2 years ago

Category: Software, Business, Data, Kubernetes, containerization, automation, artificial-intelligence

The IT industry is at an inflection point when it comes to edge computing, according to Andy Nelson, Nelson, a principal architect for cloud and the data center at Insight Enterprises, a B2B and IT solutions and services provider. Various proof-of-concept (POC) and proof-of-value (POV) projects have proven the ROI and business benefits of intelligent edge deployments that bring artificial intelligence (AI) and machine learning (ML) to edge environments, Nelson told The New Stack.

And to scale, it all needs to fit into a form factor about the size notebook and that can fit into a space-constrained area that can be environmentally unfriendly — very hot or cold, loud, dusty, that sort of thing. All of this comes together in this intelligent edge conversation as we need operational excellence like other industries have done, and we need to adapt that to the new-school technology,” Nelson said.

The goal for Insight is to create a container platform that will have Kubernetes (K3s is a slimmed-down, single-binary version of Kubernetes that could fit this environment) and everything developers need underneath it to write to a Kubernetes API and REST API, such as data protection and replication.