Published Release Notes

Access Manager portal

Changes to the Access Manager simplify the process of modifying the access rights of features for an application. The changes, including creation of an Access Manager portal, make it easier for non-technical users, such as business architects, to set access rights even if they may not have a deep understanding of Pega 7's security model and class inheritance structure.​

Enhanced reliability and stability of scenario tests

Several enhancements have been made to scenario tests to increase their stability and reliability. With enhanced improvements, you can now:

• Delay the execution of a step within a scenario test to add latency to a web browser and actions on a web page. This prevents tests from failing when a dynamic web page does not load all page element at once, but the test finds page elements that are immediately rendered.
• Automatically rerun failed scenario tests, which might fail because there are temporal stability issues on the environment or because the application UI is slowly renders.
• View the run history of scenario tests so that you can analyze the history of a test over time.

For more information, see the following:

• Delay the execution of a step within a test and rerun failed scenario tests for enhanced scenario test stability (8.5)
• Changing application quality metrics
• Automatically rerunning failed scenario tests
• Creating scenario tests

Support for predictive models in PMML version 4.4

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. 

Limits on active data flow runs

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

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

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

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

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

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.

New JWT access token format: Authorized Access Token

Pega Platform™ is changing from using opaque tokens to using JSON Web (JWT) tokens and the JWT access token format: Authorized Access Token (AAT). An AAT enables a client application to validate the server for user permissions and authorizes a specific application to access specific parts of a user’s data.

The major benefits to using the JWT format are:

• The JWT is a self-contained token that has authentication information, expire time information, and other user-defined claims digitally signed.
• A single token can be used with multiple applications.
• The tokens are short-lived and can minimize damage if transport security is compromised, as the token signature is verified.
• As the token is verified with the signature, there is no need to verify against a database, thus reducing latency (usually important for Web APIs).

For more information, see Understanding authorized access tokens.