Published Release Notes

Automatic retries for the SAVE operation on records

Batch and real-time data flow runs now automatically retry the SAVE operation on records when an error occurs because of resource unavailability. This functionality ensures that the records are eventually saved if the target data set is only temporarily unavailable, for example, because of load or network issues.

You can configure the default number of retries for the entire system in a dynamic system setting. To adjust the setting to different resource allocations and operating environments, you can update that number for each data flow run.

For more information, see Changing the number of retries for SAVE operations, Creating a batch run for data flows, and Creating a real-time run for data flows.

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.

REST API for monitoring DSM services

Decision Strategy Manager (DSM) now provides a REST API that you can use to monitor DSM services without having to access Pega Platform™. By integrating your daily monitoring tools with the management REST API, you can retrieve a list of DSM nodes, check the status of these nodes, and view details of a service from all nodes in the cluster.

For more information, see Getting started with Pega API for Pega Platform.

Business logic-based routing to process cases more efficiently

Process cases more efficiently by defining business logic-based routing options to route tasks to customer service representatives (CSRs) who have a specified availability or skillset. For example, you can ensure that a task is routed to a CSR with a high level of a German language if it is your business need. You can also create custom lists of operators and work queues to filter CSRs who can receive an assignment.

For more information, see Choosing an assignee at run time in Dev Studio, Choosing an assignee at run time in App Studio, Configuring business logic-based routing APIs.

Create custom criteria for proposition filters by using the condition builder

Proposition filters now use the condition builder to define the criteria that a proposition or group of propositions must match in order to be offered to a customer. The condition builder provides a simple, flexible tool for selecting and grouping the entry criteria.

For more information, see Create custom criteria for Proposition Filter rules with the condition builder (8.3).

Task board enhancements for improved tracking of tasks

App Studio and end-user portals, such as Case Manager, now provide an enhanced task board which helps you improve collaboration on task resolution. For example, you can create a checklist within a task, and then update the checklist to inform other users about the progress of the task. Attach content to a task to ensure that all users have the information that they need, and to make tasks more meaningful. Now you can also categorize tasks, and then filter them by category, to quickly access relevant information.

For more information, see Monitoring and tracking tasks in Dev Studio, Monitoring and tracking tasks in App Studio.

Fast-track change requests for high-priority business needs

Perform urgent rule updates through fast-track change requests. The new type of change requests supports addressing high-priority business needs and deploying them immediately, without the need to disrupt an ongoing revision.

For more information, see Release urgent business rule updates through fast track change requests (8.3) and Creating application overlays.

Support for custom database tables in external Cassandra clusters

Pega Platform™ now supports a connection to external Cassandra clusters through a dedicated Database Table data set, which reduces the need for data ingestion and export. You can use custom tables that you store in your external Cassandra cluster in data flows for accessing and saving data. You can access your custom data model by mapping the model to a Pega Platform class.

For more information, see Connecting to an external Cassandra database through a Database Table data set.

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