Most Recent Splunk SPLK-3002 Exam Questions & Answers

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. Reference:Deep Dives

To identify that a memory usage KPI is going critical, an analyst can leverage multiple views within Splunk IT Service Intelligence (ITSI), each offering a different perspective or level of detail:

A) Memory KPI in a glass table: A glass table can display the current status of the memory usage KPI, along with other related KPIs and services, providing a high-level overview of system health.

B) Memory panel of the OS Host Details view in the Operating System module: This specific panel within the OS Host Details view offers detailed metrics and trends related to memory usage, allowing for in-depth analysis.

C) Memory swim lane in a Deep Dive: Deep Dives allow analysts to visually track the performance and status of KPIs over time. A swim lane dedicated to memory usage can highlight periods where the KPI goes critical, along with the context of other related KPIs.

D) Service & KPI tiles in the Service Analyzer: The Service Analyzer provides a comprehensive overview of all services and their KPIs. The tiles related to memory usage can quickly alert analysts to critical conditions through color-coded indicators.

Each of these views contributes to a comprehensive monitoring strategy, enabling analysts to detect and respond to critical memory usage conditions from various analytical perspectives.

A realistic troubleshooting workflow in ITSI is:

B) Service Analyzer --> Notable Event Review --> Deep Dive

This workflow involves using the Service Analyzer dashboard to monitor the health and performance of your services and KPIs, using the Notable Event Review dashboard to investigate and manage the notable events generated by ITSI, and using the Deep Dive dashboard to analyze the historical trends and anomalies of your KPIs and metrics.

The other workflows are not realistic because they involve components that are not part of the troubleshooting process, such as correlation search, aggregation policy, and KPI. These components are used to create and configure the alerts and episodes that ITSI generates, not to investigate and resolve them. Reference: [Service Analyzer dashboard in ITSI],Overview of Episode Review in ITSI, [Overview of deep dives in ITSI]

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.

When an episode warrants investigation, the analyst acknowledges the episode, which moves the status fromNewtoIn Progress.

An episode represents a disruption of service operation causing impact to business operations. It is a deduplicated group of notable events occurring as part of a larger sequence, or an incident or period considered in isolation. In Episode Review, you can manage the episodes and their statuses using various actions. One of the actions is Acknowledge, which changes the status of an episode from New to Acknowledged and assigns the current user as the owner. This action indicates that someone is working on resolving the episode and prevents duplicate efforts from other users. Reference:Overview of Episode Review in ITSI, [Episode actions in Episode Review]