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-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?!? 😉”
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).”