due to scanner blind spots.

You can now upgrade Ubuntu Server Virtual Machine Scale Sets on Azure to Ubuntu Pro without rebuilding the set. Your instances keep serving traffic. The change is a license update, not a new image. Users could already perform in-place upgrades to Ubuntu Pro for individual VMs. Now, we’re extending the feature to scale sets – groups of load balanced virtual machines that you can manage as a single unit.

When the codename for Ubuntu 26.10 was announced, I suspect there was a measurable surge in users searching for the definition of “stonking” across search engines and the various popular AI chatbots.

Open source provides the world with access to cutting-edge software, and the learning that comes with it. But how do you validate someone’s skills in an open ecosystem? Canonical Academy is a highly rigorous, job-focused qualification platform designed to empower individuals and enterprises with industry-recognized credentials. The platform addresses a critical gap in tech: validating real-world, hands-on capability rather than rote memorization.

Some support cases are routine. Others take you off the documented path entirely, into territory where the only way forward is deep, hands on open source expertise. This series looks at how Canonical Support navigates the unexpected: cases where standard playbooks aren’t enough, and a support engineer helps a customer find a solution in real time. This is one of those cases.

Across the global landscape, telecommunications operators have already deployed machine learning for predictive maintenance, customer care chatbots, and anomaly detection. However, as the industry transitions toward Autonomous Networks Level 4 (AN L4), where networks can make intent-driven, predictive decisions and perform closed-loop management with minimal human intervention, a fundamental architectural challenge has emerged.

Canonical is now part of the Open Secure AI Alliance, announced by NVIDIA with partners across cloud computing, cybersecurity, enterprise software, open source foundations, and AI research. The alliance aims to develop and share open technologies, techniques, and tools to safeguard software and agents in the age of AI.

Confidential computing is moving quickly. The foundation is already here: AMD SEV-SNP and Intel TDX have made it possible to run confidential virtual machines (VMs) with stronger protection for data in use. Ubuntu 26.04 Long Term Support (LTS) brings integrated host and guest support for both of these technologies, making confidential computing a native part of the Ubuntu virtualization offering..