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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Troubleshooting ITSI | 10% | - Diagnose common issues - Resolve configuration and operational problems - Monitor ITSI performance |
| Topic 2: Services and KPIs | 15% | - Define services and KPIs - Configure KPI thresholds and alerts - Use entities in KPI searches - Manage service dependencies |
| Topic 3: Anomaly Detection | 5% | - Enable anomaly detection - Work with anomaly events |
| Topic 4: Access Control and Security | 5% | - Create service-level teams - Configure user roles and permissions |
| Topic 5: ITSI Architecture and Deployment | 10% | - Manage ITSI modules - Describe ITSI architecture - Plan and design deployment |
| Topic 6: Introducing ITSI | 5% | - Identify what ITSI does - Describe reasons for using ITSI - Examine the ITSI user interface |
| Topic 7: Aggregation Policies | 5% | - Create aggregation policies - Use smart mode aggregation |
| Topic 8: Event Analytics | 5% | - Describe Event Analytics features - Configure and use Event Analytics |
| Topic 9: Managing Notable Events | 10% | - Customize notable event views - Describe multi-KPI alerts - Work with notable events - Describe notable events workflow - Define key notable events terms and relationships |
| Topic 10: Correlation and Multi-KPI Searches | 5% | - Create multi-KPI alerts - Define correlation searches - Manage notable event storage |
| Topic 11: Glass Tables | 5% | - Use glass tables - Configure glass tables - Design glass tables - Describe glass tables |
| Topic 12: Deep Dives | 10% | - Create and customize deep dives - Describe deep dive concepts - Use default deep dives |
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NEW QUESTION # 56
Which of the following is a good use case regarding defining entities for a service?
Answer: B
Explanation:
Define entities before creating services. When you configure a service, you can specify entity matching rules based on entity aliases that automatically add the entities to your service.
Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/Entity/About A is the correct answer because defining entities for a service allows you to automatically associate entities to services using multiple entity aliases. Entity aliases are alternative names or identifiers for an entity, such as host name, IP address, MAC address, or DNS name. ITSI matches entity aliases to fields in your data sources and assigns entities to services accordingly. This way, you can avoid manually adding entities to each service and ensure that your services reflect the latest changes in your environment. References: Define entities for a service in ITSI
NEW QUESTION # 57
Fritz is looking at a Deep Dive with a lane showing the average percent of CPU usage across the four web servers in the web farm. Seeing a spike, he wants to add the graphs of each server on the swim lane, and selects the Lane Overlay Options to do so. No entity overlays are available for the KPI.
What is wrong with his KPI configuration?
Answer: B
Explanation:
In Splunk ITSI, swim lane overlays depend on a KPI beingsplit by entityso that each entity's individual time series can be displayed separately in the Deep Dive view. When a KPI is aggregated without an entity split, it produces asingle time seriesvalue at each timestamp representing the entire group (in this case, the average CPU across all web servers). Because that KPI does not contain per#entity values, ITSI has nothing to overlay
- therefore no entity overlays appear in the Lane Overlay Options. This configuration mistake often happens when a KPI is defined to average values across sources without specifying an entity dimension on which to split results. Entity filtering is a separate feature that enables restricting which entities are considered in display or analytics and does not control availability of swim lane overlays; pseudo#entities are artificial names that do not reflect actual system identities and are not relevant to this error; and having only three entities versus four would not prevent overlays from appearing if the KPI were correctly split by entity. The correct fix is to edit the KPI definition and configure it tosplit the metric results by the server entity field, such that each server has its own time series. This then enables Fritz to overlay the individual server CPU graphs on the swim lane as intended.
NEW QUESTION # 58
Which of the following accurately describes base searches used for KPIs in a service?
Answer: C
Explanation:
Explanation
KPI base searches let you share a search definition across multiple KPIs in IT Service Intelligence (ITSI).
Create base searches to consolidate multiple similar KPIs, reduce search load, and improve search performance.
NEW QUESTION # 59
What is the minimum number of entities a KPI must be split by in order to use Entity Cohesion anomaly detection?
Answer: C
Explanation:
For Entity Cohesion anomaly detection in Splunk IT Service Intelligence (ITSI), the minimum number of entities a KPI must be split by is 2. Entity Cohesion as a method of anomaly detection focuses on identifying anomalies based on the deviation of an entity's behavior in comparison to other entities within the same group or cohort. By requiring a minimum of only two entities, ITSI allows for the comparison of entities to detect significant deviations in one entity's performance or behavior, which could indicate potential issues. This method leverages the idea that entities performing similar functions or within the same service should exhibit similar patterns of behavior, and significant deviations could be indicative of anomalies. The low minimum requirement of two entities ensures that this powerful anomaly detection feature can be utilized even in smaller environments.
NEW QUESTION # 60
ITSI Saved Search Scheduling is configured to use realtime_schedule = 0. Which statement is accurate about this configuration?
Answer: A
Explanation:
ITSI Saved Search Scheduling is a feature that allows you to schedule searches that run periodically to populate the data for your KPIs. You can configure various settings for your scheduled searches, such as the search frequency, the time range, the cron expression, and so on. One of the settings is realtime_schedule, which controls the way the scheduler computes the next execution time of a scheduled search. The statement that is accurate about this configuration is:
B) If this value is set to 0, the scheduler bases its determination of the next scheduled search on the last search execution time. This is called continuous scheduling. If set to 0, the scheduler never skips scheduled execution periods. However, the execution of the saved search might fall behind depending on the scheduler's load. Use continuous scheduling whenever you enable the summary index option.
The other statements are not accurate because:
A) If this value is set to 0, the scheduler bases its determination of the next scheduled search execution time on the current time. This is not true because this is what happens when the value is set to 1, not 0.
C) If this value is set to 0, the scheduler may skip scheduled execution periods. This is not true because this is what happens when the value is set to 1, not 0.
D) If this value is set to 0, the scheduler might skip some execution periods to make sure that the scheduler is executing the searches running over the most recent time range. This is not true because this is what happens when the value is set to 1, not 0.
NEW QUESTION # 61
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