Splunk SPLK-3002 Dumps

• 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.

References: Create and manage service templates in ITSI, [Apply service template changes to linked services in ITSI]

In Splunk IT Service Intelligence (ITSI), notable event groups are used to logically group related notable events, which enhances the manageability and analysis of events:

A.Notable event groups combine independent notable events:This characteristic allows for the aggregation of related events into a single group, making it easier for users to manage and investigate related issues. By grouping events, users can focus on the broader context of an issue rather than getting lost in the details of individual events.

While notable event groups play a critical role in organizing and managing events in ITSI, they do not inherently allow users to adjust threshold settings, which is typically handled at the KPI or service level. Additionally, while notable event groups are utilized within the ITSI framework, the statement that they are created in the 'itsi_tracked_alerts' index might not fully capture the complexity of how event groups are managed and stored within the ITSI architecture.

Creating a custom module in Splunk IT Service Intelligence (ITSI) is particularly beneficial for the purpose of migrating KPI base searches and related visualizations to other ITSI installations. Custom modules can encapsulate a set of configurations, searches, and visualizations that are tailored to specific monitoring needs or environments. By packaging these elements into a module, it becomes easier to transfer, deploy, and maintain consistency across different ITSI instances. This modularity supports the reuse of developed components, simplifying the process of scaling and replicating monitoring setups in diverse operational contexts. The ability to migrate these components seamlessly enhances operational efficiency and ensures that best practices and custom configurations can be shared across an organization's ITSI deployments.

Before a module can be created in Splunk IT Service Intelligence (ITSI), it is essential to have one or more datamodels established. Datamodels in Splunk provide a structured format for organizing and interpreting data, which is crucial for modules within ITSI. Modules often rely on datamodels to extract, transform, and present data in a meaningful way, especially when dealing with complex datasets across various sources. Datamodels serve as the foundation for the module's ability to categorize and analyze data efficiently, enabling the creation of KPIs, services, and visualizations that are aligned with the specific needs of the module. Having these datamodels in place ensures that the module can function correctly and provide valuable insights into the monitored IT environments.

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.

By default, impacting service health scores have an importance value of 11.

Among the anomaly detection algorithms included within Splunk IT Service Intelligence (ITSI), "Entity Cohesion" is a notable option. The Entity Cohesion algorithm is designed to detect anomalies by comparing the behavior of one entity against the collective behavior of a group of similar entities. This approach is particularly useful in scenarios where entities are expected to exhibit similar patterns of behavior under normal conditions. Anomalies are identified when an entity's metrics deviate significantly from the group norm, suggesting a potential issue with thatspecific entity. This method leverages the concept of cohesion among similar entities to enhance the accuracy and relevance of anomaly detection within ITSI environments.

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

In Splunk IT Service Intelligence (ITSI), creating teams for each department and assigning services to those teams is an effective way to segregate data and ensure that information remains private between different groups within an organization. Teams in ITSI provide a mechanism for role-based access control, allowing administrators to define which users or groups have access to specific services, KPIs, and dashboards. By setting up teams corresponding to each department and then assigning services to these teams, ITSI canaccommodate multi-departmental use within the same instance while maintaining strict access controls. This ensures that each department can only view and interact with the data and services relevant to their operations, preserving confidentiality and data integrity across the organization.

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.

An ITSI Glass Table provides a customizable, high-level view that can display a system's topology overlaid with real-time Key Performance Indicator (KPI) metrics and service health scores. This visualization tool allows users to create a visual representation of their IT infrastructure, applications, and services, integrating live data to monitor the health and performance of each component in context. The ability to overlay KPI metrics on the system topology enables IT and business stakeholders to quickly understand the operational status and health of various elements within their environment, facilitating more informed decision-making and rapid response to issues.

