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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Business Transactions | 25% | - Transaction detection and configuration - Slow, error, and stalled transaction identification - Metrics analysis and baselining |
| Topic 2: Troubleshooting and Performance Analysis | 15% | - Remediation and optimization steps - Analyzing call graphs and snapshots - Identifying bottlenecks and root causes |
| Topic 3: Flow Maps and Application Architecture | 20% | - Component dependency visualization - Environment and topology overview - Interpreting flow maps |
| Topic 4: Information Points, Collectors, and Service Endpoints | 20% | - Database and custom collectors - Configuring information points - Service endpoint monitoring |
| Topic 5: Health Rules, Alerts, and Dashboards | 20% | - Creating and managing health rules - Custom dashboards and reporting - Alert configuration and actions |
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NEW QUESTION # 38
Which three programming languages are supported by the AppDynamics Application Performance Monitoring solution? (Choose three.)
Answer: B,D,F
Explanation:
The supported programming-language options are Go, C/C++, and C#. AppDynamics provides monitoring capabilities for applications built with these languages through language-specific agents, supported runtime instrumentation, or application-monitoring SDKs.
C# is monitored through the AppDynamics .NET Agent, which instruments supported .NET and .NET Framework applications to discover Business Transactions, collect call graphs, monitor exceptions, and correlate downstream service calls. C/C++ applications can be monitored using the AppDynamics C/C++ SDK and associated application instrumentation capabilities, enabling custom Business Transaction definition, exit-call tracking, and distributed transaction correlation. Go applications are supported through AppDynamics monitoring components designed for Go-based services, allowing transaction visibility and correlation within distributed application environments.
Perl is not listed as a standard AppDynamics APM language-agent platform. React is a JavaScript user- interface library rather than a programming language; browser-side React applications are typically observed through Browser Real User Monitoring. iOS Family describes a mobile platform, not a programming language, and is addressed through Mobile Real User Monitoring.
Relevant CAAPA topics include Application Agent Platforms, .NET Agent, C/C++ SDK, Go Application Monitoring, Business Transaction Instrumentation, and Real User Monitoring.
NEW QUESTION # 39
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 # 40
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 # 41
Which two statements are correct about creating Information Points? (Choose two.)
Answer: B,C
Explanation:
When creating Information Points in AppDynamics, wildcards can be utilized to select multiple methods or classes, thereby broadening the scope of data collection. This feature is particularly useful for monitoring similar operations across different components of an application, enabling a more efficient and scalable approach to gathering custom metrics.
References:
AppDynamics documentation on Information Points: Elaborates on the process of setting up Information Points, including the use of wildcards to capture metrics from multiple methods or classes.
NEW QUESTION # 42
When a manual diagnostic session is triggered, what snapshots are captured?
Answer: A
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 # 43
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