Published Release Notes

Tabbed templates in portal authoring

Portal authoring in Pega Platform™ now includes tabbed templates that provide you with the tools to build complex user interfaces with less effort. The new templates help you save screen space and display the contents of your application in smaller, meaningful chunks.

For more information, see Configuring a tab-based landing page.

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.

Extend PegaUnit setup and cleanup capabilities using custom fixtures

The set up and clean up capabilities in the PegaUnit framework are now customizable through the use of custom fixtures. Custom fixtures extend the default testing functionality and allow you to define and implement specific runtime actions, such as running a specific test case during set up or sending an email after testing has completed execution. 

For more information, see Setting up and cleaning the context for a test case or test suite. 

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.

External data flow rules are removed

In previous versions of Pega Platform™, you could configure data flows to run in an external Hadoop environment. The external data flows functionality was deprecated and hidden from view in Pega Platform 8.5. The functionality has been now removed and is no longer available in Pega Platform 8.6.

For more information, see External data flow rules are deprecated.

Embedded properties in DX API v2 requests are no longer removed

In Pega Platform version 8.5, when you use the POST and PATCH v2 DX API methods with an embedded page property included in the content element of the request, the system removes all properties in the embedded page that are included in the case but are not a part of the request. Now, the merge logic has been modified to update embedded page fields sent up in the request, and keep other fields unchanged.

This feature simplifies client code and prevents data corruption.

Naming pattern changed for file data sets

File data sets are used to import from and export data to a file repository. In case of data export, prior to version 8.6.3, the first file exported had the same file name that was provided by the user in the data set, and any subsequent file exported to the repository had a unique identifier appended to it. Starting in Pega Platform version 8.6.3, each file has a unique identifier, automatically generated based on the data flow node, thread ID, and timestamp.

Upgrade impact

If your process to consume output files expects files with a specific name, it may not be able to process the resulting files correctly.

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

If you have configured the process before updating to Pega Platform version 8.6.3, but the exported files are no longer recognized by downstream processing logic after the upgrade, ensure that the downstream tool is configured to recognize the files by a pattern rather than the full name. For example, when referring to files exported to the repository, use the * character to indicate a pattern instead of using the full file name. For example, use Export*.csv to refer to the files.

Handlebars library update

Pega Platform version 8.6.4 uses the 4.7.7 version of the Handlebars template to generate client-side template files. The updated version, which is the latest available, introduces a wide variety of security fixes and new features that improve application reliability.

Tags disappear from Rich Text Editor source mode

When you use Rich Text Editor in HTML source mode, some tags disappear from the markup, which causes backward compatibility issues and data loss.

Cause

Pega Platform™ version 8.5.5 introduced the DOM Purifier security plugin. The plugin removes potentially vulnerable tags, including custom tags, from the raw HTML code in the Rich Text Editor source mode.

Workaround

You can disable the DOM Purifier plugin by adding the the window.disableDomPurifier = true markup to the userWorkForm HTML fragment rule.

Alternatively, as of Pega Platform version 8.5.6, you can add a tag to the allow list by including the window.rteCustomAllowedTags = ['myCustomTag'] snippet in the userWorkForm HTML fragment rule. 

In Pega Platform versions 8.5.6 to 8.6, the iframe tag is added to the allow list by default.

Facebook and YouTube data sets are deprecated

Pega Platform™ no longer supports the data set types in the Social category:

• Facebook data sets
• YouTube data sets

These features are deprecated and will be removed in future Pega Platform versions. Do not create any data sets using the Facebook or YouTube types.