CI/CD
Infographic: 10 reasons why developers should consider Podman Desktop
Podman Desktop provides a graphical interface for application developers to work seamlessly with containers and Kubernetes in a local environment.
Ephemeral OpenShift clusters in Konflux CI using the Cluster-as-a-Service operator
When it comes to testing, many of Red Hat's development teams require administrative access to an OpenShift cluster to verify their OLM Operators. In the Konflux project we set out to provide ephemeral clusters as a service to support our users.
Manage OpenShift virtual machines with GitOps
Learn how to utilize GitOps in OpenShift to manage your virtual machines (VMs).
Perform in-place Kubernetes updates with a Blue/Green Deployment
Learn how to update an application with one simple command.
Deploy to Red Hat OpenShift using Helm charts
Helm charts are a proven and useful tool for deploying several pieces of
Build container images in OpenShift using Podman as a GitLab runner
Learn how to set up a Podman container to run on OpenShift and integrate it with a GitLab runner with this tutorial.
DevOps with OpenShift Pipelines and OpenShift GitOps
Discover how Red Hat OpenShift Pipelines and OpenShift GitOps provide key components of a combined DevOps solution in this overview, and check out a video demo.
Securing the Software Supply Chain with Jenkins, TAS, and TPA: A Red Hat Approach
In this learning exercise, you will learn how to secure your Jenkins pipeline
Create a Windows golden image for OpenShift Virtualization
Learn how to use the OpenShift Virtualization Windows UEFI installer pipeline to prepare a golden image of Windows 11 in an automated, repeatable manner.
Sign and Verify Artifacts with GitHub identity provider and Red Hat Trusted Artifact Signer
In this learning exercise, we'll set up the ability to sign and verify commits
Integrate Red Hat Trusted Artifact Signer with GitHub Actions
In this learning exercise, we'll learn how to automate the signing and
Openshift Pipelines and Node.js: Part 1 - Next.js
For this post, we are going to look at creating a Next.js application and
From Podman Desktop to containers in production
Learn how to build and run containers locally using Podman Desktop, then configure an automated CI/CD pipeline that will build your container images and push them to an image registry.
A brief introduction to Apps and Stacks Container Images
This article aims to describe Apps and Stacks container images from two perspectives: user’s and developer's.
What's new in Red Hat OpenShift 4.16
Find out what new features and capabilities have been provided in Red Hat
Reproducible OpenJDK builds
The Adoptium project has achieved reproducible builds for Java versions 21 and 22 across Linux, Windows, and Mac platforms. This capability ensures an independently verifiable path from source to binary code, enhancing trust in the software and its dependencies.
Solution Pattern: MultiCloud GitOps with ODF
Demonstrate how ArgoCD with Red Hat ACM can manage different clusters and...
Solution Pattern: Instant Multi Cloud - Openshift Everywhere
Discover how to easily deploy applications on Kuberenetes cluster in Multiple...
Enhance Kubernetes deployment efficiency with Argo CD and ApplicationSet
Discover how using Argo CD with ApplicationSet and generators provides a robust and flexible solution for managing deployments in complex Kubernetes environments.
Unveiling Backstage: A developer's guide to the CNCF project
Learn about the open source Backstage project and how it empowers developers by providing a central platform to build customizable developer portals.
The Modern DevOps Lifecycle: Shifting CI/CD and Application Architectures
Download this report to learn about the state of DevOps today and where it’s headed i
Announcing image mode for Red Hat Enterprise Linux
Image mode for Red Hat Enterprise Linux is a new deployment method that takes a container-native approach to deliver the operating system as a bootc container image.
Integrated Hybrid Cloud MLOps & Application Platform
A common platform for machine learning and app development on the hybrid cloud.
AI/ML Workloads
Applications based on machine learning and deep learning, using structured and unstructured data as the fuel to drive these applications.