Cisco 500-420 - Cisco AppDynamics Associate Performance Analyst(CAAPA)

The Transaction Score view in the Application Dashboard categorizes transactions by load, response time, errors, slow transactions, and stalled transactions. It provides an aggregated value for a specific time range, giving an at-a-glance indication of the health and performance of business transactions.

References:

AppDynamics documentation on Transaction Score: https://docs.appdynamics.com/latest/en/application-monitoring/application-dashboard

To plot Host CPU and GC (Garbage Collection) Time Spent in a single view, the "JMX tab under 'Tiers and Nodes'" and the "Metrics Browser" are the appropriate methods. TheJMX tab provides access to Java Management Extensions (JMX) metrics, including those related to GC time. The Metrics Browser allows for the customization and aggregation of various metrics, including Host CPU usage and GC metrics, enabling a combined view of these critical performance indicators.

References:

AppDynamics documentation on Monitoring Tiers and Nodes: Discusses the JMX metrics available for Java applications, including garbage collection details.

AppDynamics documentation on the Metrics Browser: Describes how to use the Metrics Browser to view and analyze a wide range of performance metrics.

The primary concern for a Performance Analyst when considering the impact of automatic diagnostic sessions is the application itself. Intensive diagnostic sessions can be resource-heavy, potentially affecting the application's performance. Therefore, it is often necessary to limit the duration and frequency of these sessions to ensure they do not negatively impact the application’s end-user experience.

References:

AppDynamics documentation on Diagnostic Sessions: https://docs.appdynamics.com/latest/en/troubleshoot/diagnostic-sessions

When a Performance Analyst modifies an existing health rule that is already in a state of critical violation, the event that is typically triggered is "Health Rule Violation Continues - Critical." This event indicates that, despite the modification, the health rule is still being violated at a critical level. The system recognizes that the conditions for the health rule violation are still being met and continues to alert accordingly.

References:

AppDynamics documentation on Health Rules and Events: Explains the different types of health rule events and the conditions under which they are triggered.

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.

References:

AppDynamics documentation on Database Monitoring:

When a Performance Analyst observes a significant decrease in an application's workload (calls/min), reviewing the "Top Business Transactions by Load" in the Application Dashboard can provide valuable insights. This feature allows the analyst to quickly identify which business transactions have experienced the most significant changes in load, potentially pinpointing the root cause of the overall workload decrease. It offers a focused view of the application's performance, highlighting areas that may require further investigation or immediate action.

References:

AppDynamics documentation on Application Dashboard: Describes the features and capabilities of the Application Dashboard, including how to view and analyze the top business transactions by load.

AppDynamics documentation on Business Transactions: Details the importance of monitoring business transactions and how they can be used to understand application performance trends.

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.

References:

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

When an application team requests an increase in the Application Business Transaction limit for visibility purposes, it's crucial for the Performance Analyst to focus on the transactions that are currently exceeding the limit and understand why. This approach helps in identifying whether the limit is being reached due to genuinely essential transactions or if there are redundant, irrelevant, or improperly defined transactions contributing to the limit breach. By analyzing and rationalizing the transactions, the analyst can ensure that only valuable transactions are monitored, optimizing resource usage and maintaining effective observability without necessarily increasing the limit.

References:

AppDynamics documentation on Business Transaction Limits: Discusses the implications of business transaction limits and strategies for managing and optimizing these limits within AppDynamics.

AppDynamics Best Practices Guide: Offers recommendations for configuring and managing business transactions, including handling limits and ensuring meaningful transaction monitoring.

Controller-level custom dashboards in AppDynamics have the flexibility to provide views that aggregate and compare data from different applications on the same Controller, as well as offer a customized view of applications, servers, and database performance data. This capability enables a holistic view of the IT environment, facilitating cross-application insights and the ability to correlate performance across different layers of the technology stack. Such dashboards are invaluable for understanding overarching trends, pinpointing systemic issues, and driving informed decision-making across multiple applications and infrastructure components.

References:

AppDynamics documentation on Custom Dashboards: Provides detailed instructions on creating and customizing dashboards at the Controller level, including the aggregation and comparison of data from various sources.

AppDynamics documentation on Controller UI: Explains the functionalities available within the Controller UI, including the creation of comprehensive dashboards that encompass application, server, and database metrics.