Operations | Monitoring | ITSM | DevOps | Cloud

Sentry Snapshots diffs screenshots on every commit and blocks the PR if there are any visual changes so you can confirm they’re intentional. Users don’t interact with code, they interact with something they can see and touch. Snapshots gives you a lightweight way to test it. It’s easier than ever to change code. It’s also easier than ever to trade quality for speed. Modern codebases need guardrails to ensure correctness.

The world of IT incident response is no longer just about getting an alert. As systems grow more complex, teams need tools that not only notify them of a problem but also help them solve it quickly. In this evolving landscape, two names dominate the conversation: PagerDuty, the established enterprise leader, and incident.io, the modern, Slack-native challenger.

Three days, 20 talks at Devoxx France 2026. The through-line wasn't AI hype - it was discipline. Context engineering, code review under AI volume, and the local-vs-remote question now shaping security, cost, and sovereignty. Fabien is a senior software engineer at Qovery. He writes about platform engineering, AI tooling, context engineering, and the practical realities of running modern developer infrastructure.

Mission-critical networks are changing fast. Utilities, transport operators, and critical infrastructure providers are under pressure to deliver more data, more automation, and more resilience—without ever compromising reliability. The challenge is simple: legacy SDH/SONET networks were built for a different era. They still deliver reliability. But they can’t support what comes next.

Modern IT environments generate huge volumes of telemetry across infrastructure, applications, cloud services, and networks. Teams now have more data than ever, but that does not automatically lead to better decisions. In many organizations, the real problem is no longer visibility alone. It is the ability to identify which signals matter, understand what they mean, and respond before users or business services are affected.

You've felt it. You're deep in a flow state with Claude or Cursor, building the next great thing, and then you hit the wall. Time to leave your editor, open a browser, click through a console, copy a connection string, paste it back, and pray you didn't fumble a character. The vibe is gone. What if your AI agent could just... do it? Deploy the database. Create the Kafka topic. Ship the app. All without you ever leaving the conversation. Today, that's real.

The quick download: Most observability strategies overlook the internet layer that underpins every user’s digital experience, leaving it almost entirely unmonitored. Most IT teams monitor servers, networks, and applications, yet the infrastructure layer that carries traffic to users remains largely unmonitored.

Engineering teams are shipping more AI-generated code than ever, but at what cost? Learn how to build a telemetry pipeline to monitor Claude Code usage and costs directly in SquaredUp. It is estimated that 85-90% of engineering teams are now using AI coding assistants such as Claude, Codex and Cursor. This is not just for small-scale pilot projects— around 40% of all code now being shipped is AI-generated, and in start-ups the figure is around 95%. This can result in incredible productivity gains.

Picture this. It's the end of the financial year. Your audit team is clipboard in hand, walking floor to floor, cross-referencing serial numbers against a spreadsheet that was last updated six months ago. Three days in, two people are still checking warehouses, and someone has already found a printer that the system says was disposed of in 2022. This is how most enterprises still run their physical asset audits in 2026.