Resumes
Resumes
Mayank Ahuja Phones & Addresses
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Fremont, CA
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San Jose, CA
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Cupertino, CA
Publications
Us Patents
Heterogeneous Auto-Scaling Big-Data Clusters In The Cloud
View pageUS Patent:
20180067783, Mar 8, 2018
Filed:
Sep 7, 2017
Appl. No.:
15/698611
Inventors:
- Santa Clara CA, US
Mayank Ahuja - Cupertino CA, US
Ajaya Agrawal - Bangalore, IN
Prakhar Jain - Bangalore, IN
Hariharan Iyer - Bangalore, IN
Mayank Ahuja - Cupertino CA, US
Ajaya Agrawal - Bangalore, IN
Prakhar Jain - Bangalore, IN
Hariharan Iyer - Bangalore, IN
International Classification:
G06F 9/50
Abstract:
The present invention is generally directed to systems and methods of provisioning and using heterogeneous clusters in a cloud-based big data system, the heterogeneous clusters made up of primary instance types and different types of instances, the method including: determining if there are composition requirements of any heterogeneous cluster, the composition requirements defining instance types permitted for use; determining if any of the permitted different types of instances are required or advantageous for use; determining an amount of different types of instances to utilize, this determination based at least in part on an instance weight; provisioning the heterogeneous cluster comprising both primary instances and permitted different types of instances.
Pure-Spot And Dynamically Rebalanced Auto-Scaling Clusters
View pageUS Patent:
20160358249, Dec 8, 2016
Filed:
Jun 7, 2016
Appl. No.:
15/176061
Inventors:
Hariharan Iyer - Bangalore, IN
Joydeep Sen Sarma - Bangalore, IN
Mayank Ahuja - Cupertino CA, US
Joydeep Sen Sarma - Bangalore, IN
Mayank Ahuja - Cupertino CA, US
International Classification:
G06Q 30/08
H04L 29/08
H04L 29/08
Abstract:
The present invention is generally directed to systems and methods of providing automatic scaling pure-spot clusters. Such dusters may be dynamically rebalanced for further costs savings. In accordance with some methods of the present invention may include a method of utilizing a cluster in a big data cloud computing environment where instances may include reserved on-demand instances for a set price and on-demand spot instances that may be bid on by a user, the method including: creating one or more stable nodes, comprising spot instances with a bid price above a price for an equivalent on-demand instance; creating one or more volatile nodes, comprising spot instances with a bid price below a price for an equivalent on-demand instance; using one or more of the stable nodes as a master node; and using the volatile nodes as slave nodes.