500-420 Sample Questions Answers

Key Performance Indicators (KPIs) such as "CPU %Busy" and "Memory Used%" are critical for providing insights into server-level resource consumption. "CPU %Busy" indicates the percentage of time the CPU is actively working on processes, reflecting the server's processing workload. "Memory Used%" shows the proportion of memory utilized, indicating how much of the server's RAM is being consumed by applications and processes. These KPIs are essential for understanding and managing server performance and resource allocation.

References:

• AppDynamics documentation on Server Monitoring: Includes information on monitoring server-level metrics, including CPU and memory utilization, to assess resource consumption.

Server Tagging in AppDynamics allows a Performance Analyst to compare and filter related servers by using custom metadata. This feature enables users to group and organize their servers based on criteria that make sense for their environment, such as role, location, environment type, or any other custom metadata.

References:

• AppDynamics documentation on Server Tagging: https://docs.appdynamics.com/latest/en/infrastructure-visibility/infrastructure-visibility-settings/server-tags

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

To determine if a given Java class is visible in AppDynamics, the "Preview Business transactions" feature in a Business Transaction Discovery Session can be used. This feature allows users to validate and preview the detection of business transactions, which includes ensuring that specific Java classes and methods are being correctly identified and monitored by AppDynamics.

References:

• AppDynamics documentation on Business Transaction Detection: Explains how to conduct a Business Transaction Discovery Session and use the preview feature to validate the visibility and detection of business transactions, including specific Java classes.

To share snapshot details from the snapshot window in AppDynamics, the options to "Download PDF" and "Export" are typically used. "Download PDF" allows users to generate a PDF report of the snapshot details, providing a convenient and portable format for sharing and review. The "Export" option enables the extraction of snapshot data in various formats (e.g., CSV, XML), facilitating further analysis or sharing with other tools and stakeholders.

References:

• AppDynamics documentation on Snapshots: This section covers how snapshots capture detailed performance data for transactions, including how to share and export this information for collaborative 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.

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

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

The permission to enable snapshot archiving in AppDynamics typically falls under advanced operational capabilities, such as those categorized under "Agent Advanced Operation." This permission allows users to archive transaction snapshots for long-term storage and analysis, which is essential for historical performance analysis and auditing purposes.

References:

• AppDynamics documentation on Role-Based Access Control: Explains the different permissions and roles within AppDynamics, including those related to advanced agent operations and snapshot archiving.

When integrating with a third-party event management system, the Performance Analyst can set up an HTTP Request action within AppDynamics. This allows for the creation of a custom HTTPrequest to the event management system's API, which can be configured to send alerts to Level 1 support or any other designated recipient.

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.

A transaction snapshot in AppDynamics is a detailed report of a single execution of a business transaction. Its primary purpose is to analyze issues with a specific business transaction by providing a comprehensive view of the transaction's execution path, including timing, call graphs, and database queries. This allows performance analystsand developers to drill down into individual transactions to diagnose performance bottlenecks, errors, or anomalies.

References:

• AppDynamics documentation on Transaction Snapshots: Offers detailed guidance on how to capture and analyze transaction snapshots to troubleshoot and optimize application performance.

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:

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.

Creating a Transaction Group using the 'Create Group' action in AppDynamics allows for the aggregation of data from multiple transactions under a single group, facilitating a consolidated view of similar transactions. This differs from defining a Transaction Detection Rule, which typically focuses on identifying and categorizing individual transactions based on specific criteria. Transaction Groups do not change the names of incoming requests nor reduce the number of overall business transactions; instead, they provide a method for organizing and analyzing related transactions collectively, offering a streamlined approach compared to individually configuring Transaction Detection Rules for each transaction.

References:

• AppDynamics documentation on Business Transactions: Covers the concept of Transaction Groups and their role in organizing and analyzing transaction data, as well as the process for creating and managing Transaction Detection Rules.