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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.

Integrate your application with external Kafka clusters

Valid from Pega Version 8.4

Configure your application to use an external Kafka cluster for managing real-time data. By having an external Stream service provider, you can perform such maintenance tasks as an upgrade or hotfix deployment faster because external nodes do not require restarting.

For more information, see Externally managed Stream service.

Updated default dynamic system setting for requestor pools

Valid from Pega Version 8.4

Clients can now enable or disable requestor pools for processing service requests using a new dynamic system setting called EnableRequestorPools with Pega-IntegrationEngine as the owning rulest. Previously, all deployments utilized requestor pools to improve service processing response efficiency; requestor pools eliminated overhead by automatically returning a requestor to the pool after it fulfills a service request. Starting in Pega Platform 8.4, requestor pools are disabled in Client-managed cloud deployments, since these deployments use autoscaling to handle service request traffic. Enabling requestor pools in Kubernetes environments is not recommended, because they can inhibit the default autoscaling settings in the environment.

Requestor pools remain enabled by default in Pega Cloud and on-premises environments.

To help clients navigate this change, Pega has updated its best practice guidance for configuring requestor pools. For an overview, see Requestor pooling for services. For guidance on the use of requestor pools in your application, see the EnableRequestorPools entry in Dynamic system settings data instances.

Upgrade impact

Requestor pools are disabled by default in Pega Platform 8.4 in client-managed cloud deployments. Clients who deployed previous versions of Pega Platform on a Kubernetes environment and who upgrade to Pega Platform 8.4 could see that their services behave differently.

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

If clients that are deployed in a Client-managed cloud environment need to configure their services to use requestor pools and they understand how to configure requestor pools for their optimized use, these clients can re-enable requestor pools. Clients should review the best practice for configuring requestor pools before they re-enable requestor pools. To re-enable requestor pools, you modify the EnableRequestorPools setting in the Pega-IntegrationEngine Owning ruleset from “disabled” to Enabled [no value]. For details, see Editing a dynamic system setting.

Updated architecture of the data flow service

Valid from Pega Version 8.4

Benefit from improvements to data flow architecture that increase the stability of data flow runs and minimize the need for manual restarting of data flow jobs. Real-time data flows now use improved node rebalancing for better handling of failed or restarted nodes. If the topology changes, batch data flows no longer attempt to pause and resume the run. As such, there are fewer interactions with the database and between the nodes, resulting in the increased resilience of the Data Flow service.

If you are upgrading from a previous version of Pega Platform™, see Changes to the architecture of the Data Flow service for an overview of the changes to the Data Flow service compared to previous versions.

Changes to the architecture of the Data Flow service

Valid from Pega Version 8.4

In Pega Platform™ 8.4, the architecture of batch and real-time data flows uses improved node handling to increase the stability of data flow runs. As a result, there are fewer interactions with the database and between the nodes, resulting in increased resilience of the Data Flow service.

If you upgrade from a previous version of Pega Plaftorm, see the following list for an overview of the changes in the behavior of the Data Flow service compared to previous versions:

Responsiveness

Nodes no longer communicate and trigger each other, but run periodic tasks instead. As such, triggering a new run does not cause the service nodes to immediately start the run. Instead, the run starts a few seconds later. The same applies to user actions such as stopping, starting, and updating the run. The system also processes topology changes as periodic tasks, so it might take a few minutes for new nodes to join runs, or for partitions to redistribute when a node leaves a run.

Updates to lifecycle actions

To make lifecycle actions more intuitive, the Stop action consolidates both the Stop and Pause actions. The Start action consolidates both the Resume and Start actions.

You can resume or restart stopped and failed runs with the Start and Restart actions. The Start action is only available for resumable runs and continues the run from where it stopped. The Restart action causes the run to process from the beginning. Completed runs can only be restarted. If a run completes with failures, you can restart it from the beginning, or process only the errors by using the Reprocess failures action.

Starting a run

New data flow runs have the Initializing status, and start automatically. You no longer need to manually start a new run, so the New status is now removed.

If there are no nodes available to process a run, the run gets the Queued status and waits for an available node.

Triggering pre- and post-activities

The system now triggers pre-activities on a random service node, rather than on the node that triggered the run.

The system triggers post-activities only for runs that complete, fail, or complete with failures. If you manually stop a run with the Stop action, the post-activity does not trigger. However, restarting the run with the Restart action triggers first the post-activity, and then the pre-activity.

You can no longer choose to run pre- and post-activities on all nodes.

Selecting a node fail policy

For resumable runs, you can no longer select a node fail policy. If a node fails, the partitions assigned to that node automatically continue the run on different nodes.

For non-resumable runs, you can choose to restart the partitions assigned to the failed node on different nodes, or to fail the partitions assigned to the failed node.

No service nodes and active runs

If the last data flow node for an in-progress run fails, the run remains in the In Progress state, even if no processing takes place. This behavior results from the fact that data flow architecture now prevents unrelated nodes from affecting runs.

Email Wizard support discontinued

Valid from Pega Version 8.4

Pega Platform™ no longer includes the Email Wizard. This wizard helped set up an email service for sending and receiving email in Pega Platform. The wizard generated an email account, an email listener, and an email service rule.

After an upgrade to Pega Platform 8.4 and later, existing clients must create new email accounts and email channels in App Studio. When you configure a new email channel, you add your email accounts so that customers can send and receive email by using the Pega Email Bot. Configuration of an email channel automatically generates an email listener and service email rules.

For more information, see Creating an email account and Building an Email channel.

Improved indexing performance by gradual retrieval of data

Valid from Pega Version 8.4

Search functionality in Pega Platform™ versions from 8.4.5 to 8.6 now includes the option to improve indexing performance when reading query results from a large table in a database. For example, to load the recommended 50 records at a time, in the Pega-SearchEngine ruleset, create the indexing/distributed/fetchsize dynamic system setting, and set the value to 50.


Creating the fetchsize dynamic system setting ensures that your system does not crash while indexing classes with numerous instances.

For more information, see Creating a dynamic system setting.

Node description cannot match application server node name

Valid from Pega Version 6.3 SP1

A node's Short Description should not be the same value as the application server node name. If the node's Short Description is changed to be the same value as the application server node name, then the node description is automatically changed back to the original value after a system restart.

Twitter data sets no longer supported

Valid from Pega Version 7.1.9

Twitter is deprecating several APIs, which will disrupt the Twitter data set functionality. Twitter data sets will not be able to fetch any tweets or direct messages. This issue affects all applications that use Twitter data sets to connect to social (mainly Pega Customer Service applications).

This change applies to the current and earlier releases of Pega Platform™ that make use of Twitter data sets and it impacts all environments, including Pixar, VM, and Pega Labs instances.

Twitter connectors will be fully functional at a later date. For now, the best practice is to de-emphasize social media in your data sets.

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