Understanding Kubeflow
You can manage the full AI/ML life cycle with Kubeflow. It is a native Kubernetes Operations Support System (OSS) platform for developing, deploying, and managing scalable, end-to-end ML workloads in hybrid and multi-cloud settings. Kubeflow Pipelines, a Kubeflow service, aids in the automation of a complete AI/ML life cycle, allowing you to compose, orchestrate, and automate your AI/ML workloads.
It is an open source project, and the following diagram of the commits shows that it is an active and growing project. One of Kubeflow’s key goals is to make it simple for anybody to design, implement, and manage portable, scalable ML. At the time of writing, the Kubeflow GitHub project had 121,000 stars and over 2,000 forks (https://github.com/kubeflow/kubeflow/graphs/contributors):
Figure 6.12 – Contributions to the Kubeflow GitHub repo
The best thing is that you can use the Kubeflow API to design your AI/ML workflow...