Splunk SPLK-3002 Exam Dumps & Practice Test Questions

Question 1:

What is the default duration for which metadata from a resolved notable event is stored in the KV Store in Splunk ITSI?

A. Three months
B. Six months
C. Nine months
D. One year

Correct Answer: D

Explanation:

In Splunk IT Service Intelligence (ITSI), notable events are key components that represent alerts or issues requiring attention. These events carry metadata—such as severity, timestamps, resolution status, and user comments—which provide valuable context for investigation, audit, and reporting purposes.

When a notable event is marked as resolved or closed, it does not disappear from the system immediately. Instead, its associated metadata is retained in the KV Store—a high-performance, non-relational database used by Splunk to store structured key-value pair data. This design enables rapid lookup, querying, and integration with dashboards and analytics within ITSI.

By default, Splunk ITSI retains the metadata of resolved notable events for a period of one year (365 days) in the KV Store. This retention period ensures that organizations can conduct historical analysis, identify recurring issues, generate compliance reports, and perform effective root cause analysis over a longer timeline.

Retention of this metadata is vital for:

• Post-incident reviews: Teams can evaluate past alerts to identify trends or misconfigurations.

• Regulatory compliance: Many industries require event tracking for a defined period.

• Audit readiness: Security and operational audits may demand historical data for validation.

Now, let’s evaluate the incorrect options:

• A (Three months) and B (Six months): While shorter durations may be applicable in environments with strict storage constraints, they are insufficient for most enterprise use cases, especially those with long audit or incident review cycles.

• C (Nine months): Though closer to the actual value, it is not the correct default. It is only valid if explicitly customized by an administrator.

Splunk allows modification of this default through administrative settings, but unless configured otherwise, the system adheres to the one-year retention policy. Organizations with specific storage or compliance needs may reduce or extend this period, but they should balance performance implications with historical data needs.

To conclude, understanding the default retention behavior helps in both planning storage capacity and ensuring that operational and compliance requirements are effectively met within Splunk ITSI deployments.

Question 2:

When rolling out ITSI in phases, which strategy is recommended for selecting which services to implement first?

A. Select only those KPIs that are common across multiple services
B. Focus first on the organization’s most critical and business-impacting services
C. Begin with low-level infrastructure services
D. Create a large initial list of services for full visibility

Correct Answer: B

Explanation:

During an incremental or phased rollout of Splunk ITSI, selecting the right services to prioritize can significantly influence the success of the overall implementation. The recommended best practice is to start with the most essential, high-impact business services, as these are closely tied to core business functions and outcomes.

Focusing on mission-critical services delivers early wins by improving visibility into areas that directly affect end-user experience, revenue generation, or customer satisfaction. This approach also aligns the ITSI implementation with business objectives, which is a core tenet of business service monitoring and AIOps.

Deploying ITSI in this way provides multiple benefits:

• Stakeholder engagement: Demonstrating value quickly helps gain buy-in from business and technical leadership.

• Faster ROI: Monitoring top-tier services ensures that any improvements have measurable business value.

• Strategic insight: High-priority services often reveal patterns and performance issues that impact downstream systems.

Let’s review the other options:

• A (Only include KPIs shared across multiple services): While reusing KPIs promotes consistency and reduces configuration effort, it shouldn’t be the main selection criterion. Critical services may rely on unique KPIs that are essential for accurate monitoring.

• C (Start with foundational infrastructure services): Infrastructure components are important, but starting with them may not yield immediate visibility into user-facing impacts. This could delay the realization of business benefits and reduce stakeholder enthusiasm.

• D (Define many services upfront): Attempting broad coverage at the beginning often results in misconfigurations, inconsistent naming conventions, and overwhelm for teams managing the rollout. It also increases complexity without delivering focused insights.

By initially targeting high-value business services, teams create a strong foundation for expanding ITSI gradually and effectively. Once these services are in place and delivering value, additional services—such as infrastructure or supporting systems—can be added in future iterations with clearer context and objectives.

