Which of the following items apply to anomaly detection? (Choose all that apply.)

Which of the following items apply to anomaly detection? (Choose all that apply.)
A . Use AD on KPIs that have an unestablished baseline of data points. This allows the ML pattern to perform it’s magic.
B . A minimum of 24 hours of data is needed for anomaly detection, and a minimum of 4 entities for cohesive analysis.
C . Anomaly detection automatically generates notable events when KPI data diverges from the pattern.
D . There are 3 types of anomaly detection supported in ITSI: adhoc, trending, and cohesive.

View Answer

Answer: B, C

Explanation:

Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/SI/AD

Anomaly detection is a feature of ITSI that uses machine learning to detect when KPI data deviates from a normal pattern. The following items apply to anomaly detection:

B) A minimum of 24 hours of data is needed for anomaly detection, and a minimum of 4 entities for cohesive analysis. This ensures that there is enough data to establish a baseline pattern and compare different entities within a service.

C) Anomaly detection automatically generates notable events when KPI data diverges from the pattern. You can configure the sensitivity and severity of the anomaly detection alerts and assign them to episodes or teams.

Reference: [Anomaly Detection]