Self-management of data applications
First Claim
1. A method comprising:
- retrieving, by a self-management engine from a data storage device, health data indicative of a utilization of a collection of data by one or more computing devices;
identifying, by analyzing the health data, one or more errors occurring while an application utilizes the collection of data over a first period of time;
learning, by analyzing one or more log files generated while the application utilizes the collection of data over the first period of time, a new pattern in the utilization of the collection of data, the pattern associated with the occurrence of errors;
detecting, by the self-management engine, the learned pattern in a utilization of the collection of data over a second period of time;
automatically determining, by the self-management engine, a correction to be applied to the collection of data based on the detected pattern and based on one or more rules corresponding to the detected pattern;
causing, by the self-management engine, the correction to be applied to the collection of data;
transmitting, from the self-management engine to a remote computing device, an indication of the correction to be applied to the collection of data; and
in response to the transmission of the indication of the correction, receiving, at the self-management engine, an approval of the correction;
and in response to receiving the approval, causing, by the self-management engine, a deviation detection script to be stored, wherein the deviation detection script is to be executed at future times to detect the pattern;
wherein causing the correction to be applied to the collection of data is in response to receiving the approval of the correction.
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Abstract
The present embodiments relate generally to the enforcement of guidelines, standards, and best practices for software applications. According to certain aspects, a method of retrieving, by a self-management engine from a data storage device, health data indicative of a utilization of a collection of data by one or more computing devices is disclosed, including detecting, by the self-management engine, a pattern in the utilization of the collection of data based on the health data; automatically determining, by the self-management engine, a correction to be applied to the collection of data based on the detected pattern and based on one or more rules corresponding to the detected pattern; and causing, by the self-management engine, the correction to be applied to the collection of data.
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Citations
20 Claims
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1. A method comprising:
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retrieving, by a self-management engine from a data storage device, health data indicative of a utilization of a collection of data by one or more computing devices; identifying, by analyzing the health data, one or more errors occurring while an application utilizes the collection of data over a first period of time; learning, by analyzing one or more log files generated while the application utilizes the collection of data over the first period of time, a new pattern in the utilization of the collection of data, the pattern associated with the occurrence of errors; detecting, by the self-management engine, the learned pattern in a utilization of the collection of data over a second period of time; automatically determining, by the self-management engine, a correction to be applied to the collection of data based on the detected pattern and based on one or more rules corresponding to the detected pattern; causing, by the self-management engine, the correction to be applied to the collection of data; transmitting, from the self-management engine to a remote computing device, an indication of the correction to be applied to the collection of data; and in response to the transmission of the indication of the correction, receiving, at the self-management engine, an approval of the correction; and in response to receiving the approval, causing, by the self-management engine, a deviation detection script to be stored, wherein the deviation detection script is to be executed at future times to detect the pattern; wherein causing the correction to be applied to the collection of data is in response to receiving the approval of the correction. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 13)
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11. A system comprising:
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a non-transitory computer-readable medium storing instructions thereon; and one or more processors specially configured by the instructions stored on the non-transitory computer-readable medium to; receive health data indicative of a utilization of a collection of data by one or more computing devices executing one or more applications, identify, by analyzing the health data, one or more errors occurring while one of the one or more applications utilizes the collection of data over a first period of time; learn, by analyzing one or more log files generated while the application utilizes the collection of data over the first period of time, a new pattern in the utilization of the collection of data, the pattern associated with the occurrence of errors; detect the learned pattern in the utilization of the collection of data over a second period of time, automatically determine a correction to be applied to at least one of the collection of data or the one or more applications based on the detected pattern and based on one or more rules corresponding to the detected pattern, and cause the correction to be applied to the collection of data; transmit, to a remote computing device, an indication of the correction to be applied to the collection of data; and receive, in response to the transmission of the indication of the correction, an approval of the correction; cause, in response to receiving the approval, a deviation detection script to be stored, wherein the deviation detection script is to be executed at future times to detect the pattern; wherein causing the correction to be applied to the collection of data is in response to receiving the approval of the correction. - View Dependent Claims (12, 14, 15, 16, 17, 18, 19, 20)
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Specification