In summary, prioritizing impactful business services during the initial phase ensures that Splunk ITSI provides tangible, high-value results early in the deployment lifecycle.

Question 3:

In the topology view of a custom deep dive in Splunk ITSI, which color is used to indicate that a service or KPI is currently in maintenance mode?

A. Gray
B. Purple
C. Gear Icon
D. Blue

Correct Answer: A

Explanation:

In Splunk IT Service Intelligence (ITSI), the topology view within a custom deep dive provides a graphical map showing how services and KPIs relate to one another in real time. These nodes are color-coded to reflect the health state or operational context of each entity. One special operational context that ITSI accounts for is maintenance mode, which is used when planned changes, system updates, or diagnostic activities are taking place. When a service or KPI is in this state, it is intentionally excluded from triggering alerts or influencing overall service health scores.

To make this state easily recognizable in the topology view, ITSI uses the color gray. This visual indicator is neutral, helping distinguish maintenance mode from critical states like warning or failure, which are represented by more urgent colors such as red or orange. The gray coloration effectively communicates that the component is temporarily not contributing to the service’s real-time analytics or alerting logic, thereby preventing false alarms during routine maintenance or planned downtime.

This color-coding plays an essential role in assisting operations teams with rapid visual assessments. If a service appears gray, the team can immediately infer it is under maintenance and doesn’t need urgent intervention, even if associated data appears abnormal.

Let’s examine why the other choices are incorrect:

• Purple is not used for maintenance mode in ITSI. While ITSI uses a wide range of colors to reflect severity levels and other statuses, purple is not designated for maintenance.

• Gear Icon typically denotes settings or configuration options in user interfaces, but it is not used as a node color or symbol in the topology view.

• Blue is sometimes used in other UI contexts but not to reflect maintenance status in this visual layer.

Understanding these visual cues is crucial during event investigations, service monitoring, and root cause analysis, allowing teams to focus on actionable alerts rather than components in benign, planned states.

Question 4:

In an ITSI deep dive dashboard, which swim lane type can be added without requiring the user to write any custom SPL (Search Processing Language)?

A. Event lane
B. Automatic lane
C. Metric lane
D. KPI lane

Correct Answer: D

Explanation:

In Splunk ITSI’s deep dive dashboards, swim lanes are powerful tools used to visually analyze service behaviors and KPIs over a specific time frame. These horizontal bands display time-series data, enabling operational teams to correlate patterns, detect anomalies, and investigate the root causes of issues. Each swim lane represents a different type of data, and while some require advanced configurations or custom queries, others are plug-and-play.

The KPI lane stands out as the easiest to use and configure, as it does not require any new SPL (Search Processing Language) to be written. This is because KPIs (Key Performance Indicators) are already pre-configured components within ITSI services. They come with their own data sources, threshold definitions, and SPL behind the scenes. When you add a KPI lane to a deep dive, you simply select the KPI from a dropdown list, and the system automatically populates the lane with its associated data.

This eliminates the need for users to manually craft SPL queries, significantly lowering the technical barrier for creating insightful dashboards. It empowers users — especially those without advanced SPL knowledge — to explore service health visually and effectively.

Let’s compare this with the other swim lane types:

• Event lane: While it can display alert events or notable incidents, filtering or customizing what events show often involves writing SPL to define which events are relevant.

• Automatic lane: Although it can sometimes auto-populate based on system inputs, it may still require tuning or custom SPL to get meaningful results from complex or multi-source data.

• Metric lane: This lane is designed to show raw metric data (like CPU usage, memory stats, etc.). To use it effectively, users often need to write SPL — typically using mstats commands — to specify what metrics to fetch and how they should be displayed.

In summary, the KPI lane provides a ready-made, SPL-free experience. It exemplifies ITSI’s goal of democratizing observability by letting operations teams focus on insights rather than query writing. This helps speed up dashboard creation and facilitates proactive service monitoring even by non-technical users.

Question 5:

Which of the following statements accurately describe how anomaly detection operates in Splunk ITSI?

