최신Splunk IT Service Intelligence Certified Admin - SPLK-3002무료샘플문제

A. Plan to build as many data models as possible for ITSI to leverage

B. Check if the data could leverage pre-built KPIs from modules, then use the correct TA to onboard the data.

C. Use | stats functions in custom fields to prepare the data for KPI calculations.

D. Make sure that all fields conform to CIM, then use the corresponding module to import related services.

A. An anomaly alert will appear in core splunk, in index=main.

B. A separate correlation search needs to be created in order to see it.

C. An anomaly alert will appear as a notable event in Episode Review.

D. A SNMP trap will be sent.

A. Raising an alert when one or more KPIs indicate an outage is occurring.

B. Comparing anomaly detection between two KPIs.

C. Using machine learning to evaluate when data falls outside of an expected pattern.

D. Comparing content between two notable events.

A. Service dependencies.

B. Ad-hoc search.

C. Service templates.

D. Service swapping.

A. Anomaly detection.

B. Maintenance windows

C. Adaptive thresholding.

D. Correlation searches.

A. Linear regression

B. Infantile regression

C. Entity cohesion

D. Standard deviation

A. Service swapping configuration.

B. Adding KPI metric lanes to glass tables.

C. Correlation search creation.

D. Creating glass tables.

A. Create a custom service analyzer from selected deep dive lanes.

B. Create a predictive analysis model from the deep dive to warn of future service degradation.

C. Create a Multi-KPI alert from the deep dive's current state to warn of similar situations in the future.

D. Create an anomaly detection alert to show when the same pattern begins in the future.

A. Use AD on KPIs that have an unestablished baseline of data points. This allows the ML pattern to perform it's magic.

B. Anomaly detection automatically generates notable events when KPI data diverges from the pattern.

C. A minimum of 24 hours of data is needed for anomaly detection, and a minimum of 4 entities for cohesive analysis.

D. There are 3 types of anomaly detection supported in ITSI: adhoc, trending, and cohesive.

A. Maintenance mode slots are scheduled on a per hour basis.

B. KPIs are shown in blue while in maintenance mode.

C. Once the window is over, KPIs and notable events will begin to be generated again.

D. Service health scores and KPI events are deleted until the window is over.