Title:	CLOUD AGNOSTIC STREAM ANALYTICS
Author(s):	Chandan Kumar
ISBN:	978-989-8533-92-0
Editors:	Ajith P. Abraham and Jörg Roth
Year:	2019
Edition:	Single
Keywords:	Bigdata, Stream Analytics, Cloud Agnostic, Sentiment Analytics
Type:	Short Paper
First Page:	209
Last Page:	213
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	As machine learning is getting more and more mainstream, increasing number of public cloud providers are providing machine learning related APIs such as Text Analytics, ANN, Auto ML (pretrained) APIs which are on one hand make life easier for many application developers, but on the other hand brings API management complexity in hybrid or multi cloud environment. The current evolution of these ML (machine learning) APIs leads to more coherent integration with the current cloud provider and makes it harder to switch between the providers. These leads to a vendor locked in situation where it becomes difficult for application to easily switch the service provider. A cloud agnostic framework has been proposed here which would allow to develop modern cloud-based data science, machine learning, AI applications using the proposed framework or similar approaches where the application provider could seamlessly switch between various cloud vendors as well as native OS level APIs painlessly and programmatically. As the subject of data science is so broad that we will focus only on one aspect of it to show case the proof of concept of the framework using sentiment analysis APIs to demonstrate stream analytics capabilities. Same approach could easily be applied on other APIs as well.
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