Analytics @ The Edge
Close to the consumer
Cloud IoT
Platform
Machine Learning
Serverless Computing
Cloud Based
• Elastic
• Scalable
• Secure
Figure 3 : Emerging IoT Technology Landscape
Serverless Computing
Serverless computing allows IoT providers to seamlessly scale their computing needs and provide advanced functionality without the need to invest in traditional IT operations resources and processes . Serverless computing ensures that common operations tasks like patches , upgrades and host inventory are no longer needed This frees up resources to focus on product enhancements and feature development . The smaller footprint of a serverless environment also minimizes exposure to security threats , enabling IoT vendors to share responsibility with cloud vendors and their large depth of security knowledge , monitoring ability and automated response resources .
Machine Learning
Machine learning , which happens at the cloud platform level , allows for changes in user behavior to be reflected in all analytical work and positively influences the quality of user recommendations . Machine learning provides for improved user feedback as well as improved security through better detection of anomalies .
IoT providers must constantly evaluate new and emerging technologies to connect them in the most effective ways in order to provide a unique , compelling and secure experience . Doing so judiciously will also ensure IoT users ’ privacy , security , as well as notification integrity and relevance . Serverless computing promises to lower the operational overhead for IoT vendors . Analytics @ The Edge will ensure faster , higher quality recommendations . Machine Learning technologies will both improve security and recommendations quality for IoT users .
Platform Versatility
All major public cloud vendors are deploying their own IoT platforms . Their goal is to ensure that knowledge can be shared across many different IoT ven-
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