US 11,656,928 B2
Detecting datacenter mass outage with near real-time/offline using ml models
Amarpal Singh Monga, Issaquah, WA (US); Bin Chen, Redmond, WA (US); and Alex Edward Hamilton, Yarrow Point, WA (US)
Assigned to Oracle International Corporation, Redwood Shores, CA (US)
Filed by Oracle International Corporation, Redwood Shores, CA (US)
Filed on Jun. 22, 2022, as Appl. No. 17/846,537.
Application 17/846,537 is a continuation of application No. 17/338,478, filed on Jun. 3, 2021, granted, now 11,397,634.
Prior Publication US 2022/0391278 A1, Dec. 8, 2022
Int. Cl. G06F 11/00 (2006.01); G06F 11/07 (2006.01); G06F 16/23 (2019.01); G06F 11/22 (2006.01)
CPC G06F 11/0769 (2013.01) [G06F 11/0709 (2013.01); G06F 11/079 (2013.01); G06F 11/0754 (2013.01); G06F 11/2252 (2013.01); G06F 11/2257 (2013.01); G06F 16/2379 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method for deriving one or more projected sources of an outage in a datacenter, the method comprising:
obtaining a set of input data providing various parameters relating to a datacenter and a listing of devices in the data center and applications executing on the devices in the datacenter;
processing the set of input data to identify a data type and one or more associated devices relating to each portion of the set of input data;
assigning, to each portion of the set of input data, a timestamp indicating a time of obtaining each portion of the set of input data;
detecting an outage of at least one functionality of the datacenter based at least in part on the obtained set of input data;
responsive to detecting the outage, processing the set of input data using a model to derive the one or more projected sources of the outage, the model incorporating a set of rules specifying correlations between the set of input data and the devices or the applications executing on the devices as the one or more projected sources of the outage, wherein deriving the one or more projected sources of the outage comprises:
determining, based at least in part on the set of rules accessible to the model, one or more anomalous parameters within the set of input data stored in the database; and
identifying one or more potential devices and/or potential applications that corresponds to each of the determined anomalous parameters, wherein each of the identified one or more potential devices and/or potential applications are part of the one or more projected sources of the outage; and
generating an outage notification message including a user interface that comprises a) at least a portion of the identified one or more potential devices and/or potential applications, and b) a graph that represents at least a portion of the set of input data and at least a portion of the one or more anomalous parameters.