Open Virtual Network (OVN) is a project born as a sub-component of Open vSwitch (OVS), which is a performant, programmable, multi-platform virtual switch. OVN allows OVS users to natively create overlay networks by introducing virtual network abstractions such as virtual switches and routers. Moreover, OVN provides methods for setting up Access Control Lists (ACLs) and network services such as DHCP. Many Red Hat products, like Red Hat OpenStack Platform, Red Hat Virtualization, and Red Hat OpenShift Container Platform, rely on OVN to configure network functionalities.
In this article, I will cover the OVN unidling issue and how the proposed solution can be used to forward events to a CMS (e.g., OpenStack or OpenShift).
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As an architect in the Red Hat Consulting team, I’ve helped countless customers with their integration challenges over the last six years. Recently, I had a few consulting gigs around Red Hat AMQ 7 Broker (the enterprise version of Apache ActiveMQ Artemis), where the requirements and outcomes were similar. That similarity made me think that the whole requirement identification process and can be more structured and repeatable.
This guide is intended for sharing what I learned from these few gigs in an attempt to make the AMQ Broker architecting process, the resulting deployment topologies, and the expected effort more predictable—at least for the common use cases. As such, what follows will be useful for messaging and integration consultants and architects tasked with creating a messaging architecture for Apache Artemis, and other messaging solutions in general. This article focuses on Apache Artemis. It doesn’t cover Apache Kafka, Strimzi, Apache Qpid, EnMasse, or the EAP messaging system, which are all components of our Red Hat AMQ 7 product offering.
Continue reading “Architecting messaging solutions with Apache ActiveMQ Artemis”
Red Hat AMQ Streams is an enterprise-grade Apache Kafka (event streaming) solution, which enables systems to exchange data at high throughput and low latency. AMQ Streams is available as part of the Red Hat AMQ offering in two different flavors: one on the Red Hat Enterprise Linux platform and another on the OpenShift Container Platform. In this three-part article series, we will cover AMQ Streams on the OpenShift Container Platform.
To get the most out of these articles, it will help to be familiar with messaging concepts, Red Hat OpenShift, and Kubernetes.
Continue reading “Understanding Red Hat AMQ Streams components for OpenShift and Kubernetes: Part 1”
Knative is not just a hot topic in software development, it’s a whole new way to look at services and functions. As a developer, what do you need to know to take advantage of this cutting-edge technology? Are there important design or implementation considerations? Let’s take a look.
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Our connected world is full of events that are triggered or received by different software services. One of the big issues is that event publishers tend to describe events differently and in ways that are mostly incompatible with each other.
To address this, the Serverless Working Group from the Cloud Native Computing Foundation (CNCF) recently announced version 0.2 of the CloudEvents specification. The specification aims to describe event data in a common, standardized way. To some degree, a CloudEvent is an abstract envelope with some specified attributes that describe a concrete event and its data.
Working with CloudEvents is simple. This article shows how to use the powerful JVM toolkit provided by Vert.x to either generate or receive and process CloudEvents.
Continue reading “Processing CloudEvents with Eclipse Vert.x”
Scalability is often a key issue for many growing organizations. That’s why many organizations use Apache Kafka, a popular messaging and streaming platform. It is horizontally scalable, cloud-native, and versatile. It can serve as a traditional publish-and-subscribe messaging system, as a streaming platform, or as a distributed state store. Companies around the world use Apache Kafka to build real-time streaming applications, streaming data pipelines, and event-driven architectures.
Continue reading Intro to Apache Kafka and Kafka Streams for Event-Driven Microservices on DevNation Live
This post is the first in a series of three related posts that describes a lightweight cloud-native distributed microservices framework we have created called EventFlow. EventFlow can be used to develop streaming applications that can process CloudEvents, which are an effort to standardize upon a data format for exchanging information about events generated by cloud platforms.
The EventFlow platform was created to specifically target the Kubernetes/OpenShift platforms, and it models event-processing applications as a connected flow or stream of components. The development of these components can be facilitated through the use of a simple SDK library, or they can be created as Docker images that can be configured using environment variables to attach to Kafka topics and process event data directly.
Continue reading “EventFlow: Event-driven microservices on OpenShift (Part 1)”
Microservices architecture (MSA) has become very popular.. However, one common problem is how to manage distributed transactions across multiple microservices. This post is going to share my experience from past projects and explain the problem and possible patterns that could solve it.
What is a distributed transaction?
When a microservice architecture decomposes a monolithic system into self-encapsulated services, it can break transactions. This means a local transaction in the monolithic system is now distributed into multiple services that will be called in a sequence.
Continue reading “Patterns for distributed transactions within a microservices architecture”
Using Apache Kafka in modern event-driven applications is pretty popular. For a better cloud-native experience with Apache Kafka, it’s highly recommended to check out Red Hat AMQ Streams, which offers an easy installation and management of an Apache Kafka cluster on Red Hat OpenShift.
This article shows how the Kafka-CDI library can handle difficult setup tasks and make creating Kafka-powered event-driven applications for MicroProfile and Jakarta EE very easy.
Continue reading “Introducing the Kafka-CDI Library”