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| Section | Weight | Objectives |
|---|---|---|
| Event Analytics | 5% | - Describe Event Analytics features - Configure and use Event Analytics |
| Glass Tables | 5% | - Describe glass tables - Use glass tables - Design glass tables - Configure glass tables |
| Managing Notable Events | 10% | - Work with notable events - Describe multi-KPI alerts - Define key notable events terms and relationships - Describe notable events workflow - Customize notable event views |
| Introducing ITSI | 5% | - Examine the ITSI user interface - Identify what ITSI does - Describe reasons for using ITSI |
| Deep Dives | 10% | - Use default deep dives - Describe deep dive concepts - Create and customize deep dives |
| Anomaly Detection | 5% | - Work with anomaly events - Enable anomaly detection |
| Services and KPIs | 15% | - Configure KPI thresholds and alerts - Manage service dependencies - Define services and KPIs - Use entities in KPI searches |
| Troubleshooting ITSI | 10% | - Diagnose common issues - Monitor ITSI performance - Resolve configuration and operational problems |
| Aggregation Policies | 5% | - Create aggregation policies - Use smart mode aggregation |
| ITSI Architecture and Deployment | 10% | - Describe ITSI architecture - Plan and design deployment - Manage ITSI modules |
| Correlation and Multi-KPI Searches | 5% | - Create multi-KPI alerts - Manage notable event storage - Define correlation searches |
| Access Control and Security | 5% | - Configure user roles and permissions - Create service-level teams |
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NEW QUESTION # 83
Which of the following are characteristics of service templates? (select all that apply)
Answer: C,D
Explanation:
Service templates in Splunk IT Service Intelligence (ITSI) are designed to streamline the creation of services by providing pre-defined configurations:
B) Service templates contain KPIs and KPI thresholds: This allows for the standardized deployment of services with predefined performance indicators and their associated thresholds, ensuring consistency across similar services.
C) Service templates can contain specific or generic entity rules: These rules define how entities are associated with services created from the template, allowing for both broad and targeted applicability.
While service templates contain configurations for KPIs, thresholds, and entity rules, the ability to modify templates after services have been instantiated from them is limited. Changes to a template do not retroactively affect services already created from that template. Moreover, service templates do not inherently contain domain-specific dashboards or deep dives; these are created separately within ITSI.
NEW QUESTION # 84
Which of the following statements describe default glass tables in ITSI?
Answer: A
Explanation:
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.
NEW QUESTION # 85
Which of the following is an advantage of using adaptive time thresholds?
Answer: D
Explanation:
Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/SI/TimePolicies Adaptive thresholds are thresholds calculated by machine learning algorithms that dynamically adapt and change based on the KPI's observed behavior. Adaptive thresholds are useful for monitoring KPIs that have unpredictable or seasonal patterns that are difficult to capture with static thresholds. For example, you might use adaptive thresholds for a KPI that measures web traffic volume, which can vary depending on factors such as holidays, promotions, events, and so on. The advantage of using adaptive thresholds is:
A). Automatically update thresholds daily to manage dynamic changes to KPI values. This is true because adaptive thresholds use historical data from a training window to generate threshold values for each time block in a threshold template. Each night at midnight, ITSI recalculates adaptive threshold values for a KPI by organizing the data from the training window into distinct buckets and then analyzing each bucket separately.
This way, the thresholds reflect the most recent changes in the KPI data and account for any anomalies or trends.
The other options are not advantages of using adaptive thresholds because:
B). Automatically adjust KPI calculation to manage dynamic event data. This is not true because adaptive thresholds do not affect the KPI calculation, which is based on the base search and the aggregation method.
Adaptive thresholds only affect the threshold values that are used to determine the KPI severity level.
C). Automatically adjust aggregation policy grouping to manage escalating severity. This is not true because adaptive thresholds do not affect the aggregation policy, which is a set of rules that determines how to group notable events into episodes. Adaptive thresholds only affect the threshold values that are used to generate notable events based on KPI severity level.
D). Automatically adjust correlation search thresholds to adjust sensitivity over time. This is not true because adaptive thresholds do not affect the correlation search, which is a search that looks for relationships between data points and generates notable events. Adaptive thresholds only affect the threshold values that are used by KPIs, which can be used as inputs for correlation searches.
References: Create adaptive KPI thresholds in ITSI
NEW QUESTION # 86
When working with a notable event group in the Notable Events Review dashboard, which of the following can be set at the individual or group level?
Answer: C
Explanation:
In the Notable Events Review dashboard within Splunk IT Service Intelligence (ITSI), when working with a notable event group, users can set or adjust certain attributes at the individual event level or at the group level.
These attributes include:
* Severity:The importance or impact level of the notable event or group, which can be adjusted to reflect the current assessment of the situation.
* Status:The current state of the notable event or group, such as "New," "In Progress," or "Resolved," indicating the progress in addressing the event or group.
* Owner:The user or team responsible for managing and resolving the notable event or group.
These settings allow for effective management and tracking of notable events, ensuring that they are appropriately prioritized, acted upon, and resolved by the responsible parties.
NEW QUESTION # 87
Which of the following is a best practice when configuring maintenance windows?
Answer: B
Explanation:
It's a best practice to schedule maintenance windows with a 15- to 30-minute time buffer before and after you start and stop your maintenance work.
Reference:
A maintenance window is a period of time when a service or entity is undergoing maintenance operations or does not require active monitoring. It is a best practice to schedule maintenance windows with a 15- to 30-minute time buffer before and after you start and stop your maintenance work. This gives the system an opportunity to catch up with the maintenance state and reduces the chances of ITSI generating false positives during maintenance operations. For example, if a server will be shut down for maintenance at 1:00PM and restarted at 5:00PM, the ideal maintenance window is 12:30PM to 5:30PM. The 15- to 30-minute time buffer is a rough estimate based on 15 minutes being the time period over which most KPIs are configured to search data and identify alert triggers. Reference: Overview of maintenance windows in ITSI
NEW QUESTION # 88
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