Splunk SPLK-3002 Splunk IT Service Intelligence Certified Admin Exam Exam Practice Test

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.

To utilize Adaptive Thresholding in Splunk IT Service Intelligence (ITSI), the minimum requirement for a set of Key Performance Indicator (KPI) data is that it must be at least 7 days old. Adaptive Thresholding uses historical data to dynamically adjust thresholds based on observed patterns and trends. Having a minimum of 7 days worth of data allows the system to analyze a sufficient amount of information to identify normal ranges and variances in KPI behavior, thereby setting more accurate and contextually relevant thresholds. This requirement ensures that the adaptive thresholds are based on a meaningful data set that reflects the typical operational conditions of the monitored services.

1. From the ITSI main menu, click Configuration > Notable Event Aggregation Policies.

2. Select a custom policy or the Default Policy.

3. Under Smart Mode grouping, enable Smart Mode.

4. Click Select fields. A dialog displays the fields found in your notable events from the last 24 hours.

Service templates in Splunk IT Service Intelligence (ITSI) are designed to streamline the creation of services by providing pre-defined configurations:

B.Service templates contain KPIs and KPI thresholds:This allows for the standardized deployment of services with predefined performance indicators and their associated thresholds, ensuring consistency across similar services.

C.Service templates can contain specific or generic entity rules:These rules define how entities are associated with services created from the template, allowing for both broad and targeted applicability.

While service templates contain configurations for KPIs, thresholds, and entity rules, the ability to modify templates after services have been instantiated from them is limited. Changes to a template do not retroactively affect services already created from that template. Moreover, service templates do not inherently contain domain-specific dashboards or deep dives; these are created separately within ITSI.

After you configure KPI thresholds, you can set up alerts to notify you when aggregate KPI severities change. ITSI generates notable events in Episode Review based on the alerting rules you configure.

Anomaly detection generates notable events when a KPI IT Service Intelligence (ITSI) deviates from an expected pattern.

Notable events are typically generated by a correlation search.

The IT Service Intelligence (ITSI) metrics summary index, itsi_summary_metrics, is a metrics-based summary index that stores KPI data.

In Splunk IT Service Intelligence (ITSI), entities represent infrastructure components, applications, or other elements that are monitored. Each entity is uniquely identified by its entity ID, and entities can be associated with one or more services through the concept of aliases. A problem arises when two or more entities have the same value in a single alias field because aliases are used to match events to entities in ITSI. If multiple entities share the same alias value, ITSI might incorrectly associate data with the wrong entity, leading to inaccurate monitoring and analytics. This scenario requires correction to ensure that each alias uniquely identifies a single entity, thereby maintaining the integrity of the monitoring and analysis process within ITSI. The uniqueness of service IDs, entity IDs, and entity key values in info fields is also important but does not typically present the same level of issue as duplicate values in an alias field.

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.

 D is the correct answer because ITSI provides multiple ways to delete multiple duplicate entities. You can use a CSV upload to overwrite existing entities with new or updated information, or delete them by setting the action field to delete. You can also use the entity lister page to select multiple entities and delete them in bulk. Alternatively, you can use a search command called | deleteentity to delete entities that match certain criteria. References: Create and update entities using a CSV file in ITSI, Delete entities in bulk in ITSI, Delete entities using the | deleteentity command in ITSI

B is the correct answer because adaptive thresholding is a feature of ITSI that allows you to dynamically adjust KPI thresholds based on historical patterns and trends. Adaptive thresholding requires a time buffer of at least 15 minutes to calculate the thresholds based on the previous data points. The time buffer ensures that there is enough data to perform the calculations and avoid false positives or negatives. References: Configure adaptive thresholding for a KPI in ITSI

When creating a custom deep dive, services or KPIs that are in maintenance mode are shown in gray color in the topology view. This indicates that they are not actively monitored and do not generate alerts or notable events. References: Deep Dives

In a distributed Splunk Enterprise deployment running Splunk IT Service Intelligence (ITSI), theSA‑IndexCreationapp is responsible for creating the necessary custom indexes (such as itsi_summary, itsi_notable, etc.) that ITSI uses to store metrics and notable events. These indexes must exist on the indexer layer becauseindexers are the only Splunk instance type that can actually host and write indexed data. Therefore, SA‑IndexCreation is installed onall indexersin the deployment to ensure that the index definitions are present wherever indexed data is stored. Meanwhile, the main ITSI app (which contains the UI, KPI scheduling, service modeling, analytics, and anomaly detection) is installed onsearch headssince search heads orchestrate searches across the distributed environment and provide ITSI’s interactive features. Universal forwarders and heavy forwarders arenotappropriate targets for SA‑IndexCreation because forwarders do not host writable index locations for ITSI summary and notable event indexes. Thus, the correct installation pattern for SA‑IndexCreation in a distributed environment is on both theindexers and search heads, enabling proper index definition and search functionality across the deployment.

