DevConf.cz 2022

Autonomous vehicles, face recognition, factory fault prediction, smart cities. These are only a small number of use cases where artificial intelligence is being used to power efficiency. However, there are important advantages on bringing computation capabilities to where data generation takes place, the network's edge: privacy, reduced latency, minimum bandwidth and cost reduction.

How are we going to combine faster computing and insights with a well-proven application management and orchestration platform that works in the cloud?

This session will demonstrate how we use cloud native solutions to run AI workloads at the edge using MicroShift.

MicroShift is a research project that is exploring how OpenShift (Red Hat's Kubernetes distribution) can be optimized for small form factor and edge computing devices. MicroShift has been designed to make frugal use of system resources, tolerate severe network constrains and provide a consistent development and management experience with standard OpenShift. In addition, MicroShift runs on various architectures (x86_64, ARM, ARM64 , RISC-V 64, PPC64LE), many of which are highly used in edge computing scenarios.

During the demo, we will show how we can easily run MicroShift on an NVIDIA Jetson board, and make use of its GPU capabilities to run an AI workload.

Don't miss this talk to see MicroShift in action!

Session chairs: Lucie Cervakova and Lenka Kulajtova