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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.

 

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:

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.

Naming pattern changed for file data sets

Valid from Pega Version 8.6.3

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.

The UpdateAdaptiveModels agent causes an exception after Pega 7.2 to 7.2.1 upgrade

Valid from Pega Version 7.2.1

After the Pega 7 Platform is upgraded from version 7.2 to 7.2.1, the log files might show an error that is caused by the UpdateAdaptiveModels agent. This agent is enabled by default and is responsible for updating scoring models in the Pega 7 Platform. If you use adaptive models in your solution, you can avoid this error by configuring the Adaptive Decision Manager service. If you do not use adaptive models, disable the UpdateAdaptiveModels agent.

For more information, see Configuring the Adaptive Decision Manager service and Pega-DecisionEngine agents.

Reconfiguration of the Adaptive Decision Manager service after upgrade to Pega 7.2.1

Valid from Pega Version 7.2.1

After you upgrade the Pega 7 Platform to version 7.2.1, you need to reconfigure the Adaptive Decision Manager service. Beginning with Pega 7.2.1, the Adaptive Decision Management (ADM) service is native to the Pega 7 Platform and is supported by the Decision data node infrastructure.

For more information, see Services landing page.

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