Codefresh has launched a new initiative – GitOps 2.0 – which seeks to solve limitations that have existed in GitOps and promote best practices for the future.

Codefresh’s support for the new standard includes several new tools aimed at improving the experience and speed of continuous integration and delivery (CI/CD) with GitOps, all to help companies confidently ship code faster.

The goal of GitOps 2.0 is to provide patterns and standards that improve software delivery and reliability.

GitOps has evolved around a few core principles but several issues need to be addressed: dealing with multiple environments, secrets, and most urgently, observability. Codefresh is working with the DevOps community to define those patterns and to mainstream and standardize approaches to delivering software, whether on Kubernetes or not.

According to Dan Garfield, Chief Technology Evangelist at Codefresh, the rise of microservices has led to observability difficulties.

“Questions that were difficult to answer about monolithic services can be impossible to answer after moving to large microservice stacks. This is why our first pillar of GitOps 2.0 is observability,” he said. “Today we’re releasing better tooling to not only deploy software on Kubernetes, but additional observability so you can see not only what code but also what issues are deployed.”

In addition to a detailed view that lets developers see everything related to a release and control over rollbacks, Codefresh offers larger aggregate views that make it easy to tell what’s going on across all applications. Having this visibility and control can give teams more confidence in their release processes and lead to faster, more reliable deployments.

Another important area Codefresh now supports is building logic about how and when rollouts should occur.

To address this, Codefresh has introduced different deployment steps for pipelines that can trigger Git synchronization based on pipeline logic. This allows more advanced flows such as deploy, open PRs onto other infrastructure repos, or rollouts across different clusters and segments as well as automated testing of deployed versions with rollbacks.