Event-Driven

Red Hat Process Automation Manager 7.9 brings Apache Kafka integration and more

Red Hat Process Automation Manager 7.9 brings Apache Kafka integration and more

Red Hat Process Automation Manager 7.9 brings bug fixes, performance improvements, and new features for process and case management, business and decision automation, and business optimization. This article introduces you to Process Automation Manager’s out-of-the-box integration with Apache Kafka, revamped business automation management capabilities, and support for multiple decision requirements diagrams (DRDs). I will also guide you through setting up and using the new drools-metric module for analyzing business rules performance, and I’ll briefly touch on Spring Boot integration in Process Automation Manager 7.9.

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Orchestrate event-driven, distributed services with Serverless Workflow and Kubernetes

Orchestrate event-driven, distributed services with Serverless Workflow and Kubernetes

Serverless workflows have gained renewed interest and usefulness with the rise of serverless architectures. Once seen as centralized and monolithic, they now play a key role in cloud-based event and service orchestration. Until recently, there was no vendor-neutral way to describe service orchestration, so developers were dependent on vendors and vendor implementations. We realized that we needed a common, standards-based language for describing serverless workflows.

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More for developers in the new Red Hat OpenShift 4.6 web console

More for developers in the new Red Hat OpenShift 4.6 web console

Red Hat OpenShift 4.6 streamlines developer onboarding in the OpenShift web console, but that’s not all. This article details improvements and new features in the topology view and introduces OpenShift’s new, form-based approach to creating horizontal pod autoscalers and Helm charts. I also touch on application monitoring improvements and the latest updates for Red Hat OpenShift Pipelines, Red Hat OpenShift Serverless, and the Kiali Operator in OpenShift 4.6.

Note: This article presents an overview of what’s new in OpenShift 4.6. See the video at the end of the article for a guide to accessing and using the new features in the OpenShift web console.

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Event-driven serverless applications with Camel K

Event-driven serverless applications with Camel K

DevNation Tech Talks are hosted by the Red Hat technologists who create our products. These sessions include real solutions plus code and sample projects to help you get started. In this talk, you’ll learn about event-driven serverless applications and Apache Camel K from Nicola Ferraro, Luca Burgazzoli, and Burr Sutter.

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Capture IBM Db2 data changes with Debezium Db2 connector

Capture IBM Db2 data changes with Debezium Db2 connector

This article introduces the new Debezium Db2 connector for change data capture, now available as a technical preview from Red Hat Integration. Get a quick overview of using Debezium in a Red Hat AMQ Streams Kafka cluster, then find out how to use the new Db2 connector to capture row-level changes in your Db2 database tables.

Note: Change data capture, or CDC, is a well-established software design pattern for monitoring and capturing data changes in a database. CDC captures row-level changes to database tables and passes corresponding change events to a data streaming bus. Applications can read the change-event streams and access change events in the order that they happened.

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Troubleshooting user task errors in Red Hat Process Automation Manager and Red Hat JBoss BPM Suite

Troubleshooting user task errors in Red Hat Process Automation Manager and Red Hat JBoss BPM Suite

I’ve been around Red Hat JBoss BPM Suite (jBPM) and Red Hat Process Automation Manager (RHPAM) for many years. Over that time, I’ve learned a lot about the lesser-known aspects of this business process management engine.

If you are like most people, you might believe that user tasks are trivial, and learning about their details is unnecessary. Then, one day, you will find yourself troubleshooting an error like this one:

User '[User:'admin']' was unable to execution operation 'Start' on task id 287271 due to a no 'current status' match.

Receiving one too many similar error messages led me to learn everything that I know about user tasks, and I have decided to share my experience.

User tasks are a vital part of any business process management engine, jBPM included. Their behavior is defined by the OASIS Web Services—Human Task Specification, which has been fully adopted by Business Process Model and Notation (BPMN) 2.0—the standard for business processes diagrams. The spec defines two exceptionally important things that I will discuss in this article: The user task lifecycle and task access control. Without further ado, let’s jump right in.

Note: These troubleshooting tips are applicable to Red Hat JBoss BPM Suite 6.2 and above and Red Hat Process Automation Manager 7.

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Kubernetes-native Apache Kafka with Strimzi, Debezium, and Apache Camel (Kafka Summit 2020)

Kubernetes-native Apache Kafka with Strimzi, Debezium, and Apache Camel (Kafka Summit 2020)

Apache Kafka has become the leading platform for building real-time data pipelines. Today, Kafka is heavily used for developing event-driven applications, where it lets services communicate with each other through events. Using Kubernetes for this type of workload requires adding specialized components such as Kubernetes Operators and connectors to bridge the rest of your systems and applications to the Kafka ecosystem.

In this article, we’ll look at how the open source projects Strimzi, Debezium, and Apache Camel integrate with Kafka to speed up critical areas of Kubernetes-native development.

Note: Red Hat is sponsoring the Kafka Summit 2020 virtual conference from August 24-25, 2020. See the end of this article for details.

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