500-420 Cisco AppDynamics Associate Performance Analyst(CAAPA) Questions and Answers

During a war room scenario, which is a real-time troubleshooting session, widgets in AppDynamics dashboards update in near real-time. This allows teams to observe the immediate impact of changes and identify issues as they occur.

References:

• AppDynamics documentation on War Rooms:

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.

References:

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

To determine if a given Java class is visible in AppDynamics, the "Preview Business transactions" feature in a Business Transaction Discovery Session can be used. This feature allows users to validate and preview the detection of business transactions, which includes ensuring that specific Java classes and methods are being correctly identified and monitored by AppDynamics.

References:

• AppDynamics documentation on Business Transaction Detection: Explains how to conduct a Business Transaction Discovery Session and use the preview feature to validate the visibility and detection of business transactions, including specific Java classes.

AppDynamics allows for several reports to be scheduled for periodic generation and sent to email recipients. Among these, Application Health, Error Trends, and CustomDashboards are types of reports that can be automatically generated and delivered, providing regular insights into the application's performance and issues.

References:

• AppDynamics documentation on Reports: https://docs.appdynamics.com/latest/en/application-monitoring/reporting

When analyzing database performance in AppDynamics, the "Queries" tab within the database collector view is where a Performance Analyst should navigate to find slow queries. This tab presents a list of database queries executed by the application, highlighting those with long execution times, which are potential bottlenecks impacting application performance.

References:

• AppDynamics documentation on Database Monitoring: Details the database collector feature, including how to use the Queries tab to identify and analyze slow database queries.

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 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

The Transaction Score tab within the Application Dashboard is designed to display performance trends across various metrics including Snapshots, Average Response Time, and Events. It gives a comprehensive view of the transaction performance, providing a score that reflects the health and reliability of transactions over time.

References:

• AppDynamics documentation on Application Dashboard:

To share snapshot details from the snapshot window in AppDynamics, the options to "Download PDF" and "Export" are typically used. "Download PDF" allows users to generate a PDF report of the snapshot details, providing a convenient and portable format for sharing and review. The "Export" option enables the extraction of snapshot data in various formats (e.g., CSV, XML), facilitating further analysis or sharing with other tools and stakeholders.

References:

• AppDynamics documentation on Snapshots: This section covers how snapshots capture detailed performance data for transactions, including how to share and export this information for collaborative analysis.

AppDynamics imposes a limit on the number of Service Endpoints that can be registered per node to ensure manageable performance and overhead. The limit per node is set to 100 Service Endpoints, which is a balance between providing detailed monitoring and maintaining application performance.

References:

• AppDynamics documentation on Service Endpoints: https://docs.appdynamics.com/latest/en/application-monitoring/monitor-service-endpoints

When a Performance Analyst is faced with issues related to transaction response times on a specific node, focusing on the "Transaction performance" data is most relevant. This is because transaction performance metrics provide direct insights into the business transactions' speed, response times, and execution times, which are critical for identifying and troubleshooting performance issues. By selecting "Transaction performance" when creating a health rule, the analyst can monitor specific metrics such as average response time, slow transaction count, and very slow transaction count, which are directly related to the performance of business transactions on the node in question.

References:

• AppDynamics documentation on Health Rules: This section explains how to create and configure health rules to monitor application performance metrics, including transaction performance.
• AppDynamics documentation on Business Transactions: Provides details on how AppDynamics identifies and monitors business transactions, which are key to understanding application performance.

Development Level Monitoring in AppDynamics is designed for use in a lower volume, non-production environment. For a default configuration, Development Level Monitoring will get automatically disabled if the monitored environment exceeds a threshold, typically a maximum of 1000 calls per minute, and the Maximum heap utilization percentage goes above 95%. These thresholds are in place to prevent excessive overhead in a production environment where such detailed monitoring could impact performance.

References:

• AppDynamics documentation on Agent Configuration: Provides information on configuration settings for monitoring levels, including when Development Level Monitoring is automatically disabled due to exceeding thresholds.

To monitor end-to-end latency performance metrics, a Performance Analyst must first define the end-to-end latency transaction. This involves configuring the business transactions to include the necessary entry and exit points that capture the complete flow of the transaction, thereby enabling the measurement of the total latency.

References:

• AppDynamics documentation on Business Transactions: https://docs.appdynamics.com/latest/en/application-monitoring/business-transactions

Key Performance Indicators (KPIs) such as "CPU %Busy" and "Memory Used%" are critical for providing insights into server-level resource consumption. "CPU %Busy" indicates the percentage of time the CPU is actively working on processes, reflecting the server's processing workload. "Memory Used%" shows the proportion of memory utilized, indicating how much of the server's RAM is being consumed by applications and processes. These KPIs are essential for understanding and managing server performance and resource allocation.

References:

• AppDynamics documentation on Server Monitoring: Includes information on monitoring server-level metrics, including CPU and memory utilization, to assess resource consumption.

When configuring Automatic Cleanup of stale Business Transactions, the "minutes since creation" option is often paired with the "Number of Calls" metric. This setting ensures that business transactions that have not been called within a certain timeframe and have had a negligible number of calls are automatically cleaned up, helping to maintain an organized and relevant set of business transactions in the monitoring system.

References:

• AppDynamics documentation on Business Transactions: Discusses best practices for managing business transactions, including the automatic cleanup based on time and call volume thresholds.

The Live Preview option in a Business Transaction Discovery Session in AppDynamics allows a user to verify the effectiveness of newly configured Transaction Discovery Rules. This feature provides real-time feedback on how these rules identify and categorize business transactions, enabling users to adjust and fine-tune the rules to ensure accurate and meaningful transaction monitoring.

References:

• AppDynamics documentation on Business Transaction Management: Includes information on Business Transaction Discovery Sessions and the use of Live Preview to validate Transaction Discovery Rules.