Microservices

Migrating applications to OpenShift, Part 1: Overview

Migrating applications to OpenShift, Part 1: Overview

I help teams migrate their applications onto Red Hat OpenShift, so I can’t help but notice patterns and considerations that arise regarding the migration process. Such operations have many domain-specific factors, but in regards to getting the applications up and running on OpenShift, there appear to be several common patterns that teams use to migrate successfully.

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Distribute your microservices data with events, CQRS, and event sourcing

Distribute your microservices data with events, CQRS, and event sourcing

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 distributing your microservices data with events, Command Query Responsibility Segregation (CQRS), and event sourcing from Edson Yanaga, Red Hat’s Director of Developer Experience.

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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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Metrics and traces correlation in Kiali

Metrics and traces correlation in Kiali

Metrics, traces, and logs might be the Three Pillars of Observability, as you’ve certainly already heard. This mantra helps us focus our mindset around observability, but it is not a religion. “There is so much more data that can help us have insight into our running systems,” said Frederic Branczyk at KubeCon last year.

These three kind of signals do have their specificities, but they also have common denominators that we can generalize. They could all appear on a virtual timeline and they all originate from a workload, so they are timed and sourced, which is a good start for enabling correlation. If there’s anything as important as knowing the signals that a system can emit, it’s knowing the relationships between those signals and being able to correlate one with another, even when they’re not strictly of the same nature. Ultimately, we can postulate that any sort of signal that is timed and sourced is a good candidate for correlation as well, even if we don’t have hard links between them.

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Use Red Hat OpenShift’s built-in OAuth server as an authentication provider in Open Liberty

Use Red Hat OpenShift’s built-in OAuth server as an authentication provider in Open Liberty

In Open Liberty 20.0.0.1, you can configure the Social Login feature to use Red Hat OpenShift’s OAuth server for authentication. In addition, there is a new MicroProfile Metric to measure CPU time, memory heap and response time. This release also offers faster application startups with Liberty annotation caching, and an updated JavaServer Face.

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Architecting messaging solutions with Apache ActiveMQ Artemis

Architecting messaging solutions with Apache ActiveMQ Artemis

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.

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Skupper.io: Let your services communicate across Kubernetes clusters

Skupper.io: Let your services communicate across Kubernetes clusters

In the past few years, the popularity and adoption of containers has skyrocketed, and the Kubernetes container orchestration platform has been largely adopted as well. With these changes, a new set of challenges has emerged when dealing with applications deployed on Kubernetes clusters in the real world. One challenge is how to deal with communication between multiple clusters that might be in different networks (even private ones), behind firewalls, and so on.

One possible solution to this problem is to use a Virtual Application Network (VAN), which is sometimes referred to as a Layer 7 network. In a nutshell, a VAN is a logical network that is deployed at the application level and introduces a new layer of addressing for fine-grained application components with no constraints on the network topology. For a much more in-depth explanation, please read this excellent article.

So, what is Skupper? In the project’s own words:

Skupper is a layer seven service interconnect. It enables secure communication across Kubernetes clusters with no VPNs or special firewall rules.

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Move your APIs into the serverless era with Camel K and Knative

Move your APIs into the serverless era with Camel K and Knative

In the past few years, developers have addressed the challenge of evolving from monolith systems to microservices architecture. These days, we hear about the adoption of serverless systems.

Like many trends in software, there’s no one clear view of how to define serverless or how this approach offers added value for our software architecture. The perfect place to start with serverless systems and discover serverless capabilities is through a use case.

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MicroProfile 3.2 is now available on Open Liberty in Red Hat Runtimes

MicroProfile 3.2 is now available on Open Liberty in Red Hat Runtimes

Open Liberty 19.0.0.12 provides support for MicroProfile 3.2, allowing users to provide their own health check procedures and monitor microservice applications easily with metrics. Additionally, updates allow trust to be established using the JDK’s default truststore or a certificate through an environment variable.

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