The "Application Health Report" is a built-in scheduled report in AppDynamics that includes vital metrics such as load, response time, and error graphs. This report provides a comprehensive overview of the application's health and performance, making it an essential tool for Performance Analysts to regularly review and share with stakeholders to ensure the application meets performance standards and user expectations.
References:
AppDynamics documentation on Reporting: Covers the types of reports available within AppDynamics, including the Application Health Report, detailing its contents and how to schedule and customize it.
AppDynamics documentation on Application Performance Management: Provides an overview of key performance indicators and metrics critical for assessing application health, many of which are included in the Application Health Report.

When Business Transaction Lock Down is enabled in AppDynamics, no new business transactions will be automatically discovered to avoid uncontrolled growth in the number of business transactions. To track a new service as a unique Business Transaction, one needs to create a Custom Match Rule that specifies the criteria for identifying the business transaction. In this case, the Custom Match Rule should be based on the Web Service Name and Operation Name which are the distinguishing characteristics of the new service. This allows for the precise identification and monitoring of the service within the AppDynamics platform.
References: AppDynamics documentation on Business Transaction configuration and Custom Match Rules.

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.

A snapshot flow map presents execution-specific timing information that helps explain why AppDynamics captured that particular transaction instance. The relevant metrics are Thread Blocking Time, Execution Time, and Asynchronous Activity Processing Time.
Execution Time shows the elapsed processing time for the transaction segment and helps determine whether the request exceeded slow or very slow transaction thresholds. Thread Blocking Time identifies time during which the executing thread was blocked or waiting, potentially because of lock contention, synchronization, resource availability, or another thread-related delay. A substantial blocking value can explain why an otherwise ordinary code path produced a slow snapshot.
Asynchronous Activity Processing Time represents time consumed by asynchronous work associated with the transaction, such as executor tasks, callbacks, or background processing correlated with the originating request. Excessive asynchronous processing can materially increase end-to-end completion time and trigger snapshot collection.
Tier Response Time and Node Response Time are aggregated performance metrics across multiple transactions. They provide useful operational context but do not directly describe the timing characteristics of one captured transaction execution.
Relevant CAAPA Study Guide topics include Transaction Snapshots, Snapshot Flow Maps, Execution Time, Thread Blocking, Asynchronous Transaction Tracking, and Slow Transaction Diagnostics.

In the Browser Real User Monitoring (RUM) Dashboard, the Usage Stats section provides insights into user demographics, including the types of browsers and devices they are using. This section would help the Performance Analyst understand which browsers and devices are affected during a specific time period when there has been an increase in the Business Transaction error rate.
References:
AppDynamics documentation on Browser RUM:
https://docs.appdynamics.com/21.6/en/end-user-monitoring/browser-monitoring/browser-real-user-monito