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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:

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

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.

The Metric Explorer in AppDynamics allows Performance Analysts to define and visualize Key Performance Indicators (KPIs) from a selection of metrics. By accessing the Transaction Analytics data set, analysts can create custom dashboards that focus on the metrics they've determined to be critical KPIs for their application's performance.

References:

AppDynamics documentation on Metric Explorer:

In Cisco AppDynamics, the transaction threshold configurations are typically found under the "Overview" tab. This is where you can view the health rule violations and performance baselines that are associated with transaction snapshots, which can include the configured transaction thresholds. These thresholds set the acceptable performance limits for transactions, and when these limits are exceeded, it may trigger health rule violations that are visible on the Overview tab.

References:

AppDynamics Documentation on Transaction Snapshots

AppDynamics Documentation on Health Rule Violations

Controller-level and tier/node-level dashboards in AppDynamics are treated as separate entities. They are scoped differently, with controller-level dashboards providing a global view across the entire AppDynamics domain, and tier/node-level dashboards being specific to particular tiers or nodes within an application. Performance Analysts do not have the ability to cross-reference directly between these two sets of dashboards within the AppDynamics UI.

References:

AppDynamics documentation on Dashboards: https://docs.appdynamics.com/latest/en/application-monitoring/custom-dashboards

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.

During a war room scenario, which is a real-time troubleshooting session, widgets in AppDynamics dashboards update in near real-time. This allows teams to observe the immediate impact of changes and identify issues as they occur.

References:

AppDynamics documentation on War Rooms:

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.