A. Anomaly detection can function without historical baseline data, allowing machine learning to operate on live KPI streams.
B. A minimum of 24 hours of KPI history and at least 4 entities are required for effective anomaly detection.
C. Notable events can be triggered automatically when KPI behavior deviates from learned patterns.
D. ITSI offers three different anomaly detection modes: ad hoc, trending, and cohesive.

Correct Answers: B, C, D

Explanation:

Anomaly Detection (AD) in Splunk IT Service Intelligence (ITSI) is a powerful tool that leverages machine learning algorithms to detect abnormal KPI behavior based on established historical baselines. This approach allows Splunk to dynamically monitor KPI trends without requiring static thresholds, which can often lead to false positives or missed insights in dynamic environments.

Option A is incorrect because anomaly detection requires historical data to define what constitutes normal behavior. The machine learning engine in ITSI learns patterns over time from past KPI data. If there's no baseline history, the algorithm cannot accurately identify deviations or anomalies. Without this context, the system has no frame of reference for what is unusual, making it impossible to detect anomalies reliably.

Option B is correct. For entity-based KPIs, Splunk recommends having at least 24 hours of historical data and a minimum of four entities. This volume of data ensures the model can distinguish between legitimate fluctuations and anomalous behavior. Fewer entities reduce the accuracy of the “cohesive” detection mode, which compares behaviors across different entities.

Option C is also correct. One of the most valuable aspects of anomaly detection in ITSI is its ability to generate notable events automatically when KPI data significantly deviates from learned patterns. This automation reduces the need for manual monitoring and allows operations teams to respond more quickly to real incidents while avoiding unnecessary alerts.

Option D is correct and highlights the flexibility of ITSI. The platform supports three anomaly detection modes:

• Ad Hoc: Best used for one-time investigations or quick checks on specific KPIs.

• Trending: Monitors long-term trends and alerts on deviations from established patterns.

• Cohesive: Compares multiple entities against each other to identify outliers or irregular behavior across a group.

Each mode serves a different use case, enabling ITSI to adapt to both broad service-level monitoring and more granular investigations. Collectively, these capabilities make anomaly detection a highly adaptive and powerful feature in maintaining IT health and performance visibility.

Question 6:

Which of the following are considered best practices when configuring maintenance windows for services within Splunk ITSI?

A. Turn off glass tables that include KPIs scheduled for maintenance.
B. Define a policy for handling notable events triggered during maintenance periods.
C. Add a 15-minute buffer before and after each maintenance window to prevent false alerts.
D. Manually adjust the service color in the Service Analyzer to reflect maintenance status.

Correct Answers: B, C

Explanation:

In Splunk ITSI, maintenance windows are essential for managing periods when regular KPI performance may be intentionally disrupted due to upgrades, patches, or configuration changes. These windows help ensure that alerting systems don't generate unnecessary noise, keeping operational teams focused on genuine issues rather than predictable changes.

Option A is incorrect. Disabling glass tables during maintenance is neither required nor recommended. Glass tables provide valuable visual insights, and their utility remains during maintenance periods. Rather than removing visibility, ITSI uses maintenance logic to suppress alerts and notable events while still displaying KPI data. This means users can monitor progress and system behavior in real-time without receiving false-positive alerts.

Option B is correct. A recommended best practice is to proactively define how ITSI handles notable events during maintenance windows. For example, organizations might suppress event creation entirely or route these events to a separate dashboard or queue for review. This avoids alert fatigue while still preserving visibility for post-maintenance audits or analysis. A lack of planning in this area can lead to confusion and unnecessary incident response efforts.

Option C is also correct. Including a 15-minute buffer before and after the scheduled maintenance time helps account for variations in task start and completion times. Without these buffers, alerts might fire immediately before or after the maintenance period due to temporary data anomalies that result from system restarts or transitional instability. Buffers help ensure the maintenance logic functions as intended even if timing isn’t precise.

Option D is incorrect because manual color changes in the Service Analyzer are not needed. Splunk ITSI automatically applies a gray color to services or KPIs that are currently in a maintenance state. This is part of the built-in behavior and serves as a clear, visual indicator to all users that these components are not actively monitored for anomalies or alerts at that time.

