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| Section | Objectives |
|---|---|
| AppDynamics Fundamentals | - APM concepts and terminology
|
| Dashboards and Reporting | - Performance dashboards
|
| Monitoring and Instrumentation | - Application instrumentation
|
| AppDynamics Architecture | - Controller and agents
|
| Alerting and Business Performance | - Business transaction performance
|
| Diagnostics and Troubleshooting | - Root cause analysis
|
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NEW QUESTION # 40
An online order portal for a restaurant has a "menu" transaction with different request types that must be monitored as separate transactions, such as "menu.salads" and "menu.entree." A Performance Analyst wants to create one rule that separates the transactions instead of creating an individual rule for each request type.
Which option should be enabled on a Custom Match rule?
Answer: A
Explanation:
The Performance Analyst should enable Split Transaction using request data. This capability allows a single Custom Match rule to dynamically divide one base transaction into multiple business transactions according to values contained in the incoming HTTP request. For example, the rule can identify the base transaction as menu and append a request-derived value such as salads or entree, producing distinct transactions named menu.salads and menu.entree.
This approach avoids maintaining separate match rules for every menu category and scales automatically as additional request values are introduced.
An HTTP Request Data Collector captures request attributes for visibility within transaction snapshots but does not itself split or rename business transactions. A Method Invocation Data Collector captures method parameters, return values, or invoked-object data and is also unrelated to transaction splitting. Split Transaction using JSON is appropriate only when the required discriminator must specifically be extracted from a JSON payload.
Relevant CAAPA topics include Business Transaction Detection, Custom Match Rules, Transaction Naming, Request-Based Splitting, and Data Collectors.
NEW QUESTION # 41
Which three pieces of information are required when creating a new database collector? (Choose three.)
Answer: B,C
Explanation:
When creating a new database collector in AppDynamics, the essential pieces of information required include the "Database hostname/IP address," "Database Type," and "Port number." These details are crucial for establishing a connection to the database and ensuring accurate monitoring. The hostname/IP address identifies the server where the database is hosted, the Database Type specifies the database management system (e.g., MySQL, Oracle), and the Port number is necessary for network communication with the database server.
References:
AppDynamics documentation on Database Visibility: This section explains how to set up database collectors, including the required information for successful configuration.
NEW QUESTION # 42
Developers and operations personnel complain the Controller tracks many irrelevant Java classes and methods. How does a Performance Analyst exclude this unhelpful information?
Answer: D
Explanation:
To streamline the monitoring process and enhance the relevance of collected data, AppDynamics allows Performance Analysts to exclude certain Java classes and methods from instrumentation. This is done through the " Configuration > Instrumentation > Call Graph Settings " menu, where irrelevant packages and classes can be specified for exclusion. This approach prevents the AppDynamics agent from tracking unnecessary or irrelevant methods, thus reducing overhead and focusing on the most critical aspects of application performance.
References:
AppDynamics documentation on Call Graph Settings: This section details how to configure call graph settings, including the exclusion of specific classes and methods from instrumentation, to optimize performance monitoring.
NEW QUESTION # 43
Which type of Data Collector will capture code data such as method arguments, variables, and return values?
Answer: D
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 # 44
A client needs to reference a metric from different applications on an AppDynamics dashboard. Which of the following is true?
Answer: C
Explanation:
In AppDynamics, metrics from different applications can indeed be cross-referenced on a single dashboard.
This allows for a more holistic view of an organization's application ecosystem, facilitating the comparison and correlation of performance metrics across different applications within the same AppDynamics controller.
References:
AppDynamics documentation on Custom Dashboards: Details how to create custom dashboards that can include metrics from multiple applications, enabling cross-referencing and comprehensive performance monitoring.
NEW QUESTION # 45
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