500-420 Exam Questions Tutorials

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 interactionsbetween 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.

References:

• 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.

If an agent fails to register with the Controller, a Performance Analyst should check the network/firewall rules to ensure that the agent can communicate with the Controller over the network. Additionally, it is crucial to verify the free license count to confirm thatthere are available licenses for the agent to register. Insufficient licenses or network communication barriers can prevent successful agent registration.

References:

• AppDynamics documentation on Agent Registration: Describes the prerequisites and troubleshooting steps for agent registration with the Controller.
• AppDynamics documentation on Licensing: Provides details on how the licensing model works, including how to check for available licenses.

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.

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