Cisco 500-420 Practice Test - Questions Answers, Page 6

The permission to enable snapshot archiving in AppDynamics typically falls under advanced operational capabilities, such as those categorized under 'Agent Advanced Operation.' This permission allows users to archive transaction snapshots for long-term storage and analysis, which is essential for historical performance analysis and auditing purposes.

AppDynamics documentation on Role-Based Access Control: Explains the different permissions and roles within AppDynamics, including those related to advanced agent operations and snapshot archiving.

A split exit point in AppDynamics is identified using static application values. Static values provide a consistent and predictable way to categorize exit points, making it easier to aggregate and analyze similar types of interactions with external services or components.

AppDynamics documentation on Exit Points: Provides insights into how exit points are defined and identified within AppDynamics, including the use of static values for split exit points.

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.

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.

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.

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.

When an Information Point is created in AppDynamics without adding custom data, it automatically collects three key performance indicators (KPIs): Response Time, Errors per Minute, and Calls per Minute. Response Time measures the time taken to complete a transaction or operation, providing insights into application performance. Errors per Minute tracks the number of errors occurring within the scope of the Information Point, helping identify problematic areas. Calls per Minute counts the number of times the specified operation or transaction is invoked, indicating its usage frequency and potential impact on application performance.

AppDynamics documentation on Information Points: Discusses the creation and configuration of Information Points, including the default metrics collected.

In AppDynamics Application Performance Management (APM), two types of Data Collectors are SQL data collectors and Method invocation data collectors. SQL data collectors capture and record detailed information about SQL queries executed by the application, helping identify slow or inefficient database operations. Method invocation data collectors capture information about specific method calls within the application code, including execution times and parameters, providing deep insights into code-level performance.

AppDynamics documentation on Data Collectors: Provides detailed information on configuring SQL and Method invocation data collectors for in-depth application monitoring.

In AppDynamics, you can create health rules to monitor various metrics and set up actions based on the thresholds defined for these metrics. For monitoring Java container thread counts, you can set a health rule based on Node Health - specifically on thread pools - to trigger when the thread count exceeds a specific value. The Notification Action can then be configured to send an email to the development team whenever this threshold is breached.

AppDynamics documentation on Health Rules: https://docs.appdynamics.com/21.6/en/infrastructure-visibility/health-rules

When drilling down into a JDBC exit call for an Oracle backend, AppDynamics provides detailed information about the call. The data points include:

Query type, which can indicate whether it's a SELECT, INSERT, UPDATE, or DELETE statement.

Statement type, which describes the nature of the SQL statement being executed.

Originating node, which identifies the node from which the JDBC call originated.

These data points help in understanding the nature and source of database operations, which can be critical for performance analysis and troubleshooting.

AppDynamics documentation on Database Monitoring:

Errors in a transaction are identified by examining the snapshots that capture the problematic transactions. By setting the appropriate time range, a Performance Analyst can drill down into the snapshots within the Error tab to identify and analyze errors. These snapshots provide detailed diagnostic information, such as stack traces, slow SQL queries, and error logs, which are vital for pinpointing the root cause of transaction errors.

AppDynamics documentation on Transaction Snapshots: