What is Jenkins X?
Jenkins X is a CI/CD solution for modern cloud applications on Kubernetes
Jenkins X is a tool in the Continuous Integration category of a tech stack.
Jenkins X is an open source tool with 3.3K GitHub stars and 622 GitHub forks. Here’s a link to Jenkins X's open source repository on GitHub
Who uses Jenkins X?
10 companies reportedly use Jenkins X in their tech stacks, including Letgo, zetaops, and Company.
61 developers on StackShare have stated that they use Jenkins X.
Jenkins X Integrations
Ubuntu, Kubernetes, Debian, Fedora, and macOS are some of the popular tools that integrate with Jenkins X. Here's a list of all 10 tools that integrate with Jenkins X.
Why developers like Jenkins X?
Here’s a list of reasons why companies and developers use Jenkins X
Jenkins X's Features
- Automated CI and CD - Rather than having to have deep knowledge of the internals of Jenkins Pipeline, Jenkins X will default awesome pipelines for your projects that implements fully CI and CD
- Environment Promotion via GitOps - Each team gets a set of Environments. Jenkins X then automates the management of the Environments and the Promotion of new versions of Applications between Environments via GitOps
- Pull Request Preview Environments - Jenkins X automatically spins up Preview Environments for your Pull Requests so you can get fast feedback before changes are merged to master
- Feedback on Issues and Pull Requests - Jenkins X automatically comments on your Commits, Issues and Pull Requests with feedback as code is ready to be previewed, is promoted to environments or if Pull Requests are generated automatically to upgrade versions
Jenkins X Alternatives & Comparisons
What are some alternatives to Jenkins X?
See all alternatives
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OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.
GitLab offers a continuous integration service. If you add a .gitlab-ci.yml file to the root directory of your repository, and configure your GitLab project to use a Runner, then each merge request or push triggers your CI pipeline.