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Published Release Notes

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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:

Changes to the architecture of the Data Flow service

Valid from Pega Version 8.4

In Pega Platform™ 8.4, the architecture of batch and real-time data flows uses improved node handling to increase the stability of data flow runs. As a result, there are fewer interactions with the database and between the nodes, resulting in increased resilience of the Data Flow service.

If you upgrade from a previous version of Pega Plaftorm, see the following list for an overview of the changes in the behavior of the Data Flow service compared to previous versions:

Responsiveness

Nodes no longer communicate and trigger each other, but run periodic tasks instead. As such, triggering a new run does not cause the service nodes to immediately start the run. Instead, the run starts a few seconds later. The same applies to user actions such as stopping, starting, and updating the run. The system also processes topology changes as periodic tasks, so it might take a few minutes for new nodes to join runs, or for partitions to redistribute when a node leaves a run.

Updates to lifecycle actions

To make lifecycle actions more intuitive, the Stop action consolidates both the Stop and Pause actions. The Start action consolidates both the Resume and Start actions.

You can resume or restart stopped and failed runs with the Start and Restart actions. The Start action is only available for resumable runs and continues the run from where it stopped. The Restart action causes the run to process from the beginning. Completed runs can only be restarted. If a run completes with failures, you can restart it from the beginning, or process only the errors by using the Reprocess failures action.

Starting a run

New data flow runs have the Initializing status, and start automatically. You no longer need to manually start a new run, so the New status is now removed.

If there are no nodes available to process a run, the run gets the Queued status and waits for an available node.

Triggering pre- and post-activities

The system now triggers pre-activities on a random service node, rather than on the node that triggered the run.

The system triggers post-activities only for runs that complete, fail, or complete with failures. If you manually stop a run with the Stop action, the post-activity does not trigger. However, restarting the run with the Restart action triggers first the post-activity, and then the pre-activity.

You can no longer choose to run pre- and post-activities on all nodes.

Selecting a node fail policy

For resumable runs, you can no longer select a node fail policy. If a node fails, the partitions assigned to that node automatically continue the run on different nodes.

For non-resumable runs, you can choose to restart the partitions assigned to the failed node on different nodes, or to fail the partitions assigned to the failed node.

No service nodes and active runs

If the last data flow node for an in-progress run fails, the run remains in the In Progress state, even if no processing takes place. This behavior results from the fact that data flow architecture now prevents unrelated nodes from affecting runs.

User interface distortions in the Decision Manager portal

Valid from Pega Version 7.1.6

By default, the New Application wizard in Pega 7.1.6 configures new applications to include UI-Kit-7 in the list of application rulesets. This ruleset causes user interface distortions in the Decision Manager portal. Both applications created in previous maintenance level updates and applications created in Pega 7.1.6 that do not include the UI-Kit-7 dependency are not impacted by this known issue.

Workaround:

  1. Open the application record.
  2. In Application Rulesets, remove UI-Kit-7.
  3. Save the application record.

User interface distortions in the Predictive Analytics Director portal

Valid from Pega Version 7.1.6

By default, the New Application wizard configures new applications to include UI-Kit-7 in the list of application rulesets. This ruleset causes user interface distortions in the Predictive Analytics Director portal. Applications created in maintenance level updates previous to Pega 7.1.6, and applications that do not include the UI-Kit-7 dependency, are not impacted by this known issue.

Workaround:

  1. Open the application record.
  2. In Application Rulesets, remove UI-Kit-7.
  3. Save the application record.

End of support for form-based rule forms in Pega 7.1.9

Valid from Pega Version 7.1.9

Rule forms that are configured to render as forms are no longer supported in Designer Studio or end-user applications. Form-based configurations are found on custom rule types that were created in earlier versions of Pega 7 and are characterized by pop-up windows that are rendered externally from Designer Studio.

Reconfigure Pega 7 applications that use such rule forms by using standard harnesses and sections.

  1. Open the class form.
  2. Click the Advanced tab.
  3. Select Harness from the Rule formmenu.
  4. Create a new harness and new sections that implement the logic of the custom rule, using standard user interface layouts and controls.

Migrating custom rule forms to harnesses and sections offers the following benefits:

  • User interfaces become HTML5 WC3 compatible and responsive to different screen sizes.
  • User interfaces become cross-browser compatible, rendered consistently in Google Chrome, Mozilla Firefox, Apple Safari, and recent versions of Microsoft Internet Explorer.
  • Rendering performance on modern browsers is dramatically improved.
  • User interface pop-up behavior is eliminated; all windows are rendered inside Designer Studio and end-user applications.

Context-specific documentation is not available in express mode

Valid from Pega Version 7.1.9

Help topics that are opened from express mode display content that is specific to Designer Studio.

If your system is dedicated to applications that are developed in express mode exclusively, and you do not need Designer Studio help topics, you can set the Online Help URL field on the System Settings landing page to: https://pdn.pega.com/sites/default/files/help_p7e/procomhelpmain.htm. Alternatively, you can view the contextual help system for Pega 7 Express in a separate browser tab.

Design-time limitations in express mode

Valid from Pega Version 7.1.9

Some limitations apply when you develop an enterprise application in express mode. At design time, some features are disabled or have limited options when you configure them in Designer Studio and switch to express mode. The use of these features does not restrict the run-time behavior of your application; however, you cannot change the configuration of these features unless you switch from express mode to Designer Studio.

For more information about each limitation and the recommended action to take, see the following information:

Problem with truncating Decision Data Store data set

Valid from Pega Version 7.1.9

The Truncate operation for the Decision Data Store data set may cause timeout exceptions. This problem is caused by the Apache Cassandra database that waits until compaction tasks finish before it can truncate the data set.

Recommendation:

Repeat the Truncate operation until it is successful.

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