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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 send a summary report of specific events every two hours, a Performance Analyst can use the "Email Digests" feature in AppDynamics. This feature allows for the automated aggregation and delivery of pertinent event information at predefined intervals, ensuring stakeholders remain informed about the application's performance and significant events without the need for constant manual monitoring.

References:

• AppDynamics documentation on Alerting and Notifications: Details the configuration of email notifications and digests for events and alerts, including scheduling and content customization options.
• AppDynamics documentation on Reports: Provides information on various reporting features, including the setup of automated email digests.

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.

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

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 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:

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

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

If a Business Transaction stops being displayed on the Business Transaction Dashboard after continuous load, it could be due to the deletion of the Business Transaction Custom Match Rule. Custom Match Rules in AppDynamics are used to define custom business transactions based on specific criteria. If such a rule is deleted, transactions that were previously identified and displayed based on that rule may no longer be recognized as distinct business transactions, leading to their disappearance from the dashboard.

References:

• AppDynamics documentation on Business Transactions: Provides insights on configuring and managing business transactions, including the use of custom match rules.

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.

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.

Information Points in AppDynamics are designed to collect custom metrics that are specific to the business or code aspects of an application. They can capture Business Metric Data, which pertains to the performance metrics that directly impact business processes, and Code Metric Data, which relates to the performance of specific methods or segments of code within the application. This allows for targeted monitoring and analysis of areas significant to the business's objectives and technical performance.

References:

• AppDynamics documentation on Information Points: Provides details on how to set up Information Points to collect custom business and code metrics for in-depth performance analysis.

The "Method Invocation Data Collector" is specifically designed to capture code-level data such as method arguments, variables, and return values. This type of data collector enables deep visibility into the execution of methods within transactions, providing valuable insights into the application's behavior and performance. This detailed level of monitoring is essential for diagnosing complex issues and understanding the inner workings of business transactions.

References:

• AppDynamics documentation on Data Collectors: Details the types of data collectors available, including Method Invocation Data Collectors, and how they can be used to capture detailed code-level data.

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.

The default value pair for the setting "Collect up to ____ snapshots per minute for _____ minutes" in the configuration for Slow Transactions is 10, 10. This means that by default, the system is set to collect up to 10 snapshots per minute for a duration of 10 minutes during a diagnostic session.

References:

• AppDynamics documentation on Transaction Snapshots: Outlines the default settings for diagnostic session duration and collection rates, including the collection of snapshots.

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.

When creating Information Points in AppDynamics, wildcards can be utilized to select multiple methods or classes, thereby broadening the scope of data collection. This feature is particularly useful for monitoring similar operations across different components of an application, enabling a more efficient and scalable approach to gathering custom metrics.

References:

• AppDynamics documentation on Information Points: Elaborates on the process of setting up Information Points, including the use of wildcards to capture metrics from multiple methods or classes.

To confirm if a memory leak is occurring, one should refer to the Tiers and Nodes section of the AppDynamics Controller UI, navigate to the Memory tab, and observe the Heap Utilization over time in relation to the Heap's Current Usage (MB) versus the Maximum (MB) allocated. Consistent growth in heap utilization or an upward trend that does not decrement even after garbage collection indicates a potential memory leak.References:AppDynamics documentation on Memory Leak Detection and Heap Analysis.

When an Information Point is created in AppDynamics without adding custom data, it automatically collects three key performance indicators (KPIs): Response Time, Errors per Minute, and Calls per Minute. Response Time measures the time taken to complete a transaction or operation, providing insights into application performance. Errors per Minute tracks the number of errors occurring within the scope of the Information Point, helping identify problematic areas. Calls per Minute counts the number of times the specified operation or transaction is invoked, indicating its usage frequency and potential impact on application performance.

References:

• AppDynamics documentation on Information Points: Discusses the creation and configuration of Information Points, including the default metrics collected.