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Modern business logic tooling workshop, lab 4: Create a process

Modern business logic tooling workshop, lab 4: Create a process

Since starting to update the free online rules and process automation workshops that showcase how to get started using modern business logic tooling, you’ve come a long way with process automation. The updates started with moving from JBoss BPM  to Red Hat Decision Manager and from JBoss BPM Suite to Red Hat Process Automation Manager.

In previous labs, we showed how to install Red Hat Decision Manager on your laptop, how to create a new project, and how to create a domain model. This article highlights the newest lab update for Red Hat Process Automation Manager, where you learn to design a process.

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Subsecond deployment and startup of Apache Camel applications

Subsecond deployment and startup of Apache Camel applications

The integration space is in constant change. Many open source projects and closed source technologies did not withstand the tests of time and have disappeared from the middleware stacks for good. After a decade, however, Apache Camel is still here and becoming even stronger for the next decade of integration. In this article, I’ll provide some history of Camel and then describe two changes coming to Apache Camel now (and later to Red Hat Fuse) and why they are important for developers. I call these changes subsecond deployment and subsecond startup of Camel applications.

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Self-service messaging with Red Hat AMQ Online and GitOps

Self-service messaging with Red Hat AMQ Online and GitOps

This article explores the service model of Red Hat AMQ Online 1.1 and how it maps to a GitOps workflow for different teams in your organization. For more information on new features in AMQ Online 1.1, see the release notes.

AMQ Online is an operator of stateful messaging services running on Red Hat OpenShift. AMQ Online is built around the principle that the responsibility of operating the messaging service is separate from the tenants consuming it. The operations team in can manage the messaging infrastructure, while the development teams provision messaging in a self-service manner, just as if they were using a public cloud service.

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Bringing IoT to Red Hat AMQ Online

Bringing IoT to Red Hat AMQ Online

Red Hat AMQ Online 1.1 was recently announced, and I am excited about it because it contains a tech preview of our Internet of Things (IoT) support. AMQ Online is the “messaging as service solution” from Red Hat AMQ. Leveraging the work we did on Eclipse Hono allows us to integrate a scalable, cloud-native IoT personality into this general-purpose messaging layer. And the whole reason why you need an IoT messaging layer is so you can focus on connecting your cloud-side application with the millions of devices that you have out there.

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Use the Kubernetes Python client from your running Red Hat OpenShift pods

Use the Kubernetes Python client from your running Red Hat OpenShift pods

Red Hat OpenShift is part of the Cloud Native Computing Foundation (CNCF) Certified Program, ensuring portability and interoperability for your container workloads. This also allows you to use Kubernetes tools to interact with an OpenShift cluster, like kubectl, and you can rest assured that all the APIs you know and love are right there at your fingertips.

The Kubernetes Python client is another great tool for interacting with an OpenShift cluster, allowing you to perform actions on Kubernetes resources with Python code. It also has applications within a cluster. We can configure a Python application running on OpenShift to consume the OpenShift API, and list and create resources. We could then create containerized batch jobs from the running application, or a custom service monitor, for example. It sounds a bit like “OpenShift inception,” using the OpenShift API from services created using the OpenShift API.

In this article, we’ll create a Flask application running on OpenShift. This application will use the Kubernetes Python client to interact with the OpenShift API, list other pods in the project, and display them back to the user.

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Building and understanding reactive microservices using Eclipse Vert.x and distributed tracing

Building and understanding reactive microservices using Eclipse Vert.x and distributed tracing

I recently had the opportunity to speak at Red Hat Summit 2019. In my session, titled “Vert.x application development with Jaeger distributed tracing,” I discussed how scalable event-driven applications could be built with Eclipse Vert.x, a Java Virtual Machine toolkit for building reactive applications.

Thanks to many developer tools, creating these applications is no longer the most effort-consuming task in IT. Instead, we now have to understand how parts of our application function together to deliver a service, (across dev, test and production environments).  This can be difficult because, with distributed architectures, external monitoring only tells you the overall response time and the number of invocations, providing no insight into the individual operations. Additionally, log entries for a request are scattered across numerous logs. This article discusses the use of Eclipse Vert.x, distributed tracing, and Jaeger in the context of this problem.

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Looking up a hash table library for caching in the 3scale Istio adapter

Looking up a hash table library for caching in the 3scale Istio adapter

You have probably already heard about the service mesh concept and one of its leading implementations, Istio. In the 3scale engineering team at Red Hat, we are working on a component to extend the functionality of Istio (and Red Hat’s distribution, Maistra) by integrating some API Management features via the 3scale platform. In this article, I’ll describe this work and some of the decisions made along the way.

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