Published Release Notes

Easier customer record management in Customer Profile Designer (early preview)

The new Customer Profile Designer module of Pega Customer Decision Hub™ makes it possible for marketing analysts and strategy designers to define the associated data for each customer context directly in the Pega Customer Decision Hub portal. It is also possible to define more complex associated data structures that use a custom data flow, or define associated data of different types, such as RDBMS and Cassandra, for the same customer context.

Customer Profile Designer is available in Pega Customer Decision Hub 8.6 version as an early preview version. The functionality will be further expanded in future releases.

For more information, see Manage customer records in Customer Profile Designer (8.6).

Text predictions simplify the configuration of text analytics for conversational channels

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.

Improved indexing performance by gradual retrieval of data

Search functionality in Pega Platform™ versions from 8.4.5 to 8.6 now includes the option to improve indexing performance when reading query results from a large table in a database. For example, to load the recommended 50 records at a time, in the Pega-SearchEngine ruleset, create the indexing/distributed/fetchsize dynamic system setting, and set the value to 50.

Creating the fetchsize dynamic system setting ensures that your system does not crash while indexing classes with numerous instances.

For more information, see Creating a dynamic system setting.

Kafka data set enhancements

The Kafka data set is a high-throughput and low-latency platform for handling real-time data feeds that you can use as input for Pega Platform event strategies.

For better integration of Pega Platform with externally hosted Kafka, the following enhancements are implemented:

• Support for Kafka message keys and headers - extended values data format (JSON Data Transform, Apache Avro)
• Custom value processing
• Configuring topic names by using Application Properties
• Data-Admin-Kafka enhancements - supporting a wide range of connection properties

For more information, see Improve your Kafka data set with new enhancements.

External data flow rules are removed

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.

Data model inheritance does not depend on ruleset context

Search and Reporting Service (SRS) in Pega Platform™ 8.6 now provides an improved method of synchronizing data model by distinct users. In applications built on earlier versions of Pega Platform, some users might encounter difficulties in indexing data. Now, the data model that the system sends to SRS does not depend on access privileges. With this enhancement, each user of your application is eligible to synchronize data.

Naming pattern changed for file data sets

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.

Facebook and YouTube data sets are deprecated

Pega Platform™ no longer supports the data set types in the Social category:

• Facebook data sets
• YouTube data sets

These features are deprecated and will be removed in future Pega Platform versions. Do not create any data sets using the Facebook or YouTube types.

Tomcat log files moved to work directory

For Tomcat application server users, the default path for PRPC logs has been changed to the "work" directory for Catalina. For example:

<tomcat>\work\Catalina\localhost\prweb

This directory can be cleaned up during administration. To avoid loss of files, you can redirect logging to a different directory after installation:

1. Navigate to the <tomcat-home>\webapps\prweb\WEB-INF\classes directory.
2. Open the prlogging.xml file.
3. Locate the "appender" definitions section that contains the "@{web.tmpdir}" string
4. Update the FileNamePattern values to point to the new directory.

For more details, refer to the “Change the default path to PRPC logs” section in the Tomcat installation guide for your database.

Supported JDBC drivers

Pega 7.1.1 supports Java 6 and Java 7 SDKs only. Ensure that the JDBC driver you are using supports those versions of Java. See your database installation or upgrade documentation for additional information.

* JDBC drivers are only available from the DB2 for z/OS product. Additionally, you need db2jcc_license_cisuz.jar in the same directory as db2jcc4.jar.

** The db2jcc.jar has been deprecated and may not be supported in future releases.

*** This .jar file is required for PostgreSQL version 9.1.x.