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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Information Points, Collectors, and Service Endpoints | 20% | - Service endpoint monitoring - Configuring information points - Database and custom collectors |
| Topic 2: Health Rules, Alerts, and Dashboards | 20% | - Alert configuration and actions - Custom dashboards and reporting - Creating and managing health rules |
| Topic 3: Flow Maps and Application Architecture | 20% | - Interpreting flow maps - Environment and topology overview - Component dependency visualization |
| Topic 4: Troubleshooting and Performance Analysis | 15% | - Analyzing call graphs and snapshots - Identifying bottlenecks and root causes - Remediation and optimization steps |
| Topic 5: Business Transactions | 25% | - Metrics analysis and baselining - Transaction detection and configuration - Slow, error, and stalled transaction identification |
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NEW QUESTION # 102
What is the Node limit of the maximum Service Endpoints per node?
Answer: A
Explanation:
AppDynamics imposes a limit on the number of Service Endpoints that can be registered per node to ensure manageable performance and overhead. The limit per node is set to 100 Service Endpoints, which is a balance between providing detailed monitoring and maintaining application performance.
References:
AppDynamics documentation on Service Endpoints:
https://docs.appdynamics.com/latest/en/application-monitoring/monitor-service-endpoints
NEW QUESTION # 103
When should URI Segments be used in Transaction Detection rules?
Answer: B
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 # 104
Which statement is true for shared AppDynamics Dashboards?
Answer: B
Explanation:
A shared AppDynamics dashboard can be published through a shareable URL that allows viewers to access the dashboard without logging in to an AppDynamics account. This capability is intended for distributing operational or business-performance information to stakeholders who do not require full Controller access, such as support teams, management, or external display systems.
The dashboard owner controls whether the dashboard is shared and which information is exposed. Shared access is generally read-only, so unauthenticated viewers can examine the dashboard's widgets and current data but cannot modify its configuration, create monitoring rules, or access unrelated areas of the Controller.
Administrator access is not required merely to view a shared dashboard. Likewise, authenticated AppDynamics access is not mandatory when the dashboard has been explicitly published for external or public viewing. Network restrictions may still apply at the organization, proxy, firewall, or Controller-hosting level, but they are deployment controls rather than an AppDynamics login requirement for the shared dashboard itself.
Relevant CAAPA Study Guide topics include Custom Dashboards, Dashboard Sharing, Shareable URLs, Read-Only Access, Controller Permissions, and Role-Based Access Control.
NEW QUESTION # 105
Using the Business Transaction Discovery Sessions tools, which two items can a Performance Analyst browse? (Choose two.)
Answer: C,D
Explanation:
Business Transaction Discovery Sessions allow a Performance Analyst to browse the application's classes and methods while identifying suitable entry points for custom Business Transaction detection. The discovery process observes application execution and exposes loaded or invoked code structures, enabling the analyst to locate the class and method that represent the beginning of a meaningful transaction.
Browsing classes helps narrow the search to the relevant package or application component. After selecting a class, the analyst can inspect its methods and choose the appropriate method as the transaction entry point.
This is particularly useful when automatic discovery does not recognize a proprietary framework, background process, scheduled task, or other nonstandard execution path.
Database Calls are analyzed as exit calls or backend activity rather than browsed as transaction entry-point code. JMX MBeans are accessed through JMX monitoring and metric configuration tools. Memory Objects are examined through memory diagnostics, object instance tracking, or leak-detection functions, not Business Transaction Discovery Sessions.
Relevant CAAPA Study Guide topics include Business Transaction Discovery Sessions, Class and Method Browsing, Custom Match Rules, Entry-Point Configuration, Automatic Discovery, and Application Agent Instrumentation.
NEW QUESTION # 106
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: B
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 # 107
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