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A look into Ubuntu Core 26: Deploying AI models on Renesas RZ/V series for production

Welcome to this blog series which explores innovative uses of Ubuntu Core. Throughout this series, Canonical’s Engineers will show what you can build with our releases, highlighting the features and tools available to you. In this blog, Asa Mirzaieva, engineer from the Silicon Alliances team, will show you how to deploy optimised AI models on Renesas RZ/V series hardware using the Dynamically Reconfigurable Processor for AI (DRP-AI).

Variable Sharing and Dynamic Step Conditions | Bitbucket Blitz | Atlassian

Bitbucket Pipelines lets you invoke child pipelines from a parent step, but until now there was no way to pass information between them. Variable sharing changes that. You can define variables in a parent step and pass them directly to child pipelines as custom pipeline variables. With dynamic step conditions, those child pipelines can make decisions at runtime based on the values they receive, like skipping a deployment when a security scan detects critical vulnerabilities.

Prevent container image overwrites with immutable tags in Bitbucket Packages

We’re excited to announce that immutable tags are now available for the Bitbucket Packages container registry. With immutable tags, workspace admins can set container image tags from being overwritten, moved, or modified after they’re first pushed.

Testing AI Code is a Security Nightmare? #Speedscale #DevOps #Kubernetes #AICoding #SoftwareTesting

AI can write a feature in seconds, but where are you testing it? Sending production traffic, API payloads, and auth headers to a third-party SaaS is a massive security risk. In this video, we break down why the Bring Your Own Cloud (BYOC) model is the ultimate fix for DevSecOps. Learn how to safely test AI-generated code against real production traffic entirely within your own VPC or Kubernetes cluster. No data leaks, no massive DLP pipelines, and no endless masking rules.

Minga cut infra costs 30-40% - and it scales itself | Control Plane

Minga checks in 1.5 million students across the eastern seaboard by 8:30 AM Eastern — then lets that infrastructure wind down an hour later. After migrating to Control Plane, they cut infrastructure costs 30–40% and traded fragile, manual scaling for a platform that scales itself.

Configure Ubuntu with YAML | Ubuntu Summit 26.04

Learn how to configure Ubuntu at launch using declarative, idempotent instructions stored in a version-controlled YAML file. In this talk, Rajan explains how this approach minimizes arbitrary commands, reduces risks of command injection and privilege escalation, and ensures validation and error handling. This is relevant on major public and private clouds, and virtualization solutions ranging from VMware, WSL, LXD, Multipass, Proxmox, and more.

Megaport Storage Marks the Next Step Toward Automated Infrastructure at Scale

Built as a globally distributed storage platform integrated directly into the Megaport backbone and co-located with Latitude.sh compute infrastructure, Megaport Storage simplifies how organizations store, move, and access data across distributed environments with a unified infrastructure experience spanning compute, network, and storage. For years, enterprise infrastructure has moved toward abstraction. Compute became elastic. Networks became software-defined.

uPKI: improving certificate revocation on Linux | Ubuntu Summit 26.04

What is uPKI? While web browsers automatically check if an HTTPS certificate has been revoked, other Linux command-line tools and applications usually skip this check. That leaves applications vulnerable to compromised or misissued certificates many months after this is discovered. In their talk, Joe Birr-Pixton and Dirkjan Ochtman will be introducing uPKI: a new effort to bring browser-grade certificate infrastructure to Linux. This effort is funded by Canonical, engineered by the maintainers of rustls, and builds on foundational work from Mozilla.

AI inference vs. training: What they are and how they differ

AI inference and training are terms you'd run into if you have been around software engineering or even just scrolled through the news. Both are integral to delivering the AI-powered experiences we have come to expect from many of the applications we use daily. According to McKinsey, by 2030 inference will overtake training as the dominant workload in AI data centers, making up more than half of all AI compute and roughly 30-40% of total data center demand.

GitHub Copilot Price Hike Developers Outraged! V2

What used to be $50 a month is now $3,000 — overnight. Microsoft just moved GitHub Copilot to token-based billing, and devs are split between calling it a "rug pull" and admitting someone always had to pay the bill. Here's the part that should worry every engineering leader: most can't tell you what percentage of their AI-generated code actually ships, or where the tokens went. When the meter is running on every prompt, "it feels productive" isn't good enough — you need to know that bug cost you $2,700 in tokens to fix.