Published Release Notes

New text analytics APIs for Intelligent Virtual Assistant

Pega Platform™ now provides text analytics APIs that separate Intelligent Virtual Assistant and text analyzers into independent modules. This solution prevents integration issues when you change your text analyzer configuration.

For more information, see Text analytics APIs.

Optimized performance of embedded decision strategies

The performance of embedded strategies has now been optimized so that these strategies take less time and fewer CPU and memory resources to complete. This enhancement increases the performance of cloud and on-premises deployments.

For more information, see About Strategy rules.

New method of aggregating real-time events

Event Strategy now uses the approximate median for calculating aggregations. Approximate median calculation replaces the existing method because it requires fewer system resources for saving or loading the event strategy state. In addition, you can now calculate aggregated values by using a new Landmark window type. The window type captures all values of specific event properties from the start of the data flow that references the event strategy.

For more information, see Adding aggregations in event strategies.

Extended language support in text analytics

Pega Platform™ text analytics now supports 9 more languages. You can build entity and topic detection models to analyze text in the Japanese, Russian, Turkish, Danish, Norwegian, Swedish, Polish, Croatian, and Czech languages. In addition, Pega Platform now includes a default small talk detection model for each of these languages.

For more information, see Language support for NLP and Out-of-the-box text analytics models.

Historical data extraction for adaptive models

Adaptive models now support the extraction of historical customer responses for offline analysis. Additionally, you can use the historical data to build a model in a machine learning service of your choice.

For more information, see Extract historical responses from adaptive models for offline analysis (8.4).

Improved reliability of Visual Business Director

Improvements to the reliability of Visual Business Director (VBD) eliminate the impact of temporary access loss to the VBD cluster. The improvements include the ability to continue writing data to a VBD dataset while the corresponding server node is unavailable, enhancements to single-case data flows that write data to VBD, and a reduction in the VBD cache size.

For more information, see Eliminate the impact of temporary access loss to the VBD cluster (8.4).

Rules can no longer access Pega internal Java packages

You can no longer create rules that access Java packages that reference internal APIs (syntax com.pega.platform.*.internal*). This change does not affect rules that access Pega public API packages.

If you encounter issues when running existing rules that reference internal Pega APIs, contact Pega Support.

Upgrade impact

After an upgrade to 8.4 and later, clients can no longer save new or modified rules that access Pega internal APIs; existing rules that reference internal APIs can still be run but cannot be modified. 

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

Following a software upgrade to 8.4 or later, clients can refactor existing rules into guardrail compliant rules. To find rules to refactor, run the validation tool from designer studio (Application > Tools > Validation) to identify what rules fail validation; failed rules that include the message "Test compilation failed : Illegal internal class reference : com.pega.internal.XYZ" can updated to reference appropriate APIs.

Strategies are now available as a condition type in proposition filters

When designing proposition filters, you can now include strategy outcomes as a condition to be evaluated. Select a strategy and specify the component that you want to use as output to include more advanced decisioning in your proposition filters.

For more information, see Enrich your Proposition Filter rules with conditions based on strategy results.

Client-server deployment of Hazelcast

Pega Platform™ now supports the client-server model for the Hazelcast service, which provides cluster communication and distributes Pega Platform features across nodes. This optional deployment model introduces independent scalability for both servers and clients in Pega Platform, improving stability for deployments that use a large number of nodes.

The Hazelcast client-server model is intended for select environments running Pega Platform 8.4 across a large number of nodes and should be deployed only when directed by Global Client Support.

Default text analytics model for detecting small talk

Enhance your web chat experience by configuring chatbots to detect small talk. Pega Platform™ provides the default model that is a topic detection model, available for English, German, Spanish, Dutch, Portuguese, Italian, and French.

For more information, see Configure your chatbot for small talk.