Automating Tiny ML Intelligent Sensors DevOPS Using Microsoft Azure
Publication Date
12-10-2020
Document Type
Conference Proceeding
Publication Title
2020 IEEE International Conference on Big Data (Big Data)
DOI
10.1109/BigData50022.2020.9377755
First Page
2375
Last Page
2384
Abstract
Microsoft Azure DevOps is a robust ,cross platform and powerful automation engine for script-based automation tools. Azure DevOPS enables to build, test, and deploy Cloud Native and/or Non-Cloud Native applications. The core principle and chief advantage that Azure DevOps provide are the availability of automation techniques such as infrastructure as code and the seamless integration of verifiable frameworks such as Machine Learning Operations (MLOps) with the DevOps automated pipelines to provision and configure the infrastructure that applications need to run.With the increase in application complexity and with the infusion of Machine Learning (ML) and Artificial Intelligence (AI) techniques as part of the software development lifecycle, the Azure DevOps is the most important framework that many organizations are rapidly progressing to incorporate it in their business processes to reduce the cost of building product and improve customer success.As part of the paper, we would like to propose a novel DevOps framework for building intelligent Tiny ML dairy agriculture sensors and the advantages that DevOps provide to develop high quality product in the most cost-efficient manner and serve small scale farmers who are at the bottom economic pyramid.
Keywords
Azure, CI/CD, DevOps, Infrastructure as code
Department
Computer Engineering
Recommended Citation
Chandrasekar Vuppalapati, Anitha Ilapakurti, Karthik Chillara, Sharat Kedari, and Vanaja Mamidi. "Automating Tiny ML Intelligent Sensors DevOPS Using Microsoft Azure" 2020 IEEE International Conference on Big Data (Big Data) (2020): 2375-2384. https://doi.org/10.1109/BigData50022.2020.9377755
