IBM has announced the release of its new machine-learning, end-to-end pipeline starter kit as part of the IBM Cloud-Native Toolkit. The kit is aimed at helping developers build machine-learning applications and deploy them easily and reliably in a cloud-native environment.
IBM Cloud-Native Toolkit is an open source collection of assets that provides an environment for developing cloud-native applications for deployment within Red Hat OpenShift and Kubernetes. Assets created with the Cloud-Native Toolkit can be deployed in any cloud or hybrid cloud environment.
According to the company, these starter kits offer an excellent starting point to operationalizing and industrializing AI-powered applications and making them ready for production, using open source and Red Hat OpenShift technologies. The starter kit speeds up the development, deployment, and innovation with a set of opinionated approaches/tools.
The toolkit, created by the IBM Garage, provides a set of accelerators to apply end-to-end open source patterns including GitOps to any code pattern to enable developers, administrators, and site reliability engineers support delivering business applications through the entire software development life cycle (SDLC).