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To identify if automatic remediation actions have been taken for a health rule violation in AppDynamics, a Performance Analyst should expand the "Description" field of the health rule violation event. This section will provide details on the actions executed as part of the automatic remediation process. These details help analysts understand the steps taken by the system to mitigate the issue without manual intervention.References:AppDynamics documentation on Health Rule Violations and Automated Actions.

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.

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

To view all captured endpoints by service using the REST interface in AppDynamics, a Performance Analyst would navigate to the Metric Browser and proceed to the "Consumed Endpoints" section. From there, drilling down on specific endpoints within the Metric Browser allows the analyst to explore the services associated with each endpoint. This method enables detailed analysis of endpoint metrics, facilitating the monitoring and optimization of service performance.

References:

AppDynamics documentation on Metric Browser: Guides on navigating the Metric Browser to access and analyze various application metrics, including those related to endpoints and services.

AppDynamics documentation on REST API: Provides information on how to utilize the REST API for retrieving metrics, including endpoint data.

Data collectors in AppDynamics supplement business transaction and transaction analytics data with application data by capturing additional information during transaction execution. This can include method arguments, return values, and invocation context, which enriches the transaction data with more detailed application-level insights. This capability is crucial for in-depth performance analysis and troubleshooting, providing a more comprehensive view of application behavior.

References:

AppDynamics documentation on Data Collectors: Explains how to configure data collectors to capture and display detailed application data within business transactions.

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.

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.

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

If the Average Response Time is increasing after the release of a new marketing offer, seeing an increase in Calls per Minute could quickly help the Performance Analyst determine that users may not be critically impacted. This increase may indicate that despite the higher average response time, more users are engaging with the application, possibly due to interest generated by the marketing offer. It suggests that the system is handling more load, which could be a factor in the increased response time.

References:

AppDynamics documentation on Performance Metrics: Discusses the implications of various key performance indicators, including how an increase in Calls per Minute can be interpreted in the context of application performance.

When configuring an Information Point in AppDynamics, you can add match conditions to refine what gets measured. Match conditions based on a regex applied to the method allow you to specify which methods to include based on a regular expression pattern. Matching based on the invoked object allows you to specify which objects' methods are included, filtering the data according to the object type or instance. These conditions help in pinpointing specific methods or objects for which you want to collect runtime information.References:AppDynamics documentation on Information Points and Match Conditions.