Splunk SPLK-3002 Practice Test Questions, Exam Dumps

Practice Exams:

View All

SPLK-3002 Splunk Practice Test Questions and Exam Dumps

Question 1:

How long is the metadata of a resolved notable event retained in the KV Store by default in Splunk ITSI?

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

Correct Answer: D. One year

Explanation:

In Splunk ITSI (IT Service Intelligence), when a notable event is generated, it includes both the event and associated metadata, such as status, severity, comments, and correlation identifiers. Once a notable event is resolved or closed, its data is not immediately deleted. Instead, it is preserved in the KV Store (Key-Value Store), which is a non-relational database used by Splunk to manage structured data efficiently.

By default, ITSI retains metadata for closed notable events in the KV Store for one year (365 days). This retention allows IT administrators and analysts to audit historical incidents, conduct post-incident reviews, and maintain compliance with organizational policies.

Why not the other options?

Three months (A) and six months (B) would not provide sufficient historical context for organizations with long incident review cycles.
Nine months (C) is also incorrect as it doesn’t match the default retention policy configured in ITSI.
One year (D) is accurate and aligns with ITSI’s default behavior unless customized by an admin.

Understanding this retention period is important for maintaining system performance and storage planning, particularly in environments with a high volume of alerts.

Question 2:

What is considered a best practice when deciding which services to prioritize first in an incremental deployment of ITSI?

A. Choose only KPIs that are relevant to more than one service.
B. Start by identifying the business’s most essential and high-impact services.
C. Focus primarily on foundational or lower-level infrastructure services.
D. Begin by defining a large number of services to ensure broad coverage.

Correct Answer: B. Start by identifying the business’s most essential and high-impact services.

Explanation:

When implementing ITSI using an iterative (or phased) approach, it's important to make strategic choices about where to begin. The best practice is to start with the most critical business services, as these are the areas where the impact of improved visibility and monitoring will be most beneficial.

By aligning the first services with business priorities, ITSI delivers immediate value, making it easier to gain support from stakeholders. It also helps teams better understand how service performance affects business outcomes, a key goal of AIOps and service monitoring.

Let’s look at the other options:

Option A: "Only include KPIs used in multiple services" is not ideal. While KPI reusability can be efficient, it should not be the sole criterion for inclusion. Some critical services may have unique KPIs that are vital despite not being shared.
Option C: "Focus on low-level services" may lead to wasted effort on components that do not provide clear visibility into overall business impact. While infrastructure is important, starting here doesn’t usually provide quick wins.
Option D: "Define a large number of key services early" is a common mistake. Overloading the initial deployment can lead to confusion, poor implementation, and diluted focus. Starting small with impactful services enables smoother scaling.

In summary, starting with critical, high-value business services ensures that the initial phase of ITSI deployment yields meaningful results, which can then be used to inform and guide subsequent phases. This strategy helps teams build confidence, demonstrate value, and continuously optimize the monitoring strategy.

Question 3:

In a custom deep dive within ITSI, what visual indicator (color or icon) is used in the topology view to represent services or KPIs that are currently in maintenance mode?

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

Correct Answer: A. Gray

Explanation:

In Splunk IT Service Intelligence (ITSI), the topology view in a custom deep dive helps users visualize the relationships between services and KPIs over time. This view provides a dynamic, color-coded diagram where each node represents a service or KPI, and the colors indicate the current health state.

When a service or KPI is placed in maintenance mode, it means that the data related to it is temporarily excluded from alerting and health scoring to prevent false positives (such as during planned upgrades or downtime). ITSI needs a way to visually signal this special state so that users can quickly understand the current context.

In the topology view, any service or KPI in maintenance mode is represented in gray. This neutral color visually indicates that the component is neither healthy nor unhealthy — it's simply not being evaluated for alerts or service health during its maintenance window.

Why not the other options?

Purple (B) is not used to indicate maintenance mode. ITSI does use colors to represent different severities (like red, orange, yellow, green), but purple isn't standard.
Gear Icon (C) is used in some UI areas to represent configuration settings, but not as a node color in the topology view.
Blue (D) is also not used for maintenance mode — this may represent informational states elsewhere but not in this context.

Understanding visual cues like this is critical for users conducting root cause analysis or tracking service status in real time.

Question 4:

Which type of swim lane in an ITSI deep dive dashboard does not require any custom SPL (Search Processing Language) to be written?

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

Correct Answer: D. KPI lane

Explanation:

In Splunk ITSI deep dives, swim lanes are visual timelines that display service and KPI behavior over time. Each swim lane shows data from a different source or perspective, helping users correlate issues across multiple dimensions.

There are different types of swim lanes, and each type has its own data source and configuration method:

KPI lane (Correct Answer): This swim lane displays data from existing KPIs defined in a service. Since the KPI is already configured with its own SPL and threshold logic within ITSI, adding it to a deep dive doesn’t require you to write any new SPL. You simply select the KPI from a list.
Automatic lane: This lane is driven by underlying metric or log data and may sometimes require tuning or additional SPL, especially if you're pulling from multiple sources.
Event lane: Used to show alert or notable events. While it often pulls from pre-existing data, users may write SPL to filter events by specific criteria.
Metric lane: Displays raw metric data (like CPU usage or memory), usually requiring you to write SPL or use mstats commands to gather and display the data.