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.

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.

Create a glass table to visualize and monitor the interrelationships and dependencies across your IT and business services.

The service swapping settings are saved and apply the next time you open the glass table.

You can add metrics like KPIs, ad hoc searches, and service health scores that update in real time against a background that you design. Glass tables show real-time data generated by KPIs and services.

In the context of troubleshooting KPI search performance in Splunk IT Service Intelligence (ITSI), the search names in the job activity that identify base searches typically follow the pattern "Indicator - Shared - xxxx - ITSI Search." These base searches are fundamental components of the KPI calculation process, aggregating and preparing data for further analysis by KPIs. Identifying these base searches in the job activity is crucial for diagnosing performance issues, as these searches can be resource-intensive and impact overall system performance. Understanding the naming convention helps administrators and analysts quickly pinpoint the base searches related to specific KPIs, facilitating more effective troubleshooting and optimization of search performance within the ITSI environment.

In the context of Splunk IT Service Intelligence (ITSI), a Business Service often has Key Performance Indicators (KPIs) but might not have directly associated entities. Business Services represent high-level aggregations of organizational functions or processes and are typically measured by KPIs that reflect the performance of underlying technical services or components rather than direct infrastructure entities. For example, a Business Service might monitor overall transaction completion times or customer satisfaction scores, which are abstracted from the specific technical entities that underlie these metrics. This abstraction allows Business Services to provide a business-centric view of IT health and performance, focusing on outcomes rather than specific technical components.

You might need to increase the hardware specifications of your own Enterprise Security deployment above the minimum hardware requirements depending on your environment.

Install Splunk Enterprise Security on a dedicated search head or search head cluster.

The Splunk platform uses indexers to scale horizontally. The number of indexers required in an Enterprise Security deployment varies based on the data volume, data type, retention requirements, search type, and search concurrency.

Throttling applies to any correlation search alert type, including notable events and actions (RSS feed, email, run script, and ticketing).

When an anomaly is detected in Splunk IT Service Intelligence (ITSI), it typically generates a notable event that can be reviewed and managed in the Episode Review dashboard. The Episode Review is part of ITSI's Event Analytics framework and serves as a centralized location for reviewing, annotating, and managing notable events, including those generated by anomaly detection. This process enables IT operators and analysts to efficiently identify, prioritize, and respond to potential issues highlighted by the anomaly alerts. The integration of anomaly alerts into the Episode Review dashboard streamlines the workflow for managing and investigating these alerts within the broader context of IT service management and operational intelligence.

Provide a value to filter the service to a specific set of entities. These entity rule values are meant to be custom for each service.

C. New KPIs. This is true because when you add new KPIs to a service template, they will be automatically added to all the services that are linked to that template. This helps you keep your services consistent and up-to-date with the latest KPI definitions.

The other options will not be added to linked services by default because:

A. Thresholds. This is not true because when you change thresholds in a service template, they will not affect the existing thresholds in the linked services. You need to manually apply the threshold changes to each linked service if you want them to inherit the new thresholds from the template.

B. Entity rules. This is not true because when you change entity rules in a service template, they will not affect the existing entity rules in the linked services. You need to manually apply the entity rule changes to each linked service if you want them to inherit the new entity rules from the template.

D. Health score. This is not true because when you change health score settings in a service template, they will not affect the existing health score settings in the linked services. You need to manually apply the health score changes to each linked service if you want them to inherit the new health score settings from the template.

In Splunk IT Service Intelligence (ITSI), notable events are created and managed within the context of its Event Analytics framework. These notable events are stored in theitsi_tracked_alertsindex. This index is specifically designed to hold the active notable events that are generated by ITSI's correlation searches, which are based on the conditions defined for various services and their KPIs. Notable events are essentially alerts or issues that need to be investigated and resolved. Theitsi_tracked_alertsindex enables efficient storage, querying, and management of these events, facilitating the ITSI's event management and review process. The other options, such asitsi_notable_archiveanditsi_notable_audit, serve different purposes, such as archiving resolved notable events and auditing changes to notable event configurations, respectively. Therefore, the correct answer for where active notable events are stored is theitsi_tracked_alertsindex.

Install SA-ITSI-Licensechecker and SA-UserAccess on any license master in a distributed or search head cluster environment. If a search head in your environment is also a license master, the license master components are installed when you install ITSI on the search heads.

Notable events in Splunk IT Service Intelligence (ITSI) are primarily generated through scheduled correlation searches. These searches are designed to monitor data for specific conditions or patterns defined by the ITSI administrator, and when these conditions are met, a notable event is created. These correlation searches are often linked to specific services or groups of services, allowing for targeted monitoring and alerting based on the operational needs of those services. This mechanism enables ITSI to provide timely and relevant alerts that can be further investigated and managed through the Episode Review dashboard, facilitating efficient incident response and management within the IT environment.