Stephen Chin – Scaling DevOps to the Edge
With the proliferation of sensors and huge volume of data on edge devices, the promise of sending all of this data back to the cloud for AI/ML analytics has far exceeded the capacity of both the network bandwidth and compute resources. However, by moving the workload to edge devices that contain increasingly powerful processing capabilities, this data can be processed locally and efficiently aggregated in the cloud, solving a whole new set of analysis, monitoring, and optimization scenarios. This also necessitates a DevOps approach to distribution that can scale to millions of edge devices, provide continuous and reliable updates, and provide security for a highly distributed network. Learn how to take your DevOps skill set and apply it to a new and challenging domain that is in need of the same human and technology best practices that help global organizations distribute software securely and continuously to self-hosted and cloud environments.