Why is the KPI lane the best answer?

The KPI lane offers the simplest setup. Since it pulls from KPIs already created and stored in ITSI services, the data is ready for use — no additional queries are needed. This enables faster setup and allows non-technical users or analysts to build powerful visualizations without needing SPL skills.

This approach supports the core philosophy of ITSI: empowering operations teams to monitor service health and respond to issues without requiring deep SPL knowledge for every dashboard.

Question 5:

Which of the following statements correctly describe key characteristics of anomaly detection in Splunk ITSI?
(Select all that apply)

A. Anomaly detection can be applied to KPIs without an established data baseline, allowing machine learning to analyze from scratch.
B. At least 24 hours of historical data and a minimum of 4 entities are required for anomaly detection to function properly.
C. When data deviates from expected patterns, anomaly detection can automatically generate notable events.
D. ITSI supports three modes of anomaly detection: ad hoc, trending, and cohesive.

Correct Answers: B, C, D

Explanation:

Anomaly Detection (AD) in Splunk ITSI is a machine learning-based feature designed to identify unexpected changes in KPI values. It doesn't rely on static thresholds but instead builds dynamic baselines using historical data.

Let’s break down each option:

Option A – Incorrect:
While it may seem intuitive to use AD on KPIs with no history, machine learning models actually require a historical baseline to function effectively. Without sufficient data, the algorithm can’t determine what’s “normal,” and thus cannot flag anomalies reliably. The “magic” of AD depends on pattern recognition from historical trends, not immediate pattern guessing.
Option B – Correct:
This is accurate. For entity-based KPIs, at least 24 hours of historical data is needed. Also, a minimum of 4 entities helps the model distinguish outliers more effectively through comparison. If fewer entities are available, cohesive analysis (which compares behavior across entities) may not function optimally.
Option C – Correct:
Yes. When a KPI’s behavior significantly diverges from learned patterns, ITSI can automatically trigger notable events. This allows teams to respond quickly to unexpected performance drops or spikes without setting explicit thresholds.
Option D – Correct:
Splunk ITSI supports three types of anomaly detection:

Ad hoc: Used for one-time investigations.
Trending: Tracks deviations from long-term patterns.
Cohesive: Compares behavior across multiple entities to find outliers.

These modes provide flexibility depending on the type of analysis required, and allow ITSI to tailor anomaly detection strategies for different monitoring needs.

Question 6:

What is a recommended best practice when setting up maintenance windows for services in ITSI?

A. Temporarily disable glass tables that reference KPIs under active maintenance.
B. Create a strategy for handling notable event generation when a service is in maintenance mode.
C. Include a 15-minute buffer period before and after the planned maintenance time.
D. Manually change the display color of services and entities under maintenance in the Service Analyzer.

Correct Answers: B, C

Explanation:

Maintenance windows in Splunk ITSI are used to suppress alerts and event generation for services and KPIs that are undergoing planned changes or updates. This ensures that false alarms are avoided during periods when irregular data behavior is expected (like during system upgrades or server restarts).

Let’s go through each option:

Option A – Incorrect:
Disabling glass tables is not necessary. Glass tables remain functional and serve as a visual tool for monitoring. Instead of disabling them, it's better to rely on built-in maintenance window logic that suppresses event generation.
Option B – Correct:
A solid best practice is to plan how ITSI handles notable events during maintenance. This could involve suppressing them entirely, flagging them differently, or routing them to a lower-priority queue. Without this, teams may still be alerted unnecessarily, defeating the purpose of maintenance mode.
Option C – Correct:
Including a buffer time, like 15 minutes before and after scheduled maintenance, accounts for tasks starting early or running late. This helps avoid edge cases where alerts might be triggered just before or after the window due to normal transitional behaviors.
Option D – Incorrect:
There is no need to manually change colors in the Service Analyzer. ITSI automatically grays out services and KPIs under maintenance, indicating their suppressed status. Manual color changes are neither efficient nor scalable.

Question 7:

In the ITSI Episode Review dashboard, what happens when a user clicks the “Acknowledge” button for a selected episode?

A. The current user is assigned as the episode's owner.
B. The episode's status changes from "New" to "Acknowledged".
C. The status is changed to "In Progress", and the current user becomes the owner.
D. The status updates to "Acknowledged", and ownership is assigned to the current user.

Correct Answer: D. The status updates to "Acknowledged", and ownership is assigned to the current user.

Explanation:

In Splunk ITSI, the Episode Review interface allows users to investigate, triage, and resolve aggregated alerts (called episodes). When an episode is generated (from correlated notable events), it initially appears with a status of "New", indicating that no one has interacted with it yet.

Clicking the "Acknowledge" button in the Episode Review view serves two main purposes:

Status Change:
The episode’s status is automatically changed from "New" to "Acknowledged". This signals to others that someone has recognized the issue but hasn't begun working on it in detail.
Ownership Assignment:
At the same time, the user who clicked “Acknowledge” is assigned as the owner of that episode. This helps with accountability and makes it clear who is responsible for the next action.

