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| Section | Weight | Objectives |
|---|---|---|
| Flow Maps and Application Architecture | 20% | - Component dependency visualization - Interpreting flow maps - Environment and topology overview |
| Information Points, Collectors, and Service Endpoints | 20% | - Service endpoint monitoring - Configuring information points - Database and custom collectors |
| Troubleshooting and Performance Analysis | 15% | - Analyzing call graphs and snapshots - Identifying bottlenecks and root causes - Remediation and optimization steps |
| Health Rules, Alerts, and Dashboards | 20% | - Creating and managing health rules - Custom dashboards and reporting - Alert configuration and actions |
| Business Transactions | 25% | - Transaction detection and configuration - Slow, error, and stalled transaction identification - Metrics analysis and baselining |
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NEW QUESTION # 82
In which two cases does AppDynamics start transaction snapshots? (Choose two.)
Answer: A,B
Explanation:
AppDynamics initiates transaction snapshot collection when a Business Transaction is classified as slow, very slow, stalled, or erroneous, subject to the configured snapshot thresholds and agent collection limits. These snapshots preserve detailed diagnostic context, including call graphs, exit calls, errors, and participating tiers, allowing analysts to isolate the code path or downstream dependency responsible for degraded user experience.
AppDynamics also captures snapshots through periodic snapshot collection. Periodic collection samples transactions at configured intervals even when their performance is normal. This provides representative diagnostic evidence and enables comparison between healthy and problematic executions without requiring every transaction to violate a performance threshold.
A sudden increase in Calls per Minute does not, by itself, constitute a standard snapshot trigger. Workload surges may influence application performance, but snapshots begin only when an applicable collection mechanism or diagnostic condition is satisfied. An "asynchronous session" is also not a standard snapshot- start condition; asynchronous processing can be included within a correlated snapshot after collection has already been initiated.
Relevant CAAPA Study Guide topics include Transaction Snapshots, User Experience Classification, Slow and Error Transactions, Periodic Snapshot Collection, Call Graphs, and Snapshot Collection Thresholds.
NEW QUESTION # 83
Which path is used to specify a metric that evaluates across multiple hardware entities or memory pools?
Answer: C
Explanation:
A relative metric path with a wildcard is used when a metric condition must be evaluated across multiple comparable entities, such as hardware resources, JVM memory pools, nodes, or other dynamically named metric branches.
A relative path is resolved in the context of each entity selected by the health rule or metric evaluation scope.
Adding a wildcard allows AppDynamics to match multiple child metric paths rather than requiring one fixed, fully qualified metric location. This is particularly useful when memory-pool names, hardware instances, or resource identifiers differ between nodes or runtime environments.
An absolute metric path points to one exact location in the metric hierarchy and is therefore better suited to a single, explicitly identified metric. Although wildcard matching can be supported in metric configurations, the correct approach for evaluating equivalent metrics across multiple scoped entities is the relative-path model.
The Metric Browser supports hierarchical metric navigation, and wildcard-capable paths are used where dynamic or repeated entity structures must be addressed. Relevant CAAPA Study Guide topics include Metric Browser, Relative and Absolute Metric Paths, Wildcard Metric Selection, Health Rule Conditions, Hardware Resource Metrics, and JVM Memory Pool Monitoring.
NEW QUESTION # 84 
Refer to the exhibit. The transaction score in the graphic displays an interesting performance pattern outside of business hours on 6/16/18. Which additional performance anomaly should be of most interest to a Performance Analyst?
Answer: C
Explanation:
The performance pattern outside of business hours on 6/16/18 that would be of most interest to a Performance Analyst is the elevated response time, as indicated on 6/19/18. This is because it shows a significant spike in response time, which could indicate a performance issue that needs to be addressed. Anomalies in response time can often be more indicative of underlying problems than changes in call volume, especially when they occur outside of expected peak periods.
References:
AppDynamics documentation on Transaction Score: https://docs.appdynamics.com/latest/en/application- monitoring/application-dashboard/transaction-score
NEW QUESTION # 85
When should URI Segments be used in Transaction Detection rules?
Answer: C
Explanation:
URI Segments should be used in Transaction Detection rules when the application is web-oriented. Web- oriented applications often have meaningful information in the URI that can identify different business transactions. URI Segments can help in defining patterns that match specific parts of the URI to distinguish different transactions.
References:
AppDynamics documentation on Transaction Detection: https://docs.appdynamics.com/latest/en/application- monitoring/business-transactions
NEW QUESTION # 86
A Performance Analyst received an alert that the Average Response Time is increasing after a new marketing offer was released. Which metric would quickly help the Performance Analyst determine that users may not be critically impacted?
Answer: D
Explanation:
If the Average Response Time is increasing after the release of a new marketing offer, seeing an increase in Calls per Minute could quickly help the Performance Analyst determine that users may not be critically impacted. This increase may indicate that despite the higher average response time, more users are engaging with the application, possibly due to interest generated by the marketing offer. It suggests that the system is handling more load, which could be a factor in the increased response time.
References:
AppDynamics documentation on Performance Metrics: Discusses the implications of various key performance indicators, including how an increase in Calls per Minute can be interpreted in the context of application performance.
NEW QUESTION # 87
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