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.

Cassandra 3.11.3 support for Pega Platform

Valid from Pega Version 8.3

Increase your system's reliability and reduce its memory footprint by upgrading the internal Cassandra database to version 3.11.3.

For on-premises Pega Platform™ users, after you upgrade to Pega 8.3, it is recommended that you manually upgrade to Cassandra 3.11.3. You can upgrade to Cassandra 3.11.3 on all operating systems except IBM AIX. If you do not want to upgrade to Cassandra 3.11.3, you can continue to use Cassandra 2.1.20, which is still supported.

For Pega Cloud Services 2.13 and later versions, Cassandra automatically upgrades to version 3.11.3 after your environment is upgraded to Pega Platform 8.3.

For information on how to manually upgrade to Cassandra 3.11.3, see the Pega Platform 8.3 Upgrade Guide for your server and database at Deploy Pega Platform.

Upgrade impact

After an on-premises Pega Platform upgrade, you still have the older version of Cassandra and must manually upgrade.

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

To upgrade Cassandra, you must create a prconfig setting or a dynamic system setting with the new Cassandra version and then do a rolling restart of all the Decision Data Store nodes to upgrade them to the latest version of Cassandra.

 

Support for the decisioning-enabled NLP text analyzer in IVAs and Email Bots

Valid from Pega Version 8.3

You can now use the new intelligent natural language processing (iNLP) text analyzer in Pega Intelligent Virtual Assistants™ (IVAs) and Pega Email Bots™. This advanced text analyzer is decisioning-enabled and empowers IVA or Email Bot for all conversational channels to provide smarter responses. The decisioning capability in the system integrates text analytics with strategies, prepositions, and interaction history, to provide the context for making better next-best-action decisions.

For more information, see Use the decisioning-enabled NLP text analyzer in IVAs and Email Bots, Defining advanced Facebook text analyzer configuration and Facebook channel behavior.

Upgrade impact

Existing channels remain with the current configuration, and their current functionality does not change. Channels created after the upgrade automatically use the new text analyzer.  

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

The new text analyzer is enabled or disabled using a new interactive API (iAPI) selection, which is selected by default for new channels. You can disable the iAPI for new channels if you want to maintain current functionality. You can also enable it for existing channels if you want to move existing channels to the new functionality.

Text analytics models editing and versioning

Valid from Pega Version 8.3

Pega Platform™ now supports editing and updating training data for text analytics models.

Pega Platform also supports the versioning of text analytics models. When you update the model, Prediction Studio creates an updated model version. You can then switch between the model versions.

Upgrade impact

In versions of Pega Platform earlier than 8.3, the training data for text models was stored in the database. In Pega Platform version 8.3 and later, the training data for text models is stored in Pega Repository. You cannot build new models without setting the repository. After the repository is set, all text models are automatically upgraded and will work normally.

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

After a successful upgrade, set the repository in Prediction Studio before building or updating any Natural Language Processing (NLP) models.  In Prediction Studio, click Settings > Text Model Data Repository.

 

For more information, see:

 

Text analytics models migration

Valid from Pega Version 8.3

Pega Platform™ now supports the exporting and importing of text analytics models. For example, you can export a model to a production system so that it can gather feedback data. You can then update the model with the collected feedback data to increase the model's accuracy.

Upgrade impact

In versions of Pega Platform earlier than 8.3, the training data for text models was stored in the database. In Pega Platform version 8.3 and later, the training data for text models is stored in Pega Repository. You cannot build new models without setting the repository. After the repository is set, all text models are automatically upgraded and will work normally.

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

After a successful upgrade, set the repository in Prediction Studio before building or updating any Natural Language Processing (NLP) models.  In Prediction Studio, click Settings > Text Model Data Repository.

 

For more information, see:

Upgraded selected third-party JAR files to support Pega Platform functionalities

Valid from Pega Version 8.6

Pega Platform™ 8.6 now provides upgraded versions of the JAR files that support various functionalities within the Platform, such as generating documents or PPTX files.

Upgrade impact

If you have custom implementations and use any classes from the upgraded JAR files directly in your code or through JAR APIs, after your upgrade to Pega Platform 8.6, your application might experience unexpected run-time behavior if the upgraded JAR version lacks any elements from the previous version. For example, custom implementations can typically include activities, functions, or non-autogenerated sections. Unexpected run-time behavior might also occur when you use a third-party library that has dependencies on the upgraded JAR files. If you use only default Pega Platform functionalities without any customizations, the JAR files continue to work correctly without any additional actions.

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

If you have any JAR customizations, ensure that you test the upgraded JAR files for compatibility and upgrade impact. The following table lists the upgraded JAR files that might impact your application:

JAR file nameUpgraded version
apache-mime4j-core0.8.3
apache-mime4j-dom0.8.3
commons-codec1.15
commons-collectionons44.4
commons:commons-math33.6.1
commons-compress1.20
commons-lang33.9
fontbox2.0.19
httpclient4.5.12
httpcore4.4.13
httpmime4.5.12
istack-commons-runtime3.0.8
jackson-annotations2.10.3
jackson-core2.10.3
jackson-databind2.10.3
jaxb-runtime2.3.2
java-libpst0.9.3
jcommaner1.78
junrar4.0.0
metadata-extractor2.13
openjson1.0.11
parso2.0.11
pdfbox2.0.19
poi4.1.2
poi-ooxml4.1.2
poi-ooxml-schemas4.1.2
poi-scratchpad4.1.2
slf4j-api1.7.28
xmlbeans3.1.0
xmpcore6.1.10

For more information, refer to the documentation of  your JAR provider.

Text predictions simplify the configuration of text analytics for conversational channels

Valid from Pega Version 8.6

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.

External data flow rules are removed

Valid from Pega Version 8.6

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.

Improved rich user interface controls in IVA for Web Chatbot

Valid from Pega Version 8.3

In Pega Intelligent Virtual Assistant™ (IVA) for Web Chatbot, you can use additional rich user interface controls, such as the time and date picker or a simple form, to help users accomplish tasks more quickly and to limit errors. IVA for Web Chat can now also display a welcome message in the chat window, for example, to inform the user about the person with whom they are chatting.

For more information, see Streamline conversations in IVA for Web Chatbot with rich user interface controls.

Upgrade impact

The new Ul controls for Web Chatbot are enabled by default upon upgrade. If you do not want the controls enabled, you must disable them.

Also, if you have changed the styles for the welcome message, you may need to make changes to the welcome message to incorporate the new areas in the bot conversation area (such as quick replies).

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

Existing channels will behave as they did previously, so you should determine whether you want to use the new UI controls. If you want to use the new Ul controls, configure the new design-time options.

If you have changed the default styles for the welcome message, review the new settings to ensure that the welcome message is configured properly. 

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