Let’s examine the incorrect options:

Option A is partially correct but incomplete — it doesn’t mention the status change.
Option B correctly notes the status change but misses the ownership assignment.
Option C incorrectly states that the status changes to “In Progress” — this status is only used when a user explicitly changes it, usually when beginning active investigation or remediation.

Thus, Option D is the most accurate and complete answer, reflecting both the status transition and ownership change.

Question 8:

In a glass table visualization, which feature enables users to dynamically switch between services to display their respective KPI values in the same widget?

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

Correct Answer: D. Service swapping

Explanation:

Glass tables in Splunk ITSI are visual dashboards that display key metrics, KPIs, and service health in near real-time. They are used for both operational overviews and executive-level monitoring.

When you want to reuse a widget (like a gauge, chart, or indicator) to display KPI values from different services, rather than building a separate widget for each service, you can use service swapping.

What is Service Swapping?

Service swapping allows you to toggle the service context for a widget at runtime. For example, you can display the CPU usage KPI of “Web Server A,” then switch the same widget to show the CPU usage of “Web Server B.” This is incredibly efficient and helps maintain a clean, reusable dashboard layout.

Why not the other options?

Option A: Service templates
Service templates help with creating multiple services that share a similar structure. They simplify service creation but aren’t used to toggle services in a glass table.
Option B: Service dependencies
This refers to the relationship between services (e.g., databases supporting applications), but it has nothing to do with glass table visualization toggling.
Option C: Ad-hoc search
Ad-hoc searches allow users to run custom SPL-based queries, which can be added to widgets manually. However, they do not provide dynamic switching functionality for services in widgets.

Service swapping (D) is a powerful glass table feature that supports interactive dashboards by allowing users to view different service contexts within the same visual elements. It boosts efficiency, enhances user experience, and reduces the need to clone or duplicate widgets for every service monitored.

Question 9:

Which of the following accurately describes a feature or behavior of base searches in ITSI?

A. Base searches contain the search logic, entity rules, and thresholds that are applied across all associated KPIs.
B. Base searches can be configured to include only those entities that are part of the associated service when calculating KPI values.
C. The fewer KPIs that rely on a shared base search, the better the performance and efficiency, especially for anomaly detection.
D. A base search will execute on its defined schedule regardless of whether any KPI actually requires it.

Correct Answer: B. Base searches can be configured to include only those entities that are part of the associated service when calculating KPI values.

Explanation:

In Splunk ITSI, a base search is a shared search configuration that can be used by multiple KPIs across one or more services. Base searches are used to reduce redundancy, improve search performance, and maintain consistent logic across KPIs.

Let’s analyze each option:

Option A – Incorrect:
While the search logic is defined at the base search level, entity splitting and thresholds are defined at the KPI level, not at the base search. Each KPI uses the base search but applies its own entity-specific behavior and threshold conditions independently.
Option B – Correct:
ITSI provides an option to filter the base search results so that only entities associated with the service are considered in KPI calculation. This helps ensure that KPIs focus only on relevant components, which improves both accuracy and performance. This feature is especially useful in multi-tenant environments or when services share underlying infrastructure.
Option C – Incorrect:
Actually, the more KPIs that share a base search, the more efficient your system becomes. This is because the base search runs only once per interval and its results are reused across KPIs. So this statement contradicts best practices.
Option D – Incorrect:
A base search only runs if at least one KPI assigned to it is scheduled to run. If no active KPIs are using it during a specific time window, the base search will not execute, which conserves system resources.

So, Option B correctly captures a practical and valuable behavior of base searches — entity filtering for more precise and efficient KPI calculations.

Question 10:

Which of the following capabilities are supported in the ITSI Glass Table editor interface?
(Select all that apply)

A. Building and designing new glass tables from scratch.
B. Creating new correlation searches to detect notable events.
C. Configuring widgets to support service swapping functionality.
D. Adding KPI metric visualizations (like charts or gauges) to a glass table interface.

Correct Answers: A, C, D

Explanation:

The Glass Table editor in Splunk ITSI is a drag-and-drop design tool used to create custom dashboards for visualizing real-time KPI data, service health, and operational metrics. It provides rich interactivity and design flexibility.

Let’s break down each option:

Option A – Correct:
Yes, users can create glass tables from scratch using the visual editor. They can add background images, text, icons, and widgets to display KPI or service data in a customized layout.
Option B – Incorrect:
Correlation searches are not created in the glass table editor. Instead, they are configured separately in ITSI under “Correlation Searches” or “Content Management.” These searches detect patterns of interest and generate notable events, but they are not part of the visual design editor.
Option C – Correct:
The editor allows users to configure service swapping, a feature where users can toggle between services on a widget to dynamically view their data (e.g., swapping CPU KPI from Server A to Server B). This improves reusability and interaction in dashboards.
Option D – Correct:
Users can add KPI widgets, such as metric lanes, gauges, or line charts, which visualize historical or real-time KPI values directly on the glass table. These widgets are connected to ITSI’s KPIs or metrics and support threshold-based coloring and tooltips.