Published Release Notes

Cassandra 3.11.3 support for Pega Platform

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

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:

• Increase the accuracy of text analytics models by adding feedback data (8.3)
• Updating training data for text analytics models

Text analytics models migration

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:

• Increase the accuracy of text analytics models by adding feedback data (8.3)
• Exporting text analytics models
• Importing text analytics models

PDF/UA support

PDF documents that you generate in Pega Platform™ are now in PDF/UA format. This enhancement improves accessibility for users who rely on assistive technology, such as screen readers.

For more information, see Setting PDF file versions.

Upgrade impact

With an upgrade to Pega Platform 8.4 and later, the underlying PD4ML library in Pega Platform changes from v3.10 to v4.x. Following an upgrade, most standard HTML-CSS conversions to PDF work seamlessly; however, if you use the following custom coding in their application to convert HTML to PDF, you may find that PDF generation works differently than expected or no longer works:

• Application layer Java in activities that directly link to the underlying PD4ML library
• A Rule Utility Function
• PD4ML tags in HTML fragments

For example, the following PD4ML proprietary CSS keywords are no longer supported in v4.x:

• pd4ml-page-break-border-top
• pd4ml-page-break-border-bottom

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

After you upgrade to Pega Platform 8.4 and later and find your PDF generation works differently than expected or no longer works, you should consult the latest documentation available at pd[4]ml support site. You may also consider using the Compact CSS instead of the application skin for PDF generation; for details, see Creating PDF files by using a compact style sheet.

Personalized views in table layouts

Table layouts now provide users with the option to save preferred run-time configurations, such as column visibility and filtering, as permanent profiles. This enhancement helps users create dedicated views for specific work scenarios, which reduces the need for repetitive adjustments to the user interface and improves productivity.

For more information, see Enabling table personalization.

Upgrade impact

After an upgrade to 8.4 and later, the default table toolbar styling and experience may be unexpectedly different for any customized tables in a client's application: if you enabled a tool bar action for a personalizable table and the 8.4 application overrides your customization, your application now displays the default 8.4 table toolbar.

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

Existing clients that upgrade to Pega Platform 8.4 and later may need to update applications in some scenarios. Any custom actions present in the overridden section may need to be re-authored into this toolbar using the additional actions section.

Changes to the architecture of the Data Flow service

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
• Updates to lifecycle actions
• Starting a run
• Triggering pre- and post-activities
• Selecting a node fail policy
• No service nodes and active runs

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.

Set a time zone for the DateTime control

The DateTime control now supports the selection of a specific time zone. Apart from the default local time zone, you can choose a Java-supported time zone or enter a property. For example, you can make it easier for a manager working in New York to schedule a task for a worker in London by configuring a calendar picker on user forms to show a date and time for Europe/London.

Beginning with this release, the calendar picker defaults to the current time in the time zone that is defined in the operator record. Previously, it defaulted to the local time zone of the system.

For more information, see Specifying a time zone for a DateTime control.

Upgrade impact

After a successful upgrade, the DateTime gadget displays the time in the current operator's locale, which is defined on the operator rule form or in the browser.  

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

If you need to display the system time from which the user has logged in, and if this is not the same as the time in the user's locale (based on the browser setting), set the Locale field in the operator ID to be blank so that the browser-based setting and the displayed time are the same as the system time.