Abstract
Effective data mining is going to be important for differentiating and succeeding in the digital economy especially with increased commoditization and reduced barrier to entry for infrastructure devices like servers, storage and networking systems. There is lot of telemetry data from manufacturing facilities and customers that can be used to drive improved supportability experience, unmatched product quality and reliability of infrastructure devices like servers and storage devices. Currently data mining of hardware, firmware and platform logs is a challenging task as the domain knowledge is complex with expertise for large multinational organization distributed across the world. With increasing complexity and data mining continuing to be a very time consuming task that requires math/statistics skills, diverse programming & machine learning skills and cross domain knowledge, it is important to look at next generation analytics solution tailored to infrastructure vendors to improve supportability, quality, reliability, performance and security. In this publication we propose a smart, automated and generic data analytics platform that enables a 24/7 data mining solution using an built in platform domain modeler, an expert system for analyzing hardware and firmware logs and a policy manager that allows user defined hypothesis to be verified round the clock based on policies and configurable triggers. This smart data analytics platform will help democratize data mining of hardware and firmware logs and help improve troubleshooting complex issues, improve supportability experience, reliability and quality and reduce warranty costs.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Shivanna, Suhas, "Automation and orchestration of hardware and firmware data mining using a smart data analytics platform", Technical Disclosure Commons, (February 22, 2018)
https://www.tdcommons.org/dpubs_series/1065