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Published Release Notes

Find release notes for the selected Pega Version and Capability

Browse resolved issues for Platform releases.

This documentation is for non-current versions of Pega Platform. For current release notes, go here.

End of support for Microsoft Internet Explorer 9 in Pega 7.2.1

Valid from Pega Version 7.2.1

In accordance with Microsoft’s announcement to discontinue support for Internet Explorer 9, Pega 7.2.1 will not support Internet Explorer 9. You should not upgrade to Pega 7.2.1 if you are still using Internet Explorer 9. Otherwise, upgrade to Microsoft Internet Explorer 10 or later, or use Google Chrome, Apple Safari, or Mozilla Firefox, which support certain HTML5 and CSS3 standards not supported in Internet Explorer 9.

For more information about browser support, see the Platform Support Guide or contact Pegasystems Global Customer Support.

 

 

 

Discontinued support for multithreaded requestors

Valid from Pega Version 7.2.1

Multithreaded requestors are no longer supported in the Pega 7 Platform. Multithreading was previously specified by the prconfig setting initialization/allowMultiplePRThreads. If this setting is set to true when you upgrade to Pega 7.2.1, errors occur during the quiesce process.

Child case queries can be slow after upgrade

Valid from Pega Version 7.2.1

After upgrading, performance might be slow when you run queries on child cases for work tables that existed prior to the upgrade. This issue is often indicated by PEGA0005 (query time exceeded limit) alerts that can be correlated to these queries in the logs. To resolve the issue, add a database index to each of your work tables by using a multicolumn index on the pxCoverInsKey, pxObjClass, and pyStatusWork columns.

For more information, see Performance improvements for child case queries.

The UpdateAdaptiveModels agent causes an exception after Pega 7.2 to 7.2.1 upgrade

Valid from Pega Version 7.2.1

After the Pega 7 Platform is upgraded from version 7.2 to 7.2.1, the log files might show an error that is caused by the UpdateAdaptiveModels agent. This agent is enabled by default and is responsible for updating scoring models in the Pega 7 Platform. If you use adaptive models in your solution, you can avoid this error by configuring the Adaptive Decision Manager service. If you do not use adaptive models, disable the UpdateAdaptiveModels agent.

For more information, see Configuring the Adaptive Decision Manager service and Pega-DecisionEngine agents.

Reconfiguration of the Adaptive Decision Manager service after upgrade to Pega 7.2.1

Valid from Pega Version 7.2.1

After you upgrade the Pega 7 Platform to version 7.2.1, you need to reconfigure the Adaptive Decision Manager service. Beginning with Pega 7.2.1, the Adaptive Decision Management (ADM) service is native to the Pega 7 Platform and is supported by the Decision data node infrastructure.

For more information, see Services landing page.

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.

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.

Visual Business Director data is automatically cleaned after a retention period expires

Valid from Pega Version 8.5

To avoid negative impact on system resources, such as memory and disk space, Pega Platform™ automatically cleans out collections data accumulated in Visual Business Director after the time period specified in the vbd/dataRetentionTimeout dynamic system setting.

Upgrade impact

In versions of Pega Platform earlier than 8.5, collections data was not automatically removed. From version 8.5, the data is removed after 465 days (15 months) by default.

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

If the default data retention period does not meet your requirements, you can change it by editing the vbd/dataRetentionTimeout setting.

For more information, see "Configuring the data retention period for Visual Business Director" in the Pega Customer Decision Hub 8.5 Upgrade Guide on the Pega Customer Decision Hub product page.

Uploading customer responses into adaptive models is no longer available

Valid from Pega Version 8.5

The option to train adaptive models by uploading a static list of historical interaction records has been deprecated in Pega Platform™ 8.5.

Upgrade impact

In versions of Pega Platform earlier than 8.5, it was possible to train an adaptive model by uploading historical data of customer interaction. After the upgrade to version 8.5, this option is no longer available.

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

Use data from a report definition to train adaptive models. For more information, see Training adaptive models.

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