Special Offer: Get 50% off your first 2 months when you do one of the following
Personalized offer codes will be given in each session

(CLOUD 2020) Cardinality based rate limiting system for time-series data

About This Webinar

Abstract: Massive monitoring systems that require high availability and performance for both ingestion and retrieval of data are often encountered with rogue streams of data having a high cardinality. The management of such high cardinality data sets for time-series data and a performance sensitive system is challenging. The challenges primarily arise as the time-series data sets, typically needs to be loaded onto a limited memory space before results can be returned to the client. This affects the number of incoming queries that can be supported simultaneously. Too many time-series can potentially degraded read performance and thereby affect user experience. Our proposed rate-limiting system described herein seeks to address a key availability issue on a high-volume, time-series system by using a dynamic cardinality computation in combination with a central assessment service to detect and block high cardinality data streams. As a result of this technical improvement, anomalous logging behavior is detected quickly, affected tenants are notified, and hardware resources are used optimally.

Authors: Deepak K Vasthimal (eBay Inc, USA); Sudeep Kumar (eBay Inc., USA)

Email: deepujain@gmail.com, sudekumar@ebay.com

Who can view: Everyone
Webinar Price: Free
Featured Presenters
Webinar hosting presenter Services Society
Deepak Kumar Vasthimal received his Bachelors in Computer Science and Engineering from Vijayanagar Engineering College, Bellary India and Masters of Science in Software Systems from BITS Pilani, India. He is currently Senior MTS, Software Engineer at eBay Inc. San Jose, California USA. He has filed several patents, research publications in the fields of recommendation algorithms, adaptive data platforms, search algorithms, digital advertising platforms, temporal social networks, graphical user interface, payments, marketplaces, wearable hardware and system infrastructure. His current research and engineering work focus is on hosting a scalable, multi-tenant, distributed machine learning platform at eBay.

Sudeep has deep expertise in building scalable and resilient platforms capable of handling petabytes of unstructured data every day. His industry experience spans across different domains like E-commerce, Embedded systems and Telecom. Specialized technical skills include solving Big data problems, Building platforms and frameworks, Client Side programming and scalable Server side backends.
Hosted By
Services Society webinar platform hosts   (CLOUD 2020) Cardinality based rate limiting system for time-series data
Services Society's Channel