Pega Autonomic Event Services

Not only a monitoring console, Pega® Autonomic Event Services is an intelligent agent that predicts and notifies administrators about system performance and business logic problems. The application provides suggestions and administration tools to correct these issues.

You can use Pega Autonomic Event Services in development and production environments.

In a development environment

Pega Autonomic Event Services is useful when building enterprise-level applications for discovering issues of scale and load that may significantly affect processing performance in a production environment. The application accelerates process optimization by identifying potential performance issues early in the development and testing phases. For example, a work object might have a list that is loaded from the database for the user to review. In a test system, the list might be small. However, when that system goes into production, there are many more items on the list and more users that are loading the list at the same time, which places greater stress on system performance. By using Pega Autonomic Event Services, you can identify trouble spots when they are small and before they cause a larger impact on application performance.

In a production environment

Pega Autonomic Event Services flags issues that might arise due to increased workload or reconfigured applications. For example, you might want to run processes during non-work periods that formerly were spread out during longer work periods. The concentration of server and database interactions might trigger alerts that reveal the need for better load balancing or hardware upgrades. As another example, you might configure a flow to automate a manual flow action, thus creating new demands on server and database interactions.

The following image shows the scorecard, which provides information about performance trends and a list of the most important items to fix.

Weekly scorecard for a system with performance issues

Weekly scorecard for a system with performance issues


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