By incorporating these practices, Splunk ITSI users can create a more predictable and controlled monitoring environment, even during periods of intentional disruption. This ensures that teams remain focused, alerts are relevant, and system visibility is maintained without unnecessary operational noise.

Question 7:

When a user selects an episode in the ITSI Episode Review dashboard and clicks on the “Acknowledge” button, what exactly occurs as a result of this action?

A. The current user is set as the episode’s owner only
B. The episode status changes to “Acknowledged” only
C. The status becomes “In Progress” and the current user is assigned ownership
D. The episode status changes to “Acknowledged” and the current user becomes the owner

Correct Answer: D

Explanation:

In Splunk IT Service Intelligence (ITSI), the Episode Review dashboard is a central interface where users can monitor, assess, and respond to aggregated alerts, also known as episodes. Each episode is a collection of related notable events that have been correlated by the system to represent a broader issue or trend.

When a new episode appears, it is typically marked with the status “New”, indicating that it has not yet been addressed by any team member. When a user interacts with an episode by clicking the “Acknowledge” button, two key updates are made:

1. Status Change to “Acknowledged”:
   The episode's status immediately transitions from “New” to “Acknowledged.” This change signals to others reviewing the dashboard that someone has seen the episode and has taken initial responsibility for it, even if detailed investigation hasn't yet begun. This helps prevent duplication of effort and ensures better team coordination.

2. Ownership Assignment:
   In addition to updating the status, ITSI also automatically assigns ownership of the episode to the user who clicked “Acknowledge.” This serves as a tracking mechanism and ensures accountability, allowing teams to easily identify who is currently responsible for resolving the issue or moving it to the next stage of the lifecycle.

Let’s evaluate the incorrect options:

• Option A mentions ownership assignment but fails to include the important status update.

• Option B correctly identifies the status change, but omits the assignment of ownership.

• Option C inaccurately refers to a status of “In Progress”, which is only used when a user explicitly changes the status to reflect deeper engagement or remediation.

Therefore, Option D is the only choice that fully and accurately describes what happens when the “Acknowledge” button is used. It captures both the status update and ownership assignment, which are essential elements of ITSI’s incident triage workflow.

Question 8:

Which functionality in a glass table dashboard allows users to change the displayed service in a widget dynamically while keeping the visualization element the same?

A. Service templates
B. Service dependencies
C. Ad-hoc search
D. Service swapping

Correct Answer: D

Explanation:

Glass tables in Splunk ITSI are designed for creating rich, interactive dashboards that display KPIs, service health scores, and other operational data in real-time. These dashboards are often used by network operations centers (NOCs), service managers, and executive teams to gain immediate insights into system performance.

One of the most powerful and flexible features of glass tables is service swapping. This feature allows users to dynamically switch the service that a widget is referencing, all within the same visualization. For example, if you have a gauge widget that shows the CPU usage of “Database Server A,” you can easily swap it to show the CPU usage of “Database Server B” — without needing to build a new widget.

This functionality is particularly useful for:

• Reusing dashboard elements across multiple services

• Maintaining clean and organized dashboards

• Allowing operators to quickly focus on different services without UI clutter

Let’s examine the incorrect answers:

• Option A: Service templates
  These are used for standardizing the creation of services with similar structures (like common KPIs and thresholds). While useful for configuration, they do not offer dynamic switching within dashboards.

• Option B: Service dependencies
  This refers to mapping how services rely on one another (e.g., frontend app relies on backend database). This is helpful for topology and impact analysis, but it has no relation to widget content switching in glass tables.

• Option C: Ad-hoc search
  Ad-hoc searches are custom SPL queries created on the fly and added to widgets manually. However, they do not allow dynamic interaction such as swapping service data.

Therefore, Option D: Service swapping is the correct and most suitable feature for enabling real-time service context switching within a single widget on a glass table. It enhances dashboard reusability, reduces duplication, and makes monitoring more efficient and user-friendly.

