Scaling Anomaly Detection Service Using Serverless Technology

Abstract

This poster paper presents an efficient design of deploying anomaly detection service using serverless technology. Our design is motivated by the fact that the workload originating from the service calls are adhoc and reserving the infrastructure upfront is not advisable. To address this, we utilized the emerging serverless platform for executing the incoming training request. Our extensive experimental analysis demonstrate the usefulness of the proposed idea.