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| Section | Objectives |
|---|---|
| Diagnostics and Troubleshooting | - Performance bottleneck identification
|
| Dashboards and Reporting | - Performance dashboards
|
| Alerting and Business Performance | - Business transaction performance
|
| Monitoring and Instrumentation | - Application instrumentation
|
| AppDynamics Architecture | - Controller and agents
|
| AppDynamics Fundamentals | - APM concepts and terminology
|
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問題 #105
Where would a Performance Analyst view detailed trend graphs representing application performance from the viewpoint of the end user in AppDynamics?
答案：A
解題說明：
The Performance Analyst should use Browser Apps. This area contains Browser Real User Monitoring data and presents application performance from the actual end user's perspective. It provides detailed trend graphs for browser pages and AJAX requests, including metrics such as end-user response time, page load time, network time, server time, DOM processing time, resource-loading time, request volume, errors, and geographic or browser-related performance variations.
These measurements enable the analyst to determine whether a performance problem originates in the browser, network, content-delivery path, application server, or a downstream dependency. The graphs can also be filtered by time range, page, browser type, device, operating system, location, and other user-session dimensions.
Transaction Analytics is used for querying and analyzing transaction and business-event data. Remote Services focuses on backend dependencies and external service calls. Applications primarily provides server- side APM visibility into Business Transactions, tiers, nodes, and application flow.
Relevant CAAPA Study Guide topics include Browser Real User Monitoring, Browser Applications, End- User Response Time, Page and AJAX Performance, User Experience Analysis, and Client-Side Performance Trends.
問題 #106
A Performance Analyst needs to send a summary report of specific events every two hours. Which feature can enable this automated report summary?
答案：D
解題說明：
To send a summary report of specific events every two hours, a Performance Analyst can use the "Email Digests" feature in AppDynamics. This feature allows for the automated aggregation and delivery of pertinent event information at predefined intervals, ensuring stakeholders remain informed about the application's performance and significant events without the need for constant manual monitoring.
References:
AppDynamics documentation on Alerting and Notifications: Details the configuration of email notifications and digests for events and alerts, including scheduling and content customization options.
AppDynamics documentation on Reports: Provides information on various reporting features, including the setup of automated email digests.
問題 #107
Refer to the exhibit.
Using this heap-utilization graph, which method is used to confirm whether a memory leak is occurring during a specific timeframe?
答案：B
解題說明：
The Tiers and Nodes > Memory tab provides the appropriate JVM-level view for confirming suspected heap growth over a selected timeframe. The analyst should compare Heap Utilization (%) with Heap Current Usage (MB) versus Max (MB) and observe the effect of major garbage-collection events.
A potential memory leak is indicated when heap usage rises progressively and fails to return to a stable lower level after garbage collection. The important pattern is not simply high memory utilization, but an increasing post-garbage-collection baseline over time. The exhibit shows current heap usage gradually increasing relative to the maximum heap allocation, which warrants further memory diagnostics.
Hardware-resource memory metrics represent operating-system memory and do not isolate JVM heap behavior. Swap usage can indicate host memory pressure but cannot confirm an application heap leak. JMX metrics may expose heap values, but the dedicated Memory tab provides the quickest correlated visualization for heap utilization, maximum heap, current usage, and garbage collection.
Relevant CAAPA topics include JVM Memory Monitoring, Heap Utilization, Garbage Collection, Tiers and Nodes Memory View, Memory Leak Detection, and Object Instance Tracking.
問題 #108
Refer to the exhibit.
The application flow map shows several downstream applications in yellow, while the flow lines are blue and activity within the current application appears normal. Because the tier depends on these downstream applications, how could a Performance Analyst quickly evaluate the map against previous performance?
答案：B
解題說明：
The Performance Analyst should use Compare Against Baseline. This flow-map function provides an immediate comparison between current application behavior and the established historical baseline for the selected time range. It helps identify whether response time, load, call volume, or dependency behavior has deviated from what AppDynamics considers normal.
In the exhibit, the yellow downstream applications indicate a warning state, even though the blue flow lines suggest that the current calls themselves are not showing an obvious critical condition. Comparing the current flow map against baseline allows the analyst to determine whether those downstream dependencies are performing worse than their customary levels and whether the tier's dependency pattern has changed.
Correlation Analysis is intended to identify statistical relationships among metrics rather than provide a direct historical flow-map comparison. Health Rule Violations show triggered conditions but do not provide the fastest visual comparison with prior performance. Metric Browser Baselines can expose baseline values for individual metrics, but require more manual investigation.
Relevant CAAPA topics include Application Flow Maps, Dynamic Baselines, Compare Against Baseline, Dependency Analysis, and Health-State Interpretation.
問題 #109
A Performance Analyst is creating a custom baseline and attempting to tag it to a widget in a dashboard.
Which statement is true?
答案：C
解題說明：
AppDynamics supports the creation of custom baselines, allowing a Performance Analyst to define expected metric behavior over a selected historical period and recurring time pattern. Custom baselines are useful when the standard daily, weekly, or trend-based baselines do not accurately represent the application's operating schedule, seasonal demand, or business cycle.
However, a custom baseline cannot be directly tagged or bound to an individual dashboard widget. Dashboard widgets can visualize metrics and, depending on the widget type, may display standard comparison or baseline-related information, but they do not provide a mechanism for associating a specifically named custom baseline with that widget.
Custom baselines are primarily applied in monitoring and evaluation contexts such as health-rule conditions, where current metric values can be compared against expected behavior using defined baseline criteria and standard deviations. Therefore, the baseline itself can be created and used for performance evaluation, but the analyst's attempt to attach it directly to a dashboard widget is unsupported.
Relevant CAAPA Study Guide topics include Dynamic Baselines, Custom Baseline Configuration, Health Rule Conditions, Baseline Evaluation, Metric Visualization, and Custom Dashboard Widget Limitations.
問題 #110
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