Operations | Monitoring | ITSM | DevOps | Cloud

Setting up a local Deep Learning environment can be a headache. Between managing CUDA drivers, resolving Python library conflicts, and ensuring you have enough GPU power, you often spend more time configuring than coding. Google Cloud and Canonical work together to solve this with Deep Learning VM Images, which use Ubuntu Accelerator Optimized OS as the base OS. These are pre-configured virtual machines optimized for data science and machine learning tasks.

In software engineering, we often talk about the “iron triangle” of constraints: time, resources, and features. You can rarely fix all three. At many companies, when scope creeps or resources get tight, the timeline is often the first element of the triangle to slip. At Canonical, we take a different approach. For us, time is the fixed constraint. This isn’t just about strict project management. It is a mechanism of trust.

Telecommunications networks are undergoing a cloud-native revolution. 5G promises ultra-fast connectivity and real-time services, but achieving those benefits requires an infrastructure that is agile, low-latency, and highly reliable. Kubernetes has emerged as a cornerstone for telecom operators to meet 5G demands.

5G continues to transform the telecommunications landscape, enabling massive device density, edge computing, and new enterprise use cases. However, operators still face significant cost pressures: from accelerating RAN modernization and 5G SA rollouts to energy demands and the shift to cloud-native network functions (CNFs). As telcos redesign their infrastructure strategies, open source has become a key lever to reduce costs, increase flexibility, and accelerate innovation.

Open source software is known for its ability to lower IT costs. But in 2025, affordability is only part of the story. A new Linux Foundation report, The strategic evolution of open source, reveals that open source has evolved from a tactical cost-saving measure to a mission-critical infrastructure supporting enterprise-grade investments, and delivering stronger business outcomes as a result.

Open source has come a long way. Recently I was watching a keynote address by our founder, Mark Shuttleworth, in which he discussed his vision for Ubuntu to provide quality support and security maintenance across the broad open source ecosystem, and it made me reflect on how far the open source software (OSS) community has come. Indeed, when looking at today’s interoperable open source landscape, the fragmented, disconnected landscape of the past seems like another planet.

Sylva 1.5 becomes the first release to include Kubernetes 1.32, bringing the latest open source cloud-native capabilities to the European telecommunications industry With the launch of Sylva 1.5, Canonical Kubernetes is now officially part of the project’s reference architecture. This follows its earlier availability as a technology preview in Sylva 1.4.

Ubuntu images on Microsoft Azure have recently started shipping with the open source package azure-vm-utils included by default. Azure VM utils is a package that provides essential utilities and udev rules to optimize the Linux experience on Azure. This change results in more reliable disks, smoother networking on accelerated setups, and fewer tweaks to get things running. Here’s what you need to know.

On October 23rd, we announced the beta availability of silicon-optimized AI models in Ubuntu. Developers can locally install DeepSeek R1 and Qwen 2.5 VL with a single command, benefiting from maximized hardware performance and automated dependency management. Application developers can access the local API of a quantized generative AI (GenAI) model with runtime optimizations for efficient performance on their CPU, GPU, or NPU.

Ubuntu 25.10 Questing Quokka has landed, marking the final interim release before Ubuntu 26.04 LTS, and it’s a bold one. Interim releases have always been the proving grounds for features that define the next LTS, and this cycle is no exception.