Operations | Monitoring | ITSM | DevOps | Cloud

On February 17, 2026, YouTube went down for users worldwide. Starting around 8:00 PM ET, the platform's homepage, Shorts feed, sign-in system, smart TV apps, YouTube Music, and YouTube Kids all stopped working. Over 21,000 reports were logged on IsDown alone. The error message was the same everywhere: "Something went wrong." For consumer users, it was an inconvenience. For businesses that depend on YouTube — content teams, advertisers, media companies, live streamers — it was a blind spot.

Organizations using entry-level tools face limited visibility, slow issue response, and scalability challenges that increase downtime risks. ManageEngine solves this with its enterprise-grade, AI-powered platform, delivering end-to-end digital experience monitoring in cloud and On-Premise versions. Switching isn't only easy, it brings predictive intelligence, global precision, and seamless growth support to your workflows—protecting your revenue while improving your operational excellence.

How we built an AI agent that implements Jira tickets, creates merge requests, and tracks them on its own, and our journey to get to that point.

In a global microservices architecture, technical performance initially presents as a chaotic stream of disconnected telemetry. For a Technical Program Manager (TPM), success depends on the ability to move past these disconnected individual data points to identify stable patterns. If they have services entering critical states, looking at individual logs or traces is inefficient. Protecting system reliability requires an engine that can automate pattern recognition at scale.

AlloyScan enters 2026 with a fully redesigned interface and meaningful enhancements that improve clarity, visibility, and control across your IT environment.

Hybrid and multi-cloud monitoring breaks down when teams can’t connect signals to customer impact fast enough to act. Hybrid and multi-cloud sound simple: run some workloads in public cloud, keep some on-premises, and connect it all. But in practice, you’re managing dependencies across teams and systems, tools that don’t share context, and incidents that refuse to stay in one place.

Starting from today, Healthchecks.io users on all plans (Hobbyist, Supporter, Business, Business Plus) can invite an unlimited number of users into their projects. Previously, the limits were: 3 team members for Hobbyist and Supporter, 10 team members for Business, and unlimited team members for Business Plus. From now on, it is unlimited for all.

In the first two posts of this series, we explored how alert noise emerges from design decisions, and why notification lists fail to create accountability when responsibility is unclear. There’s a deeper issue underneath both of those problems. Many alerting systems are designed without being clear about the outcome they’re meant to produce. When teams don’t explicitly decide what they want to happen as a result of a signal, they default to the loudest option available.

When a database security incident happens, everyone turns to the security team. We look for a simple root cause analysis, and then we add a control, tighten a policy, and maybe even buy a silver bullet tool. We feel progress! But the incident didn’t start there. It started years earlier, when the organization made a series of perfectly reasonable decisions that quietly expanded the surface area and weakened the consistency of control.