CI/CD

Leveraging OpenShift or Kubernetes for automated performance tests (part 3)

Leveraging OpenShift or Kubernetes for automated performance tests (part 3)

This is the third of a series of three articles based on a session I held at EMEA Red Hat Tech Exchange. In the first article, I presented the rationale and approach for leveraging Red Hat OpenShift or Kubernetes for automated performance testing, and I gave an overview of the setup. In the second article, we looked at building an observability stack. In this third part, we will see how the execution of the performance tests can be automated and related metrics gathered.

An example of what is described in this article is available in my GitHub repository.

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Leveraging OpenShift or Kubernetes for automated performance tests (part 2)

Leveraging OpenShift or Kubernetes for automated performance tests (part 2)

This is the second of a series of three articles based on a session I hold at EMEA Red Hat Tech Exchange. In the first article, I presented the rationale and approach for leveraging Red Hat OpenShift or Kubernetes for automated performance testing, and I gave an overview of the setup.

In this article, we will look at building an observability stack that, beyond the support it provides in production, can be leveraged during performance tests. This will provide insight into how the application performs under load.

An example of what is described in this article is available in my GitHub repository.

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Building Java 11 and Gradle containers for OpenShift

Building Java 11 and Gradle containers for OpenShift

How do YOU get your Java apps running in a cloud?

First you grab a cloud from the sky by, for example,  (1) Getting started with a free account on Red Hat OpenShift Online, or (2) locally on your laptop using Red Hat Container Development Kit (CDK) or upstream Minishift on Windows, macOS, and Linux, or (3) using oc cluster up (only on Linux), or (4) by obtaining a login from someone running Red Hat OpenShift on a public or on-premises cloud. Then, you download the oc CLI client tool probably for Windows (and put it on your PATH). Then you select the Copy Login Command from the menu in the upper right corner under your name in the OpenShift Console’s UI, and you use, for example, the oc status command.

Great—now you just need to containerize your Java app. You could, of course, start to write your own Dockerfile, pick an appropriate container base image (and discuss Red Hat Enterprise Linux versus CentOS versus Fedora versus Ubuntu versus Debian versus Alpine with your co-workers; and, especially if you’re in an enterprise environment, figure out how to have that supported in production), figure out appropriate JVM startup parameters for a container, add monitoring, and so.

But perhaps what you really wanted to do today is…well, just get your Java app running in a cloud!

Read on to find an easier way.

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Building .NET Core container images using S2I

Building .NET Core container images using S2I

Red Hat OpenShift implements .NET Core support via a source-to-image (S2I) builder. In this article, we’ll take a closer look at how you can use that builder directly. Using S2I, you can build .NET Core application images without having to write custom build scripts or Dockerfiles. This can be useful on your development machine or as part of a CI/CD pipeline.

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Leveraging OpenShift or Kubernetes for automated performance tests (part 1)

Leveraging OpenShift or Kubernetes for automated performance tests (part 1)

This is the first article in a series of three articles based on a session I hold at Red Hat Tech Exchange EMEA. In this first article, I present the rationale and approach for leveraging Red Hat OpenShift or Kubernetes for automated performance testing, give an overview of the setup, and discuss points that are worth considering when executing and analyzing performance tests. I will also say a few words about performance tuning.

In the second article, we will look at building an observability stack, which—beyond the support it provides in production—can be leveraged during performance tests. Open sources projects like Prometheus, Jaeger, Elasticsearch and Grafana will be used for the purpose. The third article will present the details for building an environment for performance testing and automating the execution with JMeter and Jenkins.

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Container-native integration testing

Container-native integration testing

Integration testing is still an important step in a CI/CD pipeline even when you are developing container-native applications. Integration tests tend to be very resource-intensive workloads that run for a limited time.

I wanted to explore how integration testing technologies and tools could leverage a container orchestrator (such as Red Hat OpenShift) to run faster and more-dynamic tests, while at the same time using resources more effectively.

In this post, you will learn how to build behavior-driven development (BDD) integration tests using Cucumber, Protractor, and Selenium and how to run them in OpenShift using Zalenium.

The code for the example of this article can be found on GitHub in redhat-cop/container-pipelinesh.

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July 19th DevNation Live: Container pipeline master: Continuous integration + continuous delivery with Jenkins

July 19th DevNation Live: Container pipeline master: Continuous integration + continuous delivery with Jenkins

Join us for the next online DevNation Live on Thursday, July 19th at 12pm EDT for Container pipeline master: Continuous integration + continuous delivery with Jenkins, presented by Red Hat principal technical product marketing manager for Red Hat OpenShift, Siamak Sadeghianfar.

In this session, we’ll take a detailed look into how you can build a super slick, automated continuous integration and continuous delivery (CI/CD) Jenkins pipeline that delivers your application payloads onto the enterprise Kubernetes platform, Red Hat OpenShift. You see how zero-downtime deployment patterns can be part of your release process when you are using a container platform based on Kubernetes.

Automating your build, test, and deployment processes can improve reliability and reduce the need for rollbacks. However, we’ll show you how rollbacks can be handled too.

Register now and join the live presentation at 12pm EDT, Thursday, July 19th.

Session Agenda:

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Container Testing in OpenShift with Meta Test Family

Container Testing in OpenShift with Meta Test Family

Without proper testing, we should not ship any container. We should guarantee that a given service in a container works properly. Meta Test Family (MTF) was designed for this very purpose.

Containers can be tested as “standalone” containers and as “orchestrated” containers. Let’s look at how to test containers with the Red Hat OpenShift environment. This article describes how to do that and what actions are needed.

MTF is a minimalistic library built on the existing Avocado and behave testing frameworks, assisting developers in quickly enabling test automation and requirements. MTF adds basic support and abstraction for testing various module artifact types: RPM-based, Docker images, and more. For detailed information about the framework and how to use it check out the MTF documentation.

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Inside a Red Hat Open Innovation Labs Residency (Part 3)

Inside a Red Hat Open Innovation Labs Residency (Part 3)

This article is the final in a series taking readers on a journey to peek inside life in a Red Hat Open Innovation Labs residency.

This is the top-tier experience for any customer*, exposing them to open collaboration, open technologies, and fast agile application delivery methods.

This experience often escapes organizations attempting digital transformation, so through submersion in an Open Innovation Labs residency, Red Hat shares its experience in managing, developing, and delivering solutions with communities, open technologies, and open collaboration.

Join me as I share experiences from inside a real-life residency, watching Red Hat work intimately with a customer, exposing new ways of working, leveraging open technologies using fast, agile application delivery methods and open collaboration.

In the first part, I shared what’s in a Red Hat Open Innovation Labs residency. Then in part two, I looked at what I encountered as the residency progressed towards delivery. All that’s left now is to share the delivery week, known as Demo Day.

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