We have a production database. The load on the database varies at different times. I want to identify anomalies; for e.g, the number of database processes responding to user queries at 9 am is 100 for a given day. If the number is 200, then it's an anomaly and as the DBA, we need to check the DB immediately. The goal is to identify a pattern and alert when there's an event outside this pattern.
Day time processcount label Mon 09:00 100 Normal Mon 09:05 150 Normal Tue 09:00 200 Abnormal
I'm using pandas to collect the data but I'm not sure how to identify the pattern and report anomalies. The closest i could get is this thread How do I approach grouped anomaly detection?