Open Source Summit + ELC North America 2019

What if it was possible to query your data using aggregation functions, windowing, and grouping results while the data was in motion and in-memory but on the edge side?

In Data Analysis, logging is one of the key components to collect and pre-process data, usually, a logging mechanism goes through collect, parse, filter and centralize logs to a storage backend like a database, so data processing and analysis can be performed. This usually happens after the data has been aggregated and stored, but for real-time analysis needs, process the data while is still in motion brings a lot of advantages and this kind of approach is called Stream Processing.

In this presentation, we will go further and present an extended approach called 'Stream Processing on the Edge', where data is processed on the edge service or device, in a lightweight mode empowering features like anomaly detection (in the order of milliseconds) and Machine Learning in a distributed way using pure Open Source software.