When you configure an information point, you automatically receive the KPI metrics (called code metrics) for the information point method.

The code metrics are:

• Total call count
• Calls per minute count
• Errors per minute
• Average response time

You can supplement the KPI metrics with custom business metrics for the information point.

Business metrics reflect the value of runtime data, such as the method parameter, return value, or a value captured by getter chain on the object on which the identified method was invoked. The business metric value represents either the sum or average of the values of the code point you identify as the information point.

Information points can give you significant insight into how the performance of an application corresponds to business performance. For example, depending on the nature of your application, you could use it to resolve business questions such as:

• What is the average value of the credit card total?
• How many credit cards did my application process in a certain time period, regardless of the business transaction?
• What was the average time spent processing a credit card transaction?

A example of a practical use of an information point is ignored exceptions. Exceptions, especially one that occurs frequently, can contribute to CPU spikes in a JVM. If you configure the exception to be ignored in Splunk AppDynamics, for example, if it is generated in the underlying application framework and does not have a direct bearing on your application performance, it may not be readily evident to you when the exception is affecting your application. An information point that counts the exception occurrence can help you identify the additional overhead.