Operations | Monitoring | ITSM | DevOps | Cloud

Personas are easy to create but often ignored. This is the first of two posts about how we developed archetypes to keep our personas fresh at Canonical. These are shared, machine-readable descriptions of our users that multiple teams and their agents can use. This post explains the system, its purpose, and its structure. The second post’ll cover how we maintain and update it. Personas should be functional tools.

Your site loads in Chrome fine. Then a deploy script, a webhook, or integration calls the same URL and gets this: Python says certificate verify failed: unable to get local issuer certificate. Node says unable to get local issuer certificate, or unable to verify the first certificate. It’s all the same problem. It’s a misconfiguration between your certificate and a trusted root. Either the server isn’t sending it, or the client doesn’t have it.

When you ask Grafana Assistant to build a dashboard or investigate an alert, you're doing so because there's work to be done. To do that work effectively, you need the right data, changes you can inspect, and conclusions supported by evidence. You also want Assistant to avoid mistakes and act quickly. Over the past six months, our team has worked hard to improve what makes those outcomes possible.

LogicMonitor and Work4Flow extend Edwin AI into ServiceNow with A2A, bringing alert context, metrics, root cause analysis, and diagnostic guidance into the incident workflow.

Recent Shopify checkout hijacking attacks reveal an important security risk that many online retailers may not realise exists: the difference between Shopify itself, the apps installed on a store, and the software customers interact with before reaching checkout. In this article In October 2026, customers visiting legitimate Shopify stores were redirected to fraudulent checkout pages designed to steal their payment details. The stores were real. The products were real.

Every time a smart utility meter transmits consumption data, a connected vehicle updates its telemetry, or a fleet of logistics trackers crosses international borders, seamless and uninterrupted connectivity is vital. Yet for years, managing Internet of Things (IoT) devices at scale has been constrained by physical SIM logistics, operator lock-in and remote SIM provisioning standards that were simply never built for autonomous, resource-constrained hardware.

A pull request lands with a function an AI assistant generated. It reads cleanly, passes the existing tests, and gets merged. Three weeks later it breaks, but only for accounts with a specific billing history. Nobody wrote a test for that condition because nobody was thinking about it when the code went in. Now someone has to debug logic they didn't reason through, against a failure they can't picture without the exact data that triggered it. Debugging someone else's code has always worked this way.