Operations | Monitoring | ITSM | DevOps | Cloud

Not every incident alert needs the same kind of response. One incident may need to wake someone up right away. Another may simply need to be picked up when the team starts work in the morning. Without a clear way to tell them apart, every incident feels equally urgent. That usually adds noise and makes incident response decisions harder than they need to be. This is where two questions help: In this guide, we’ll discuss what those questions mean and the four combinations that follow.

An alert in the middle of the night warns of a potential business failure. Manual incident response becomes more complex due to the overwhelming data from distributed and dynamic digital services. With an SRE agent, your engineering team can cut through alert clutter. They can sort through various signals quicker, decreasing burnout and achieving faster, more affordable resolutions. Operational resilience will see its next evolution with Agentic AI.

Quick Answer A Network Operations Center (NOC) — pronounced “knock” — is a centralized physical or virtual facility where IT professionals monitor, manage, and maintain an organization’s network infrastructure on a 24/7/365 basis. The NOC serves as the nerve center for detecting incidents, coordinating responses, and ensuring maximum network availability and performance.

A Playwright Check fails at 2 am. The login flow is broken. Until today, that alert triggered a human to get up, open the Checkly dashboard, copy Rocky AI root cause analysis (RCA), and then tell an agent to get to work. There were two AI agents, one incident, and no way for them to talk to each other. The extended checkly checks and new checkly rca CLI commands close that gap. Your coding agent can now pull Rocky AI's analysis into its ongoing work, read the diagnosis, and go fix the code.

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.