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

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 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

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.

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.

When creating a new database collector in AppDynamics, the essential pieces of information required include the "Database hostname/IP address," "Database Type," and "Port number." These details are crucial for establishing a connection to the database and ensuring accurate monitoring. The hostname/IP address identifies the server where the database is hosted, the Database Type specifies the database management system (e.g., MySQL, Oracle), and the Port number is necessary for network communication with the database server.

References:

• AppDynamics documentation on Database Visibility: This section explains how to set up database collectors, including the required information for successful configuration.

To post an AppDynamics event to a third-party collaboration tool, the Performance Analyst needs to select the "Make an HTTP Request" alert action. This action allows AppDynamics to send an HTTP request to a specified URL, which can be the endpoint provided by the third-party tool's API. This integration capability enables the automatic posting of events, alerts, and notifications from AppDynamics to collaboration tools, enhancing communication and response times to performance issues.

References:

• AppDynamics documentation on Alert and Respond: Details the various alert actions available within AppDynamics, including the ability to make HTTP requests to integrate with external systems.

When an application team requests an increase in the Application Business Transaction limit for visibility purposes, it's crucial for the Performance Analyst to focus on the transactions that are currently exceeding the limit and understand why. This approach helps in identifying whether the limit is being reached due to genuinely essential transactions or if there are redundant, irrelevant, or improperly defined transactions contributing to the limit breach. By analyzing and rationalizing the transactions, the analyst can ensure that only valuable transactions are monitored, optimizing resource usage and maintaining effective observability without necessarily increasing the limit.

References:

• AppDynamics documentation on Business Transaction Limits: Discusses the implications of business transaction limits and strategies for managing and optimizing these limits within AppDynamics.
• AppDynamics Best Practices Guide: Offers recommendations for configuring and managing business transactions, including handling limits and ensuring meaningful transaction monitoring.

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 the Browser Real User Monitoring (RUM) Dashboard, the Usage Stats section provides insights into user demographics, including the types of browsers and devices they are using. This section would help the Performance Analyst understand which browsers and devices are affected during a specific time period when there has been an increase in the Business Transaction error rate.

References:

• AppDynamics documentation on Browser RUM: https://docs.appdynamics.com/21.6/en/end-user-monitoring/browser-monitoring/browser-real-user-monitoring

The "Application Health Report" is a built-in scheduled report in AppDynamics that includes vital metrics such as load, response time, and error graphs. This report provides a comprehensive overview of the application's health and performance, making it an essential tool for Performance Analysts to regularly review and share with stakeholders to ensure the application meets performance standards and user expectations.

References:

• AppDynamics documentation on Reporting: Covers the types of reports available within AppDynamics, including the Application Health Report, detailing its contents and how to schedule and customize it.
• AppDynamics documentation on Application Performance Management: Provides an overview of key performance indicators and metrics critical for assessing application health, many of which are included in the Application Health Report.

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 "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.

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.

Errors in a transaction are identified by examining the snapshots that capture the problematic transactions. By setting the appropriate time range, a Performance Analyst can drill down into the snapshots within the Error tab to identify and analyze errors. These snapshots provide detailed diagnostic information, such as stack traces, slow SQL queries, and error logs, which are vital for pinpointing the root cause of transaction errors.

References:

• AppDynamics documentation on Transaction Snapshots: