Published Release Notes

Addition of Data Access Tab to access control policy condition rules

You can now select associations and declarative index classes when creating access control policy condition rules. The Column source field in the policy condition can now accept properties from available associations and indexes. For ease of reference, the selected associations and indexes are available on the new Data Access tab. 

Using the new tab, you can build complex authorization models in which access restrictions for a class depend on the attributes present in the associated and indexed classes, along with the attributes in the current class. For example, a project management application can now separately maintain project lists for each operator and use that information to restrict read/write access to unique projects.

The information available on the new Data Access tab reflects rule form changes, which are similar to the existing functionality of the Report Definition in the Application Data Model. 

For more information, see Creating an access control policy condition.

Predictive models can drive predictions

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

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).

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

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.

Addition of Servlet Management

Pega Platform™ now has Servlet Management in Pega Cloud® Services, which provides a simple and secure way to make changes to Pega Platform servlet definitions.

Servlet Management provides Pega Cloud Service clients with solutions to manage servlet configurations with self-service options. This reduces the cycle time for delivering configuration changes in Pega Cloud Service installations while also improving upgrade reliability. 

For more information, see Servlet management.

Upgrade impact

Clients with no application servlet customizations will not experience an impact. If you upgrade from Pega Platform version 8.5 or earlier and, prior to the upgrade, the Pega Cloud team provided your application servlet customizations, then following the upgrade, you must manually add, remove, or modify your servlet customizations in your upgraded application using this servlet management landing page in Pega Platform.

What steps are required to update the application to be compatible with this change?

To manually move your pre-upgrade servlet customizations as appropriate or add new ones to your upgraded application using the new servlet management landing page, follow the steps in Adding a servlet.

Cosmos React-UI supports custom authentication

Pega Platform™ now supports custom authentication in applications that use Cosmos React-UI. Depending on the needs of your users and the functionality of your application, you might need to write custom authentication schemes to meet specific requirements. 

Clients that use custom authentication in their applications can now take advantage of the Cosmos React-UI.

For more information, see Securing Cosmos React-UI applications.

Integration and security tab now divided into two tabs

The Integration and Security tab is now two separate tabs on the Application Definition form: Integration and Security. While the content of these two tabs are related, they function more effectively as separate tabs. The Security tab now includes the Authentication section, so you can add existing authentication services to your Application Definition to more effectively manage the security of your application. 

For more information, see Security tab of the Application Definition.

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

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).

Text predictions simplify the configuration of text analytics for conversational channels

Enable text analytics for your conversational channels, such as email and chatbot, by configuring text predictions that manage the text models for your channels. This new type of prediction in Prediction Studio consolidates the AI for analyzing the messages in your conversational channels in one place and replaces the text analyzer rule in Dev Studio.

Through text predictions, you can efficiently configure the outcomes that you want to predict by analyzing the text in your channels:

• Topics (ticket booking, subscription cancellation, support request)
• Sentiments (positive, neutral, negative)
• Entities (people, organizations, airport codes)
• Languages

You can train and build the models that predict these outcomes through an intuitive process, and then monitor the outcomes through user-friendly charts.

For more information, see Predict customer needs and behaviors by using text predictions in your conversational channels.

Upgrade impact

Channels that you configured with text analyzers in the previous version of your system continue to work in the same manner after the upgrade to the current version. When you edit and save the configuration of an existing channel, the text analyzer rule is automatically upgraded to a text prediction. The associated text prediction is now an object where you can manage and monitor the text analytics for your channel. When you create a new channel in the upgraded system, the system automatically creates a text prediction for that channel.

What steps are required to update the application to be compatible with this change?

1. Enable the asynchronous model building and reporting in text predictions through job schedulers that use the System Runtime Context (SRC) by adding your application to the SRC.
   For more information, see Automating the runtime context management of background processes.
2. Enable model building in text predictions by configuring background processing nodes.
   For more information, see Assigning decision management node types to Pega Platform nodes.

Kafka data set enhancements

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.