Detection-first observability
Detection-first observability is a tool that finds the problem and proves it — instead of storing everything and handing you a search bar to go hunting. It is the opposite of search-first.
Detection-first observability is an approach in which the tool continuously watches all your signals — logs, metrics, traces, and infrastructure — detects the problem on its own, and cites the evidence. The first thing you see is the answer, not a blank query box. It inverts search-first observability, which stores everything and leaves finding the incident to you.
The three jobs search-first pushes onto you — at 2am
Knowing where to look. Forty services, a dozen dashboards, three telemetry types in three views. Picking the right one under pressure is a skill you exercise exactly when your judgment is worst.
Building the detection yourself. Search catches nothing on its own. To be told before a human notices, you write alert rules one at a time — and they encode last quarter's failures, not the one about to take you down.
Assembling the root cause across tabs. Even after you find the symptom, you still walk from logs to traces to metrics, lining up timestamps by eye. Detection-first does that assembly for you and shows its work.
Epok is a detection-first engine. It learns what normal looks like for each service — per hour of day and day of week, not one flat threshold — and flags deviations on its own. New errors, silent services, spikes, drops, and cascades are caught automatically, with the first detection within minutes of pointing telemetry at it.
Every incident comes with a drafted root cause, and every claim links the exact log, span, or metric that produced it. See what Epok catches, or read the longer argument in Stop Searching, Start Being Told.
Stop searching. Start being told.
Point your telemetry at Epok and get the first detection in minutes. Every detector and full AI included in the trial.