Cloud-native transformation for Cloud Foundry workloads
What is Korifi?
Korifi is an offering built by the Cloud Foundry community. It was born out of the need for internal development platforms to be built over Kubernetes. Korifi’s purpose is to deliver an inherently higher order abstraction over Kubernetes, ultimately enabling developers to focus on building applications. It is purpose-built to serve as a means to deploy applications on Kubernetes while providing automated networking, security, availability, and much more.
K8s Developer Platform
Dev Complete. Ops Ready
Korifi integrates into your DevOps toolchain with support for build, test, deploy, and monitoring stages. It includes Kubernetes-native tools such as Envoy and kpack, while also allowing teams to extend their existing CI/CD, logging, and observability tools. With Korifi, software engineering teams can establish a comprehensive Kubernetes strategy and adopt best practices across development, testing, and deployment phases.
Designed for Multi-cloud, Multi-tenant, and Polyglot Needs
Using a combination of different public cloud providers for diverse staging needs? Is your infrastructure a hybrid one? Have strict compliance requirements around on-prem servers? Running clusters on the edge? No problem! Korifi can help deploy apps to any permutation of infrastructure types. This allows app developers to deploy on any remote environments with ease.
Korifi builds upon Kubernetes Hierarchical Namespaces and uses it to mimic the robust Cloud Foundry paradigm of orgs and spaces. This also extends to the RBAC that is native to the Kubernetes clusters and combines it with that of CF. Together, the two provide a foundation for multi-tenancy that is resilient and secure.
Korifi preserves the classic Cloud Foundry experience of being able to deploy apps written in any language or framework with a single cf push command. It further enhances the app developer experience by using Paketo buildpacks to deploy apps as OCI-compatible containers. App developers no longer have to wrangle with complex YAML or dockerfiles for containerized deployments to Kubernetes.