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| Section | Objectives |
|---|---|
| AppDynamics Architecture | - Controller and agents
|
| AppDynamics Fundamentals | - APM concepts and terminology
|
| Diagnostics and Troubleshooting | - Root cause analysis
|
| Monitoring and Instrumentation | - Application instrumentation
|
| Dashboards and Reporting | - Performance dashboards
|
| Alerting and Business Performance | - Business transaction performance
|
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NEW QUESTION # 55
Which type of Data Collector will capture code data such as method arguments, variables, and return values?
Answer: B
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 # 56
What AppDynamics Alert Action does a Performance Analyst need to select to post an AppDynamics event to a third-party collaboration tool?
Answer: C
Explanation:
To post an AppDynamics event to a third-party collaboration tool, the Performance Analyst needs to select the
"Make an HTTP Request" alert action. This action allows AppDynamics to send an HTTP request to a specified URL, which can be the endpoint provided by the third-party tool's API. This integration capability enables the automatic posting of events, alerts, and notifications from AppDynamics to collaboration tools, enhancing communication and response times to performance issues.
References:
AppDynamics documentation on Alert and Respond: Details the various alert actions available within AppDynamics, including the ability to make HTTP requests to integrate with external systems.
NEW QUESTION # 57 
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: B
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 # 58
Which two roll-up types can be configured for an Information Point? (Choose two.)
Answer: B,D
Explanation:
An Information Point custom metric can be configured with the roll-up types Average and Sum. The selected roll-up determines how values reported by repeated executions of the monitored class and method are aggregated during each metric reporting interval.
Average calculates the mean of all collected values within the interval. This is appropriate for measurements such as average item-processing time, average order value, or another numeric value where typical behavior is the primary concern.
Sum adds all collected values reported during the interval. It is appropriate for cumulative business or operational measurements, such as the total number of items processed, total transaction value, or total quantity handled by the instrumented method.
Max is not one of the configurable Information Point roll-up choices in this context. Although maximum values can appear in other AppDynamics metric-analysis scenarios, they are not selected as an Information Point custom-metric roll-up type. Count is represented separately through invocation-frequency metrics such as Calls per Minute rather than as the configured roll-up method for the collected numeric value.
Relevant CAAPA Study Guide topics include Information Points, Custom Metrics, Metric Aggregation, Average Roll-Up, Sum Roll-Up, Method Invocation Monitoring, and Calls per Minute.
NEW QUESTION # 59
What are three effects of Development Level Monitoring? (Choose three.)
Answer: B,C,F
Explanation:
Development Level Monitoring is intended for controlled development or diagnostic environments where maximum transaction visibility is more important than minimizing agent overhead. In this mode, the agent captures full call graphs, providing method-level execution detail rather than the reduced or partial call-graph collection associated with normal production monitoring.
The agent also attempts to collect a transaction snapshot for every transaction. "Attempts" is the critical distinction: snapshot creation remains subject to agent safeguards, resource constraints, transaction behavior, and collection limits. Therefore, Development Level Monitoring does not provide an absolute guarantee that every transaction will produce a retained snapshot, making option F incorrect.
Development mode additionally collects more detailed exit-call information for calls to backend systems, improving analysis of downstream databases, services, and other remote dependencies.
The agent does not ignore dev-mode-suspend-cpm. This property is a protective calls-per-minute threshold that can suspend development-mode collection when transaction volume becomes excessive. Relevant CAAPA Study Guide topics include Agent Configuration, Monitoring Levels, Transaction Snapshots, Call Graph Collection, Exit Calls, and Development-Mode Performance Safeguards.
NEW QUESTION # 60
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