Support for custom database tables in external Cassandra clusters
Valid from Pega Version 8.3
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.
Prediction Studio notifications
Valid from Pega Version 8.3
Prediction Studio now displays notifications when adaptive or predictive models encounter problems. For example, if the performance of a model decreases suddenly, a notification appears, which you can use to immediately investigate the cause of the problem.
For more information, see Accessing Prediction Studio notifications and Prediction Studio notification types.
REST API for monitoring DSM services
Valid from Pega Version 8.3
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.
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:
- Increase the accuracy of text analytics models by adding feedback data (8.3)
- Updating training data for text analytics models
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:
- Increase the accuracy of text analytics models by adding feedback data (8.3)
- Exporting text analytics models
- Importing text analytics models