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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:

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:

When a Performance Analyst is faced with issues related to transaction response times on a specific node, focusing on the "Transaction performance" data is most relevant. This is because transaction performance metrics provide direct insights into the business transactions' speed, response times, and execution times, which are critical for identifying and troubleshooting performance issues. By selecting "Transaction performance" when creating a health rule, the analyst can monitor specific metrics such as average response time, slow transaction count, and very slow transaction count, which are directly related to the performance of business transactions on the node in question.

References:

• AppDynamics documentation on Health Rules: This section explains how to create and configure health rules to monitor application performance metrics, including transaction performance.
• AppDynamics documentation on Business Transactions: Provides details on how AppDynamics identifies and monitors business transactions, which are key to understanding application performance.