Jenkins

Automating tests and metrics gathering for Kubernetes and OpenShift  (part 3)

Automating tests and metrics gathering for Kubernetes and OpenShift (part 3)

This is the third of a series of three articles based on a session I held at Red Hat Tech Exchange EMEA. 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 Kubernetes and OpenShift for automated performance tests (part 1)

Leveraging Kubernetes and OpenShift 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 that 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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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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The CoolStore Microservices Example: DevOps and OpenShift

The CoolStore Microservices Example: DevOps and OpenShift

An introduction to microservices through a complete example

Today I want to talk about the demo we presented @ OpenShift Container Platform Roadshow in Milan & Rome last week.

The demo was based on JBoss team’s great work available on this repo:
https://github.com/jbossdemocentral/coolstore-microservice

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The fast-moving monolith: how we sped-up delivery from every three months, to every week

Editor’s note: Raffaele Spazzoli is an Architect with Red Hat Consulting’s PaaS and DevOps Practice. This blog post reflects his experience working for Key Bank prior to joining Red Hat.

A recount of the journey from three-months, to one-week release cycle-time.

This is the journey of KeyBank, a super-regional bank, from quarterly deployments to production to weekly deployments to production. In the process we adopted all open source software migrating from WebSphere to Tomcat and adopting OpenShift as our private Linux container cloud platform. We did this in the context of the digital channel modernization project, arguably the most important project for the bank during that period of time.

The scope of the digital channel modernization project was to migrate a 15-year old Java web app that was servlet-based, developed on a homegrown MVC framework and running on Java 1.6 and WebSphere 7.x to a more modern web experience and to create a new mobile web app.

This web app had grown more expensive to maintain and to meet our SLAs. It was the quintessential monolith app. Our architectural objective was to create an API layer to separate the presentation logic (web or mobile) from the business logic — what lay ahead was an effort to completely modernize the continuous integration and deployment process.

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Microservices CI/CD Pipelines in Openshift

Microservices CI/CD Pipelines in Openshift

One of the greatest advantages of using docker containers is the fact that you can move them between environments. A promotion from Development to a Production environment, shouldn’t take more than some few seconds. This is one aspect of “Continuous Delivery”

Because Microservices Architectures are “independently replaceable and upgradeable”, they are the best scenario to show a “Deployment Pipeline”.

 

Red Hat Developers has produced a sample and free application called “Red Hat Helloworlds MSA” that demonstrates different aspects of microservices (You can read more about this application in the following post: Have your own Microservices playground). This application shows how you can independently deploy the microservices using different technologies (JAX-RS and WildFly Swarm, Spring-boot, Vert.XNodeJS, etc) and how you can use different invocation patterns to integrate them. It also uses Netflix OSS, integrated via Kubeflix, and ZipKin for tracing.

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Using Jenkins in the Red Hat CI/CD Ecosystem

Using Jenkins in the Red Hat CI/CD Ecosystem

The last 4-5 years have seen the debut of many new software products specifically targeting both infrastructure services and IT automation. The consumerization of IT has caused its architects to take a fresh look at their existing, often times monolithic apps and IT infrastructure and asking: Can we do better? How do I keep IT relevant? How do I keep track of all these VMs and data? How do I scale out my IT environment without a huge budget increase or physical buildout? How do I develop and get bits to production faster and with higher quality?

These organizations are looking to evolve their development and deployment processes to be more agile and accelerate time-to-market. They are trying to embrace things like DevOps and Continuous Deployment to do that. They are breaking monolithic apps out into microservices that can be independently updated, with a focus on speed and agility, so their apps can be more reactive to changes in their business. They are evolving from traditional virtualization to public and private cloud deployments.

There are strong parallels between the way open source communities produce great software and how IT orgs build and deliver great software and services. Red Hat, a recognized pioneer in open source, is using its deep experience in open source to build products that support microservice-oriented, DevOps-embracing, container and cloud-centric IT shops.

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