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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: ITOA Administration | 10% | - ITOA dashboard overview - Configuring ITOA |
| Topic 2: Advanced Topics | 16% | - Custom KPIs and calculations - ITSI and Splunk Enterprise Security integration - Service-level availability reporting - ITSI content management |
| Topic 3: ITSI Service Design | 18% | - Service dependencies and dependencies view - Creating and configuring services - Entity templates and filters - Service Health Score calculation |
| Topic 4: Glass Tables | 14% | - Creating Glass Tables - Configuring Glass Table elements - Entity Drilldown |
| Topic 5: Service Discovery and Installation | 8% | - Service Discovery overview - Creating adaptive threshold templates - Service Discovery installation |
| Topic 6: ITSI Administration | 14% | - KPI base searches and aggregation - Managing services using deep dives - ITSI searches and scheduled searches - Backup and restore ITSI configuration |
| Topic 7: ITSI Analytics | 12% | - Glass Table thresholds - Notable Events and aggregation policies - Configuring aggregation policies |
| Topic 8: ITSI Overview and Concepts | 8% | - Entities and services - ITSI key concepts and terminology - ITSI product overview |
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NEW QUESTION # 50
Which anomaly detection algorithm fulfills the paired monitoring requirement?
Answer: B
Explanation:
Splunk ITSI offers two built#in anomaly detection algorithms:TrendingandEntity Cohesion. TheTrending algorithm works on theaggregate KPI series, comparing recent KPI behavior with its historical pattern to detect unusual trending patterns over time. It doesnotevaluate behavior across separate entities within the KPI split - it simply looks at deviations from historical trends in the combined KPI values. On the other hand, the Entity Cohesionalgorithm is specifically designed to detect when entities that are expected to behave similarly begin to diverge in behavior. When a KPI is split by entity (for example, multiple servers, locations, or service tiers), Entity Cohesion normalizes each entity's time series and compares them against each other.
If one entity's pattern differs significantly from the group's patterns, it is flagged as an anomaly. This matches the "paired monitoring requirement" of producing an alert whenone entity in the KPI is not behaving similarly to the other entities. The option describing entity cohesion paired with that requirement reflects the correct use case for this algorithm in ITSI. Neither trending anomaly detection nor entity cohesion anomaly detection is intended to detect multiple KPIs deviating at the service level - such cross#KPI alerts are handled by other alerting constructs like multi#KPI alerts or correlation searches, not these specific anomaly algorithms.
NEW QUESTION # 51
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 # 52
What is an episode?
Answer: B
Explanation:
Explanation
It's a deduplicated group of notable events occurring as part of a larger sequence, or an incident or period considered in isolation.
NEW QUESTION # 53
Which capabilities are enabled through "teams"?
Answer: C
Explanation:
D is the correct answer because teams allow you to restrict access to service content in UI views such as service analyzers, glass tables, deep dives, and episode review. Teams also control access to services and KPIs for editing and viewing purposes. Teams do not affect the ability to search against the itsi_summary index, restrict notable event alert actions, or restrict searches against the itsi_notable_audit index.
References: Overview of teams in ITSI
NEW QUESTION # 54
What are valid considerations when designing an ITSI Service? (Choose all that apply.)
Answer: A,B,C
Explanation:
Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/Configure/ImplementPerms A, B, and C are correct answers because service access control requirements for ITSI Team Access should be considered before creating the ITSI Service, as different teams may have different permissions and views of the service data. Entities, entity meta-data, and entity rules should also be planned carefully to support the service design and configuration, as they determine how ITSI maps data sources to services and KPIs.
Services, entities, and saved searches are stored in the ITSI app, while events created by KPI execution are stored in the itsi_summary index for faster retrieval and analysis. References: ITSI service design best practices, Overview of ITSI indexes
NEW QUESTION # 55
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