Operations | Monitoring | ITSM | DevOps | Cloud

Monitoring tools track what’s happening across your systems and send a Slack message or email when something looks off. But they don’t call anyone and they don’t escalate the incident. If that Slack message goes unseen at 3 AM on a Saturday, the incident just sits there until someone opens their dashboard. Incident alerting fills this gap. When an incident triggers, it contacts the right person directly through a phone call or their preferred channel.

It’s 2 a.m. An alert fires. You acknowledge it, pull up the monitoring dashboard, and immediately hit a wall: Which team owns this? What services does it impact? Worse: this is the third time this month you’ve been paged for the same issue, and you still don’t have a clear path to fix it. What should take minutes stretches into hours of Slack threads, escalation guesswork, and frantic context gathering.

Digital services are the engine of your modern business, but keeping them running feels like a constant battle. The rapid increase in the volume and speed of operational data is a direct result of growing architectures and more intricate workloads. Alert fatigue is causing your teams to be slow and reactive in addressing incidents, and this is a surefire path to burnout. The pace of this new reality is beyond what traditional, human-led processes can match.

By Doreen Jacobi, CEO of Derdack Corp Modern IT environments generate a high volume of alerts intended to improve detection and response. However, increasing alert volume does not necessarily improve operational outcomes. Alert fatigue is not simply a function of quantity. It is a predictable consequence of how humans process repeated stimuli, manage limited cognitive resources, and make decisions under sustained load.

Schedules are a core part of any on-call system. In ours, they define who to page and when. But people use them in lots of other ways too: checking their next shift, asking for cover while at the gym, keeping a Slack user group up to date, or updating a Linear triage responsibility. For many of our customers, they’re one of the main ways they interact with our product, and as they’re such a foundational part of On-call, it’s very important they work well.

The incident is over. The service is back up. The monitoring dashboard is green, the on-call engineer has stood down, and the post-incident review is on the calendar for Thursday. But there is a question that separates good operations teams from great ones: do you actually know what that incident cost you in terms of reliability commitments? Whether you breached an SLO. Whether a customer-facing SLA is now at risk.

Many teams remain bogged down by operational chaos and manual drudgery, even with access to a variety of automation solutions. These tools often operate in silos, creating disconnected islands of automation that require significant human effort to bridge. Agentic AI offers a path forward, creating a cohesive system that can intelligently and autonomously handle complex operational workflows.

When we talk about patient experience in hospitals, the conversation usually centers on clinical outcomes, bedside manner, or discharge satisfaction scores. But a growing body of research suggests that something far more basic, how quickly and clearly a care team communicates, may matter just as much. This isn’t just true inside the hospital walls.

Imagine you’re in the middle of a critical project, and suddenly, your system crashes. Or it’s the middle of the night, and your server goes down, affecting countless users. While no enterprise can avoid all IT incidents, how you handle them can significantly reduce their impact. Fast, effective IT incident management is critical, as major incidents are increasingly costly.