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| Section | Objectives |
|---|---|
| Topic 1: Monitoring and Instrumentation | - Infrastructure monitoring
|
| Topic 2: AppDynamics Fundamentals | - APM concepts and terminology
|
| Topic 3: Alerting and Business Performance | - Alert configuration
|
| Topic 4: Diagnostics and Troubleshooting | - Root cause analysis
|
| Topic 5: AppDynamics Architecture | - Controller and agents
|
| Topic 6: Dashboards and Reporting | - Performance dashboards
|
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NEW QUESTION # 63
Which type of Data Collector will capture code data such as method arguments, variables, and return values?
Answer: A
Explanation:
The "Method Invocation Data Collector" is specifically designed to capture code-level data such as method arguments, variables, and return values. This type of data collector enables deep visibility into the execution of methods within transactions, providing valuable insights into the application's behavior and performance. This detailed level of monitoring is essential for diagnosing complex issues and understanding the inner workings of business transactions.
References:
AppDynamics documentation on Data Collectors: Details the types of data collectors available, including Method Invocation Data Collectors, and how they can be used to capture detailed code-level data.
NEW QUESTION # 64
What does the Live Preview option in a Business Transaction Discovery Session allow a user to do?
Answer: A
Explanation:
The Live Preview option in a Business Transaction Discovery Session in AppDynamics allows a user to verify the effectiveness of newly configured Transaction Discovery Rules. This feature provides real-time feedback on how these rules identify and categorize business transactions, enabling users to adjust and fine-tune the rules to ensure accurate and meaningful transaction monitoring.
References:
AppDynamics documentation on Business Transaction Management: Includes information on Business Transaction Discovery Sessions and the use of Live Preview to validate Transaction Discovery Rules.
NEW QUESTION # 65
What must a Performance Analyst first configure in order to monitor end-to-end latency performance metrics in AppDynamics?
Answer: A
Explanation:
To monitor end-to-end latency performance metrics, a Performance Analyst must first define the end-to-end latency transaction. This involves configuring the business transactions to include the necessary entry and exit points that capture the complete flow of the transaction, thereby enabling the measurement of the total latency.
References:
AppDynamics documentation on Business Transactions: https://docs.appdynamics.com/latest/en/application- monitoring/business-transactions
NEW QUESTION # 66
Which health rule violation event will be triggered when a Performance Analyst modifies the existing health rule that is already in critical violation?
Answer: D
Explanation:
When a Performance Analyst modifies an existing health rule that is already in a state of critical violation, the event that is typically triggered is "Health Rule Violation Continues - Critical." This event indicates that, despite the modification, the health rule is still being violated at a critical level. The system recognizes that the conditions for the health rule violation are still being met and continues to alert accordingly.
References:
AppDynamics documentation on Health Rules and Events: Explains the different types of health rule events and the conditions under which they are triggered.
NEW QUESTION # 67
When a manual diagnostic session is triggered, what snapshots are captured?
Answer: C
Explanation:
A manual diagnostic session causes AppDynamics to collect detailed transaction snapshots for the selected Business Transaction during the active diagnostic period. When an instance of that Business Transaction crosses multiple instrumented tiers or nodes, the snapshot collection context is propagated with the transaction. Consequently, AppDynamics captures the participating transaction segments from all nodes through which the Business Transaction passes, producing an end-to-end distributed snapshot.
The capture is not restricted to transactions classified as slow, very slow, or errors. Those classifications are commonly used by automatic diagnostic-session and snapshot-triggering mechanisms, whereas a manual session is deliberately initiated to gather deeper diagnostic evidence, including transactions that might otherwise be considered normal.
Option D is incomplete because the triggering node initiates snapshot collection, but the resulting distributed snapshot can include downstream nodes that participate in the transaction. Options A and C incorrectly limit collection to performance-policy violations and error conditions.
Relevant CAAPA Study Guide topics include Transaction Snapshots, Manual Diagnostic Sessions, Distributed Transaction Correlation, Call Graph Collection, Business Transaction Health, and Cross-Tier Transaction Tracing.
NEW QUESTION # 68
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