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Generative AI on Kubernetes

Kubernetes Bytes

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Installing NVIDIA Toolkit and Kubernetes for GPU Workloads

The journey began with setting up a system from scratch, installing Ubuntu, NVIDIA drivers, and Docker, celebrating the successful installation at 2 AM. Next, the NVIDIA container toolkit was installed to enable Docker and container D to utilize CUDA and NVIDIA drivers. Subsequently, a NVIDIA container runtime validation was done through a Docker run command. Following this, upstream Kubernetes was installed, preferring it over other flavors. Setting up a single node Kubernetes with Selium as the CNI was completed, and the NVIDIA GPU operator was installed to connect Kubernetes with the container runtime. The final step involved running an Ubuntu 2020 image as a pod in Kubernetes to verify NVIDIA SMI, creating three layers of abstraction for GPU utilization.

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