SPLK-3002 Exam Dumps - Splunk IT Service Intelligence Certified Admin Exam

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.

It's a deduplicated group of notable events occurring as part of a larger sequence, or an incident or period considered in isolation.

In Splunk IT Service Intelligence (ITSI), glass tables are fully customizable dashboards that provide a visual representation of an organization's IT environment, along with the health and status of services and KPIs. Unlike some pre-configured views or dashboards that might come with default setups in various platforms, ITSI does not provide default glass tables out of the box. Instead, users are encouraged to create their own glass tables tailored to their specific monitoring needs and operational views. This approach ensures that each organization can design glass tables that best represent their unique infrastructure, applications, and service landscapes, providing a more personalized and relevant operational overview.

Search results are processed, created, and written to the itsi_summary index via an alert action. 

In Splunk IT Service Intelligence (ITSI), a KPI widget on a glass table can be configured to drill down into a variety of destinations based on the needs of the user and the design of the glass table. This flexibility allows users to dive deeper into the data or analysis represented by the KPI widget, providing context and additional insights. The destinations for drill-downs from a KPI widget can include:

A. Another glass table, offering a different perspective or more detailed view related to the KPI. B. A Splunk dashboard that provides broader analysis or incorporates data from multiple sources. C. A custom deep dive for in-depth, time-series analysis of the KPI and related metrics.

This versatility makes KPI widgets powerful tools for navigating through the wealth of operational data and insights available in ITSI, facilitating effective monitoring and decision-making.

In the context of Smart Mode configuration within Splunk IT Service Intelligence (ITSI), the two settings that control how fields affect grouping are "Text similarity" and "Category similarity." Smart Mode is a feature used in event grouping that leverages machine learning to automatically group related events. "Text similarity" refers to how closely the textual content of event fields must match for those events to be grouped together, taking into account commonalities in strings or narratives within the event data. "Category similarity," on the other hand, relates to the similarity in the categorical attributes of events, such as event types or source types, which helps in clustering events that are similar in nature or origin. Both of these settings are crucial in determining how events are grouped in ITSI, influencing the granularity and relevance of the event groupings based on textual and categorical similarities.

Deep dives in Splunk IT Service Intelligence (ITSI) allow for an in-depth analysis of services and their KPIs over time, providing a detailed view of the operational health and performance trends. One of the powerful actions that can be performed with a deep dive is the creation of a Multi-KPI alert from the deep dive's current state. This functionality enables users to define alerts based on the complex conditions observed during the deep dive analysis, allowing for the early detection of similar situations in the future. By configuring a Multi-KPI alert directly from a deep dive, ITSI users can leverage their insights and observations to proactively monitor for patterns or conditions that may indicate potential service degradation or failure, enhancing the overall responsiveness and effectiveness of the IT monitoring strategy.