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Understanding the PegaRULES Log Analyzer

Updated on September 10, 2021


What is the PegaRULES Log Analyzer tool and how does it work?


The PegaRULES Log Analyzer (PLA) tool is a Web application that consolidates and summarizes three types of logs from individual JVM server nodes in your application system. The log data provide key information about operational and system health. Developers and system administrators can use this information to quickly identify, diagnose, and remediate issues that may be degrading or compromising:

  • Performance — The Alert log contains diagnostic messages that identify individual system events that exceed performance thresholds or failures. Alert messages contain a set of field values that identify the alert, the conditions that caused it, and the state of system when it occurred.
  • Stability — The Pega (system) log gathers system errors, exceptions (with their stack trace statements), debug statements, and any other messages not specified as alerts. The Pega log can contain messages created by your activities as well as messages created by standard rules.
  • Scalability — The JVM garbage collection (GC) log provides insight into how a java application makes use of memory.

When to use PLA

It is strongly recommended that you use PLA to test a new or reconfigured Process Commander application during UAT performance and stress testing and immediately after deployment into a production environment. These are the phases when performance, stability and scaling issues are likely to occur.

Regular monitoring during development and production helps ensure that your application is operating at its full potential. PLA signals issues that may grow into major operational problems if not addressed early.

Operational checklist

The results of a PLA import should indicate the following:

  • Alert log — No critical alerts. These include PEGA0004, PEGA0017, PEGA0019, PEGA0026, and PEGA0028. If there are unusually large numbers of warning alerts, they should be evaluated for their impact before being deemed acceptable for production.
  • System log — No exceptions, errors, or debugs.
  • Garbage collection log — A GC time equal to or less than 2%.

PLA provides an efficient method for diagnosing the issues and locating their root causes.

Viewing data in PLA

The Home view in the PLA window (shown below) presents a table summarizing the benchmark metrics in each type of log. For instance, the log for January 23 there were 198 exceptions. The next day there were 116 alerts of which 5 were critical. These are issues that need immediate remediation. Given the large number of total alerts (which include non-critical alerts), you should investigate them to assess their impact on production and remedied if necessary.


Using view options located in the left panel enables you to display the data in summary and list reports for each log type. Here is an example of an alerts list report generated when you click Alerts:


You can sort the tables on almost any of the columns. For example, you can sort the alert list shown above by Severity so that Critical alerts rise to the top of the report. From this view you can drill down into an alert to display the alert details including PAL data, trace list, pega stack, and parameter page. Here is an example for a PEGA0028 alert:


Exporting PLA data to Excel spreadsheets

You can easily export the PLA data to an Excel spreadsheet (assuming it is installed on your workstation) for further diagnosis and information-sharing among development team members. Clicking an Excel button in the Home view table extracts and loads the data for that date and automatically starts Excel .

The spreadsheet is organized into summary and list report pages similar to those used in the PLA interface. Here is an example of the critical alert data as it is displayed in a spreadsheet:


Pre-configured Excel PivotTables provide multi-dimensional views of the data so that you can add or remove fields to suit your requirements.

For more information

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