In this section, we'll try to summarize how Prelert solves the challenge of anomaly detection by first understanding why data visualization is a sufficient medium when it comes to pointing out an anomaly, and then we'll see why traditional alerting systems cannot be used at scale for anomaly detection.
Anomaly detection is the art of detecting things that shouldn't occur, or that differ from normal occurrences. Anomaly detection is the general name given to a statistical modeling technique used to identify unusual patterns in time-based events.
If we take the following dashboard, we can see different things happening:
IT ops dashboard with potential anomalies
In the preceding screenshot, we can see a significant drop in the first graph (point 1). This looks suspicious, and may indicate a problem. Now, compared with the rest of the charts alongside it, we see that the increases in points...
