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Published Release Notes

Find release notes for the selected Pega Version and Capability.

Browse resolved issues for Platform releases.

Support for predictive models in PMML version 4.4

Valid from Pega Version 8.5

Pega Platform™ now supports the import of predictive models in Predictive Model Markup Language (PMML) version 4.4. With this feature, you can import PMML models that use the anomaly detection algorithm.

For a list of all supported PMML models, see Supported models for import

 

Support for advanced validation of embedded and referenced data

Valid from Pega Version 8.5

To help you define validation conditions for a broader range of use case scenarios, Pega Platform™ now supports stage entry validation for embedded fields in the form of a validation matrix. You can now define validation conditions for both field groups and field group lists, and easily navigate between them. You can also select any fields and when conditions while building a condition for both field-level and stage-level validation.

For more information, see Validating field values for stage entry.

Complete email and notification approval in App Studio

Valid from Pega Version 8.5

App Studio now supports complete email approval configuration directly in the Case Designer. Email approval settings now include composing a new message or selecting a template, saving templates to a library for future reuse, and adding attachments to an email. Additionally, you can now send the approval as a push notification to mobile users. With full configuration of email approval in App Studio, you save time and create unique and personalized email messages and push notifications in a no-code, intuitive way. 

For more information, see Obtain approvals from email and push notifications from App Studio (8.5), Requesting approval by email and push notification.

Business logic routing of approval steps

Valid from Pega Version 8.5

Pega Platform™ now supports routing of approval steps by applying business logic, in both App Studio and Dev Studio. Business logic uses a set of conditions to determine the most appropriate worker to approve a case by routing the approval based on defined conditions. For example, in a loan request case, the application can route the approval step to a manager if the importance of the case is set to high. For greater accuracy, business logic can also use skill set, availability, and workload to determine the appropriate worker. With business logic routing, you increase work efficiency and speed up case resolution.

For more information, see Determine a relevant case approver by using business logic (8.5), Requesting approval from users.

Limits on active data flow runs

Valid from Pega Version 8.5

You can now configure a maximum number of concurrent active data flow runs for a node type. Set limits to ensure that you do not run out of system resources and that you have a reasonable processing throughput. If a limit is reached, the system queues subsequent runs and waits for active runs to stop or finish before queued runs can be initiated, starting with the oldest.

For more information see, Limit the number of active runs in data flow services (8.5).

Upgrade impact

If you have many data flow runs active at the same time, you might notice that some of the runs are queued and waiting to be executed.

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

You do not have to take any action. After the active runs stop or finish, the queued runs start automatically. The default limits are intended to protect your system resources, and you should not see a negative impact on the processing of data flows. However, if you want to allow a greater number of active data flow runs to be active at the same time, you can change the limits. For more information, see Limiting active data flow runs.

Support for Apache HBase 2.1 and Hadoop 3.0

Valid from Pega Version 8.5

Support for these versions extends Pega Platform™ compatibility with HBase releases to ensure that your database implementations integrate seamlessly with Pega Platform.

Pega Platform now supports:

  • Apache HBase 2.1 for the HBase data set
  • Apache Hadoop Distributed File System (HDFS) 3.0 for the HDFS data set

For more information, see Enhance your data sets with Apache HBase 2.1 and Hadoop 3.0 (8.5).

Enhancing your revision management process with Deployment Manager pipelines

Valid from Pega Version 8.5

Pega Platform 8.5 offers improved synergy between revision management and the automated deployment process provided by Pega's Deployment Manager 4.8 pipelines. Use Deployment Manager 4.8 to increase the efficiency of business-as-usual application changes and automatize the deployment of revision packages.

For more information, see Managing the business-as-usual changes.

Support for Cloud AutoML topic detection models

Valid from Pega Version 8.5

In Prediction Studio, you can now connect to topic detection models that you create in Cloud AutoML, Google's cloud-based machine learning service. You can then use the models to categorize and route messages from your customers.

For more information, see Broaden your selection of topic detection models by connecting to third-party services (8.5).

Default Create stage in a case life cycle

Valid from Pega Version 8.5

Pega Platform™ now adds a default Create stage to a case life cycle every time you create a new case type, both in App Studio and Dev Studio. The default Create stage includes a view that users interact with to provide initial data before case processing begins. Consequently, you can now easily locate the view to make any necessary changes. In the background, the Create stage makes a case type independent from the starting process, which removes relevant advanced configurations and makes application development faster.

For more information, see Capture initial data faster with the default Create stage (8.5), The Create stage.

Control group configuration for predictions

Valid from Pega Version 8.5

You can now configure a control group for your predictions in Prediction Studio. Based on the control group, Prediction Studio calculates a lift score for each prediction that you can later use to monitor the success rate of your predictions.

For more information, see Customizing predictions.

All Pega product release notes can be found on their product pages.

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