Question 9:

Which of the following statements best describes a valid functionality of base searches within Splunk ITSI?

A. Base searches define search logic, entity assignments, and threshold settings for all linked KPIs.
B. Base searches can be set up to limit processing to entities that belong specifically to the associated service.
C. Base searches are more efficient when fewer KPIs rely on them, especially during anomaly detection.
D. Base searches always execute on their schedule, even if no KPIs are currently using them.

Correct Answer: B

Explanation:

In Splunk IT Service Intelligence (ITSI), base searches are reusable search configurations designed to optimize performance and streamline search logic across multiple KPIs and services. Instead of having each KPI run its own search individually, a base search runs once and shares its results with multiple KPIs, greatly enhancing system efficiency.

Let’s assess the provided options:

Option A is incorrect. While a base search does contain the foundational search logic, it does not dictate entity filtering or threshold values directly. Those are configured individually at the KPI level. Each KPI using the base search applies its own entity rules and thresholds, allowing for flexible customization even when KPIs share the same base logic.

Option B is correct. ITSI offers the capability to filter base search results so that only entities associated with the relevant service are included. This feature is especially beneficial in large environments with overlapping infrastructure or shared components. By limiting the scope of entity evaluation to the service's entities, the system achieves higher accuracy and improved performance, particularly when services are tightly scoped.

Option C is a common misconception and therefore incorrect. Contrary to the statement, it is actually more efficient to have more KPIs share the same base search. The reason is simple: the base search runs once per schedule and its results are distributed across all relevant KPIs. Fewer base searches mean fewer executed searches, which results in lower system load and better resource utilization — especially valuable during real-time analysis like anomaly detection.

Option D is also incorrect. A base search does not execute on its own without demand. It only runs if at least one KPI scheduled to use it is active during the same time interval. If no KPI needs it at that time, the base search remains dormant, helping to conserve system resources.

Conclusion:
The correct understanding of base searches is critical for building scalable, efficient ITSI implementations. Option B correctly reflects the functional ability to limit entity scope within a base search, improving both the relevance and performance of KPI evaluations.

Question 10:

Which of the following are features available in the Splunk ITSI Glass Table visual editor?

A. Designing new glass tables from the ground up.
B. Creating correlation searches that generate notable events.
C. Configuring visual elements to allow switching between services.
D. Inserting visual KPI metrics like gauges and trend charts into the dashboard.

Correct Answers: A, C, D

Explanation:

The Glass Table editor in Splunk ITSI is a powerful, interactive interface that allows users to build custom dashboards that visually represent real-time KPI performance and service health. It is specifically tailored for operational visibility, enabling users to present complex data in an intuitive, graphical format.

Let’s evaluate each choice:

Option A is correct. The Glass Table editor is specifically designed to let users build dashboards — or "glass tables" — from scratch. Users can start with a blank canvas and drag elements such as text labels, icons, images, and data-driven widgets into the layout. This makes it ideal for creating bespoke visualizations of your IT environment.

Option B is incorrect. While correlation searches are a major component of ITSI, they are not created or managed within the Glass Table editor. Instead, correlation searches are configured through ITSI's Content Management or Correlation Search settings. These searches monitor patterns and generate notable events, but their development takes place outside the visual design interface.

Option C is correct. One of the advanced capabilities of the Glass Table editor is service swapping. This allows users to interactively switch between services or entities displayed in a widget, making the dashboard more dynamic. For instance, a single KPI widget could display metrics for different servers or applications depending on the user’s selection — improving usability and conserving space.

Option D is also correct. The editor allows the insertion of various KPI metric visualizations, such as gauges, line graphs, and metric lanes. These widgets are linked to ITSI KPIs and can represent real-time or historical data. They also support conditional formatting like threshold-based color changes, tooltips, and contextual data, giving operators quick insight into health status.

Summary:
The Glass Table editor excels in visual presentation and dashboard customization, but does not support correlation search creation. Therefore, A, C, and D are the correct answers, while B lies outside the editor’s scope. Understanding this distinction helps users design better visual workflows in ITSI.