Cisco 500-420 - Questions & Answers

The performance pattern outside of business hours on 6/16/18 that would be of most interest to a Performance Analyst is the elevated response time, as indicated on 6/19/18. This is because it shows a significant spike in response time, which could indicate a performance issue that needs to be addressed.
Anomalies in response time can often be more indicative of underlying problems than changes in call volume, especially when they occur outside of expected peak periods.

References:
AppDynamics documentation on Transaction Score: (https://docs.appdynamics.com/latest/en/application-monitoring/application-dashboard/transaction-score)

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)

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.

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.

If a Performance Analyst has an urgent need to gather more data for an ongoing issue, they should enable Development Level Monitoring. This monitoring level increases the amount of detailed diagnostic data collected by the agent, such as snapshots and transaction traces, which can provide deeper insights into the issue at hand.

References:
AppDynamics documentation on Monitoring Levels: Describes the different levels of monitoring available, including Development Level Monitoring and the types of data each level collects.

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.

URI Segments should be used in Transaction Detection rules when the application is web-oriented. Web-oriented applications often have meaningful information in the URIthat can identify different business transactions. URI Segments can help in defining patterns that match specific parts of the URI to distinguish different transactions.

References:
AppDynamics documentation on Transaction Detection: (https://docs.appdynamics.com/latest/en/application-monitoring/business-transactions)

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)

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.

References:
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 environments where virtual machines are frequently created and destroyed, using the agent configuration properties-Dappdynamics.agent.reuse.nodeNameand-
Dappdynamics.agent.reuse.nodeName.prefixcan be beneficial. These settings allow AppDynamics agents to reuse node names for newly created instances, facilitating consistent monitoring and tracking across dynamic environments. This approach helps maintain clarity in application topology and ensures that performance data remains coherent even as the underlying infrastructure changes.

References:
AppDynamics documentation on Agent Configuration: Discusses advanced agent configuration options, including node name reuse, to accommodate dynamic environments such as those with frequently changing virtual machines. AppDynamics documentation on Infrastructure Monitoring: Offers insights into best practices for monitoring in dynamic and virtualized environments.