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.
Condition builder enhancements
Valid from Pega Version 8.5
To enhance the precision of condition builder in both App Studio and Dev Studio, the new instances include comparator helps you specify the number of field group and field group list instances to which a when rule applies. In addition, a search option that returns results on keypress helps you easily look for existing values.
For more information, see Create conditions in an enhanced condition builder (8.5), Defining conditions in the condition builder.
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).
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.
Response timeout configuration for predictions
Valid from Pega Version 8.5
You can now set a response timeout for your predictions in Prediction Studio. By setting a response timeout, you control how Prediction Studio registers customer responses that later serve as feedback data for your predictions.
For more information, see Customizing predictions.
External data flow rules are deprecated
Valid from Pega Version 8.5
External data flows are now deprecated and no longer supported. To improve your user experience with Pega Platform™, the user interface elements associated with these rules are hidden from view by default. Identifying unused features allows Pega to focus on developing and supporting the features that you need.
For more information, see Deprecated: External data flows.
Support for nested Declare Trigger rules
Valid from Pega Version 8.5
Pega Platform™ now supports nested Declare Trigger rules so that you can conveniently create correlations between actions in your case types. Declare Triggers rules invoke an action when a specified event takes place in a case type. You can now design more complex scenarios faster by nesting more Declare Trigger rules that work in the context of running another Declare Trigger rule. For example, when a case participant changes a postal code in their personal details, a Declare Trigger rule runs and a respective customer service representative (CSR) receives an email. After the CSR receives the email, a nested Declare Trigger rule runs and your application creates a document with the updated personal details and attaches it to the case.
For more information, see Develop applications faster with nested Declare Trigger rules (8.5), Declare Trigger rules.