To modify default deep dives in Splunk IT Service Intelligence (ITSI), the least permissive role typically required is theitoa_adminrole. This role is specifically designed within ITSI to provide administrative capabilities, including the ability to configure and customize various aspects of ITSI, such as services, KPIs, and deep dives. Theitoa_adminrole has the necessary permissions to edit and manage default deep dives, enabling users with this role to tailor the deep dives to meet specific operational requirements and preferences. Other roles likeitoa_analyst,admin, orpowermight not have sufficient privileges to modify default deep dives, as these roles are generally more restricted in terms of their ability to make broad changes within ITSI.

C is the correct answer because teams are a feature of ITSI that allow you to restrict access to service content in UI views based on user roles. To create separate teams for finance and sales analysts, you need to create custom roles that inherit from the itoa_analyst role, which has read-only access to ITSI content. For example, you can create itoa_finance_analyst and itoa_sales_analyst roles that inherit from itoa_analyst. Then, you need to create custom teams that include these roles and assign them to the relevant services. For example, you can create a finance team that includes the itoa_finance_analyst role and assign it to the finance services. Similarly, you can create a sales team that includes the itoa_sales_analyst role and assign it to the sales services. This way, analysts in each department can only see their own services and not each other’s. References: Create teams in ITSI, Assign teams to services in ITSI

One of the recommended best practices for Splunk IT Service Intelligence (ITSI) installation is to avoid installing ITSI on search heads that already have Splunk Enterprise Security (ES) installed. This recommendation stems from potential resource conflicts and performance issues that can arise when both resource-intensive applications are deployed on the same instance. Both ITSI and ES are complex applications that require significant system resources to function effectively, and running them concurrently on the same search head can lead to degraded performance, conflicts in resource allocation, and potential stability issues. It's generally advised to segregate these applications onto separate Splunk instances to ensure optimal performance and stability for both platforms.

In Splunk IT Service Intelligence (ITSI), when using multiple event management policies, it is important to understand that policy processing is applied in a defined order. This order is crucial because it determines how events are processed and aggregated, and which rules are applied to events first. The order of policies can be customized, allowing administrators to prioritize certain policies over others based on the specific needs and operational logic of their IT environment. This feature provides flexibility in event management, enabling more precise control over event processing and ensuring that the most critical events are handled according to the desiredprecedence. This structured approach to policy processing helps in maintaining the efficiency and effectiveness of event management within ITSI.

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.

To automatically create ServiceNow incidents when a Multi-KPI alert triggers in Splunk IT Service Intelligence (ITSI), the following approaches can be used:

C.By creating a notable event aggregation policy with a ServiceNow (SNOW) incident action:ITSI allows the creation of notable event aggregation policies that can specify actions to be taken when certain conditions are met. One of these actions can be the creation of an incident in ServiceNow, directly linking the alerting mechanism in ITSI with incident management in ServiceNow.

D.By editing the associated correlation search and specifying an alert action:Correlation searches in ITSI are used to identify patterns or conditions that signify notable events. These searches can be configured to include alert actions, such as creating a ServiceNow incident, whenever the search conditions are met. This direct integration ensures that incidents are automatically generated in ServiceNow, based on the specific criteria defined in the correlation search.

Options A and B are not standard practices for integrating ITSI with ServiceNow for automatic incident creation. The configuration typically involves setting up actionable alert mechanisms within ITSI that are specifically designed to integrate with external systems like ServiceNow.

A is the correct answer because anomaly detection can be enabled on a KPI level in ITSI. Anomaly detection allows you to identify trends and outliers in KPI search results that might indicate an issue with your system. You can enable anomaly detection for a KPI by selecting one of the two anomaly detection algorithms in the KPI configuration panel. References: Apply anomaly detection to a KPI in ITSI

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.

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.

ITSI provides a kvstore_to_json.py script that lets you backup/restore ITSI configuration data, perform bulk service KPI operations, apply time zone offsets for ITSI objects, and regenerate KPI search schedules.

When you run a backup job, ITSI saves your data to a set of JSON files compressed into a single ZIP file.