Deploying Kubeflow everywhere: desktop, edge, and IoT devices
Kubeflow, the ML toolkit on K8s, now fits on your desktop and edge devices! ? Data science workflows on Kubernetes Kubeflow provides the cloud-native interface between Kubernetes and data science tools: libraries, frameworks, pipelines, and notebooks. > Read more about what is Kubeflow Cloud-native MLOps toolkit gets heavy To make Kubeflow the standard cloud-native tool for MLOps within the AI landscape, the open-source community has accomplished the aggregation and integration of many projects on top of Kubernetes. Unfortunately, this notable accomplishment also has a downside. Deploying Kubeflow on your laptop or edge device has become impractical. The very minimum memory necessary to deploy the full Kubeflow bundle is 12Gb of RAM. On top of that, it is Linux-based. This means that on Windows and macOS you need to allocate 12+ Gb of memory to a Linux VM. Last time I tried, my 16Gb of RAM MacBook Pro did not like the idea. Kubeflow lite to experiment on ...