Argo + Codefresh - Codefresh

Argo and Codefresh. A magical combination.

Codefresh is designed to work seamlessly with Argo to support GitOps workflows to Kubernetes across any cloud or on-prem environment with clear visibility into the entire release workflow. When used together, Codefresh extends the functionality of Argo in useful ways. Specifically, the Argo integration includes:

Steps for triggering Argo CD sync/deploy

Steps for triggering specific deployment workflows such as blue/green or canary

Environments views that bring useful information from Argo on the status of deployments

A dashboard that connections deployments with commits, tests, tickets, logging, and more

One-click Argo bootstrapping and installation through Codefresh

Codefresh managed Argo instances

Codefresh pipelines can be used to run builds, tests, and then trigger deployments for integration testing or release. As these deployments are running (and after they’re completed), you’ll be able to monitor their status directly from the Codefresh interface. The ultimate goal of our Argo integration is to make deployments repeatable, reliable, maintainable and recoverable.

We’re contributing to Argo

We’re in it for the long haul—Codefresh maintains staff for contributing to the Argo open source project. Follow the project on Github.

What our customers say

“Perfect balance between low- and high-level CI/CD management.”

Mathieu F

“
Perfect balance between low-level close-to-the-metal container-based pipelines and high-level super-user-friendly UI, GitOps support, pipeline debugging with breakpoints, K8s/Docker/Helm as first-class citizens, built-in secrets, a multitude of integrations, great doc and support material/videos/webinars, nice people… (well, there’s so much more, do you really want me to keep going?!? 😉
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“Codefresh solves one of the most challenging issues with running CI/CD pipelines - usability.”

Ruben H

“
Apart from a stunning and easy to use UI and packed with tons of features, we liked how Codefresh works with containerization and Kubernetes in mind. Another helpful capability was the ability to define custom steps that can be reused in numerous pipelines. That significantly simplifies building custom pipelines (especially if following GitOps like pattern).
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