Managing Edge Computing with Serverless

Lev Radomislensky will talk about a Kubernetes-based edge solution for retail analytics based on spinning Kubernetes clusters at the edge. The solution relies on a combination of an MQTT broker such a …

Lev Radomislensky will talk about a Kubernetes-based edge solution for retail analytics based on spinning Kubernetes clusters at the edge. The solution relies on a combination of an MQTT broker such as Google IoT Core together with an edge deployed registry, database and serverless functions. In this retail solution, all edge devices are managed in the cloud, while edge computing is managed through serverless functions. Edge storage is managed with a multi model database which stores time series and machine learning models, building applications on top of Kubernetes to benefit from a cloud-native architecture. Lev will demonstrate the update of functions through the MQTT broker, managing revisions and monitoring status. He will also demo machine learning models for image recognition and predictive analytics with serverless.