microservices

Low-code microservices orchestration with Syndesis

Low-code microservices orchestration with Syndesis

Recently I wrote about decoupling infrastructure code from microservices. I found that Apache Camel and Debezium provided the middleware I needed for that project, with minimal coding on my end. After my successful experiment, I wondered if it would be possible to orchestrate two or more similarly decoupled microservices into a new service–and could I do it without writing any code at all? I decided to find out.

This article is a quick dive into orchestrating microservices without writing any code. We will use Syndesis (an open source integration platform) as our orchestration platform. Note that the examples assume that you are familiar with Debezium and Kafka.

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Dynamic case management in the event-driven era

Dynamic case management in the event-driven era

Case management applications are designed to handle a complex combination of human and automated tasks. All case updates and case data are captured as a case file, which acts as a pivot for the management. This then serves as a system of record for future audits and tracking. The key characteristic of these workflows is that they are ad hoc in nature. There is no single resolution, and often, one size doesn’t fit all.

Case management does not have structured time bounds. All cases typically don’t resolve at the same time. Consider examples like client onboarding, dispute resolution, fraud investigations, etc., which, by virtue, try to provide customized solutions based on the specific use case. With the advent of more modern technological frameworks and practices like microservices and event-driven processing, the potential of case management solutions opens up even further. This article describes how you can make use of case management for dynamic workflow processing in this modern era, including components such as Red Hat OpenShift, Red Hat AMQ Streams, Red Hat Fuse, and Red Hat Process Automation Manager.

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Event-based microservices with Red Hat AMQ Streams

Event-based microservices with Red Hat AMQ Streams

As part of Red Hat’s AMQ offerings, Red Hat offers a Kafka-based event streaming solution both for traditional deployment and microservices-based deployment branded as Red Hat AMQ Streams. The Red Hat OpenShift AMQ Streams deployment option is based on Strimzi, an open source tool that makes Kafka deployment as a container on a Kubernetes platform easy because most of the deployment prerequisites are automated with the OpenShift Operator Framework.

In this article, we look at how to deploy Apache Kafka on Red Hat OpenShift 4, using reasonable sample microservice applications to showcase the endless possibility of innovation brought by OpenShift and Kafka.

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Decoupling microservices with Apache Camel and Debezium

Decoupling microservices with Apache Camel and Debezium

The rise of microservices-oriented architecture brought us new development paradigms and mantras about independent development and decoupling. In such a scenario, we have to deal with a situation where we aim for independence, but we still need to react to state changes in different enterprise domains.

I’ll use a simple and typical example in order to show what we’re talking about. Imagine the development of two independent microservices: Order and User. We designed them to expose a REST interface and to each use a separate database, as shown in Figure 1:

Diagram 1 - Order and User microservices

Figure 1: Order and User microservices.

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How Quarkus brings imperative and reactive programming together

How Quarkus brings imperative and reactive programming together

The supersonic subatomic Java singularity has expanded!

42 releases, 8 months of community participation, and 177 amazing contributors led up to the release of Quarkus 1.0.  This release is a significant milestone with a lot of cool features behind it. You can read more in the release announcement.

Building on that awesome news, we want to delve into how Quarkus unifies both imperative and reactive programming models and its reactive core. We’ll start with a brief history and then take a deep dive into what makes up this dual-faceted reactive core and how Java developers can take advantage of it.

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Autoscaling Red Hat Fuse applications with OpenShift

Autoscaling Red Hat Fuse applications with OpenShift

In this article, we demonstrate Red Hat OpenShift’s horizontal autoscaling feature with Red Hat Fuse applications. The result is a Spring Boot-based application that uses the Apache Camel component twitter-search that searches Twitter for tweets based on specific keywords. If traffic or the number of tweets increases, and this application cannot serve all requests, then the application autoscales itself by increasing the number of pods. The ability to serve all requests is monitored by tracking this application’s CPU utilization on a particular pod. Also, as soon as traffic or CPU utilization is back to normal, the number of pods is reduced to the minimum configured value.

There are two types of scaling: horizontal and vertical. Horizontal scaling is where the number of application instances or containers is increased. Vertical scaling is where system resources like CPU and memory are increased at the running application’s or container’s runtime. Horizontal scaling can be used for stateless applications, whereas vertical scaling is more suitable for stateful applications.

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Get hands-on experience with Kubernetes and Quarkus at DevNation Live in Austin

Get hands-on experience with Kubernetes and Quarkus at DevNation Live in Austin

Join us December 12, 2019 for this free, one-day, two-track event at the Hilton Austin with Red Hat experts.

The cloud is dramatically changing established development practices, and developers need expert training and hands-on experience to stay up to date.

Join Red Hat’s developer advocates (including Burr Sutter, Edson Yanaga, and Kamesth Sampath) in Austin, Texas for a day of technical sessions, conversation, and hands-on workshops focused on Kubernetes development and Java microservices. Whether you are a Java developer or work in Node.js, C#, Ruby, or Python, you will gain a strong understanding of how to use modern architecture, new patterns, and DevOps to make the most of your work in the cloud.

Register now

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How to secure microservices with Red Hat Single Sign-On, Fuse, and 3scale

How to secure microservices with Red Hat Single Sign-On, Fuse, and 3scale

In this article, we’ll cover microservice security concepts by using protocols such as OpenID Connect with the support of Red Hat Single Sign-On and 3scale. Working with a microservice-based architecture, user identity, and access control in a distributed, in-depth form must be carefully designed. Here, the integration of these tools will be detailed, step-by-step, in a realistic view.

This article exemplifies the use of tools that can securely run your businesses, avoiding using homemade solutions, and protecting your services by using an API gateway, preventing your applications from being exposed to the public network. The use of an API gateway also provides additional access control, monetization, and analytics.

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DevNation Live Bengaluru: Kubernetes serverless application architecture

DevNation Live Bengaluru: Kubernetes serverless application architecture

Our first DevNation Live regional event was held in Bengaluru, India in July. This free technology event focused on open source innovations, with sessions presented by elite Red Hat technologists.

In this session, Burr Sutter discusses serverless architectures, which have become a common approach in organizations that want to be more effective in DevOps and optimize their IT resources. This approach adds further flexibility to the next generation of microservices, and Knative helps running your microservices serverless workloads on Kubernetes/OpenShift be more agile and effective.

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