Skip to main content

Published Release Notes

Find release notes for the selected Pega Version and Capability

Browse resolved issues for Platform releases.

This documentation is for non-current versions of Pega Platform. For current release notes, go here.

Predictive models can drive predictions

Valid from Pega Version 8.6

You can use predictive models as the basis of your predictions. As a data scientist, you can now use Machine Learning Operations (MLOps) to replace models in your system. You can replace a model in a prediction with a PMML, H2O MOJO, or Pega OXL predictive model, as well as a scorecard or field, and then approve the update for deployment to a production environment. You can respond to a Prediction Studio notification that an active model does not generate enough lift and decide to replace the low-performing model with a high-accuracy model. You can also update a prediction on a regular basis, for example, whenever you develop a new churn model in an external environment.

For more information, see Replace models in predictions and migrate changes to production with MLOps.

Enhancing the performance of your Next-Best-Action strategy with globally optimized strategies

Valid from Pega Version 8.6

Starting in version 8.6, Pega Platform™ combines the versatility of Next-Best-Action Designer with strategy performance enhancements provided by using globally optimized strategies (GOS). Decrease the run time and memory usage of executing the Next-Best-Action strategy in batch or real-time scenarios by using the globally optimized strategies generated by Next Best Action Designer.

GOS is supported by Pega Platform's standard business change management process. GOS rules are automatically included in relevant revision packages.

For more information, see Enhance the performance of your Next-Best-Action strategy with globally optimized strategies (8.6).

Improved processing of correspondence details

Valid from Pega Version 8.6

When you send correspondence, the system now does not update the pxSendDateTime property on the pxCorrSummary work page that belongs to pyWorkPage. In previous versions of Pega Platform™, after sending correspondence, the update of the pxSendDateTime property could cause errors when working with an application at run time. To prevent such issues, Pega Platform now includes a pyEnableCorrSummary when rule that, by default, is set to false. If your business scenario requires updating the pxCorrSummary work page, set the when rule value to true.

For more information, see:

Support for picklists with parameterized data pages in App Studio in Cosmos React UI

Valid from Pega Version 8.6

You can now use data pages with parameters to populate a property of the picklist type with filtered results in App Studio. For example, in a survey case type, you can use a parameterized data page to configure cascading drop-down controls in which the values in a secondary drop-down list are based on the value that the user selects in the primary drop-down list. With dynamically-sourced picklists, you get greater flexibility in configuring picklists, and users see more accurate values.

For more information, see link Dropdown control Properties — General tab.

Questionnaires available in App Studio

Valid from Pega Version 8.6

App Studio now supports authoring questionnaires, which in previous releases of Pega Platform™ were known as surveys. You can create questionnaires, add question pages, and populate the pages with questions of different types so that you can collect the exact data that your business processes require. For more efficient data management and reuse, data objects from a data model now store answers to questions, instead of autogenerated properties. For example, when a customer provides a date of birth in a questionnaire, and your application stores the date as a data object, you can conveniently reuse that data object in related cases. For greater flexibility, both standard Pega Platform and Cosmos React applications support questionnaires, however, some question types are unavailable in Cosmos React.

For more information, see:

Remote case types in App Studio

Valid from Pega Version 8.6

App Studio now supports remote case types for applications that you build on Cosmos React. With remote case types, you can create a case type inside one application, and then work on cases based on this case type in another, remote application. As a result, users can perform work from multiple applications on one screen without the need to switch between applications, which results in increased efficiency and faster case resolution.

For more information, see:

Easier customer record management in Customer Profile Designer (early preview)

Valid from Pega Version 8.6

The new Customer Profile Designer module of Pega Customer Decision Hub™ makes it possible for marketing analysts and strategy designers to define the associated data for each customer context directly in the Pega Customer Decision Hub portal. It is also possible to define more complex associated data structures that use a custom data flow, or define associated data of different types, such as RDBMS and Cassandra, for the same customer context.

Customer Profile Designer is available in Pega Customer Decision Hub 8.6 version as an early preview version. The functionality will be further expanded in future releases.

For more information, see Manage customer records in Customer Profile Designer (8.6).

Support for calling a data transform from a case life cycle in App Studio and initializing data at case creation

Valid from Pega Version 8.6

You can now call a data transform from a case life cycle in a low-code way in App Studio. For example, when a customer wants to order the same product again, your application can reuse the shipping information from their previous order. Additionally, by configuring data initialization for a case type, you can prepopulate fields at case creation. For example, an application for a delivery service can apply the customer's preferred delivery options when a new case starts. These enhancements save time for developers because the system can initialize data and prepopulate fields in a case by reusing existing logic, and for customers, who do not need to manually enter their details every time.

For more information, see Calling a data transform from a case and Initializing data at case creation.

Data propagation for questionnaires in case types

Valid from Pega Version 8.6

Pega Platform™ now provides a tool to prepopulate answers in a questionnaire that runs in a case by propagating data from a parent case. At run time, specified questions in a questionnaire that users complete as part of case processing, can display answers by using information that users already provided in the parent case. As a result, you speed up the development of your application and help users process cases and complete questionnaires faster.

For more information, see:

Kafka data set enhancements

Valid from Pega Version 8.6

The Kafka data set is a high-throughput and low-latency platform for handling real-time data feeds that you can use as input for Pega Platform event strategies.

For better integration of Pega Platform with externally hosted Kafka, the following enhancements are implemented:

  • Support for Kafka message keys and headers - extended values data format (JSON Data Transform, Apache Avro)
  • Custom value processing
  • Configuring topic names by using Application Properties
  • Data-Admin-Kafka enhancements - supporting a wide range of connection properties

For more information, see Improve your Kafka data set with new enhancements.

We'd prefer it if you saw us at our best.

Pega.com is not optimized for Internet Explorer. For the optimal experience, please use:

Close Deprecation Notice
Contact us