NVIDIA GTC is back again and we’re thrilled to be talking all things Kubernetes with you, on April 12-16! This year too, the conference will be hosted virtually and registration is free, which means even more of us can get together to share knowledge and ideas at the #1 AI conference and workshop!
Ubuntu and Canonical will be hosting two original GTC sessions, centered around Kubernetes. Whether you’re interested in Kubernetes on workstations, to cloud(s), or the edge, we’ll be showing you how Canonical’s work around MicroK8s and micro-clouds can make Kubernetes simpler for you.
Canonical and Ubuntu’s Kubernetes sessions at GTC 2021
Simplifying Kubernetes across the clouds: MicroK8s on NVIDIA Tech Stack [SS33138]
Although Kubernetes revolutionised the software life cycle, its steep learning curve still discourages many users from adopting it. MicroK8s is a production-grade, low-touch Kubernetes that abstracts the complexity and can address use cases from workstations to clouds to the edge. We’ll highlight the details of MicroK8s’ simplicity and robustness and demonstrate the different usage scenarios, running it on NVIDIA DGX, EGX, DPU and Jetson hardware using real applications from NVIDIA marketplace.
The power of micro-clouds: a new class of compute for the edge [SS33238]
Is edge computing reversing years of cloud investment? What constitutes a strong edge strategy?
Iteration of cloud technologies has made automation simpler than ever and created the right primitives to solve all kinds of problems. The reality, however, is more distributed than cloud computing is. Devices can be anywhere, in motion, or even sent in someplace to never come back. These challenges apply to edge data centers (with NVIDIA EGX boxes) as well as smart devices (with NVIDIA Jetsons) with increasing GPU usage for low latency analytics, inferencing, and visualization, while offloading security and storage to DPUs.
With micro clouds, it becomes possible to bring cloud capabilities to the broadest range of devices at the edge, accelerating innovation and underpinning operations.
This talk will cover Canonical’s micro cloud ingredients for the edge, an opinionated open source stack, from Ubuntu to MicroK8s, that gives developers the same virtualization and containerization capabilities from cloud to edge
GPU Workloads on a Mixed Container and VM Infrastructure [S31723]
We’ll cover running a small-scale (three to 50 servers) infrastructure including GPUs and making those available to various users through either system containers or virtual machines. LXD is a simple yet powerful piece of software allowing deployments like this — it supports easy clustering, multiple independent projects, and can run both container and virtual machines, mixing them on every one of the nodes.
This, combined with its support for GPU pass-through to both containers and virtual machines, makes it possible to get the most out of your physical resources. We’ll go over what LXD is, how clustering and projects work, and what the supported options for using GPUs are, including a demonstration of such a deployment.
We hope to see you there!