500-420 Exam Questions & Answers

Information Points in AppDynamics are custom metrics that track specific data within your applications, such as method invocations or the value of method arguments. These metrics can be utilized in various features of AppDynamics, most notably in 'Alerting' and 'Custom Dashboards.' Alerting allows you to set up notifications based on the thresholds set for Information Points, ensuring that teams are promptly informed about significant changes or anomalies. Custom Dashboards enable the visualization of Information Points metrics alongside other key performance indicators, providing a comprehensive view of application health and performance tailored to specific needs.

AppDynamics documentation on Information Points: Explains how to create and use Information Points to monitor specific business-relevant metrics.

AppDynamics documentation on Alerting: Details the process of setting up health rules and alerts based on various metrics, including those from Information Points.

AppDynamics documentation on Custom Dashboards: Guides on how to create dashboards that incorporate a wide range of metrics, including Information Points, for customized monitoring.

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.

For an e-commerce application built using a microservices architecture, logically grouping Transaction Detection rules can be effectively achieved through 'Use Transaction Group.' This approach allows for the organization of business transactions into meaningful groups that reflect the application's structure and the interactions between its microservices. By grouping transactions, it becomes easier to monitor, analyze, and troubleshoot the application as a whole and its individual components, enhancing the visibility and management of the application's performance.

AppDynamics documentation on Business Transactions: Provides insights on how to configure and manage business transactions, including grouping and monitoring strategies.

AppDynamics documentation on Microservices Monitoring: Offers guidance on best practices for monitoring applications designed with microservices architecture, including transaction grouping.

When new business transactions are not appearing on the Business Transaction Dashboard after deploying new code, developers should verify that there are no exclusion rules in place on the tier where the new code was deployed. Additionally, it is crucial to ensure that the Auto Discovery feature for servlets is enabled for Java agents, as this allows AppDynamics to automatically detect and name business transactions based on incoming requests to servlets. Both of these checks are necessary to ensure that new business transactions can be discovered and monitored. Reference: AppDynamics documentation on Business Transaction detection and Java Agent configuration.

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.