Computing cluster configuration standardization
Abstract
Systems and techniques for computing cluster configuration standardization are described herein. Configuration data obtained for a plurality of computing systems may be evaluated. A first computing cluster may be identified based on first configuration data for a first set of computing systems. A second computing cluster may be identified based on second configuration data for a second set of computing systems. A score may be calculated for the second computing cluster based on an evaluation of the second configuration data using the first configuration data. The second computing cluster may be associated with the first computing cluster based on the score. A standard configuration may be selected to be applied to the first set of computing systems and the second set of computing systems using the first configuration data.
Claims
exact text as granted — not AI-modified1 . (canceled)
2 . A method for computing cluster standardization comprising:
training a configuration matching machine learning model using a machine learning algorithm by extracting features from first configuration data for a first computing system; collecting second configuration data for a second computing system, the second configuration data comprising configuration variables for an application executing on the second computing system; evaluating the second configuration data using the configuration matching machine learning model to calculate a match probability for the second computing system; upon determining that the match probability is within a threshold, assigning the first computing system and the second computing system to a first computing cluster group; and applying an application configuration standard for the application to the first computing cluster group, the application configuration standard comprises instructions to apply standard application configuration variables to the first computing system and the second computing system.
3 . The method of claim 2 , wherein collecting second configuration data comprises a configuration collector scanning the second computing system for configuration information.
4 . The method of claim 2 , wherein calculating the match probability for the second computing system is based on weights for the configuration variables for an application executing on the second computing system.
5 . The method of claim 2 , wherein a record is added to a configuration database indicating that the first computing system and the second computing system belong to the first computing cluster group and to which other clusters the first computing cluster group is related.
6 . The method of claim 2 , wherein the application configuration standard is selected from a plurality of configuration standards.
7 . The method of claim 6 , wherein instructions to apply the standard application configuration variables to the first computing system and the second computing system includes updating, for components of the application, configuration variable values for the first computing system and the second computing system.
8 . The method of claim 7 , further comprising:
before applying a second application configuration standard for the application to the first computing cluster group, determining that a second configuration variable value for a second configuration variable of a component of the application is uniform across the first computing system and the second computing system; and based on the determination, preventing the application of the second application configuration standard.
9 . The method of claim 8 , further comprising:
transmitting an exception notification to an administrator of the first computing system and the second computing system.
10 . A system for computing cluster standardization comprising:
at least one processor; and memory including instructions that, when executed by the at least one processor, cause the at least one processor to perform operations to:
train a configuration matching machine learning model using a machine learning algorithm by extracting features from first configuration data for a first computing system;
collect second configuration data for a second computing system, the second configuration data comprising configuration variables for an application executing on the second computing system;
evaluate the second configuration data using the configuration matching machine learning model to calculate a match probability for the second computing system;
upon determination that the match probability is within a threshold, assign the first computing system and the second computing system to a first computing cluster group; and
apply an application configuration standard for the application to the first computing cluster group, the application configuration standard comprises instructions to apply standard application configuration variables to the first computing system and the second computing system.
11 . The system of claim 10 , the instructions to collect second configuration data further comprising instructions to:
a configuration collector to scan the second computing system for configuration information.
12 . The system of claim 10 , wherein the calculation of the match probability for the second computing system is based on weights for the configuration variables for an application executing on the second computing system.
13 . The system of claim 10 , the memory further comprising instructions to:
add a record to a configuration database indicating that the first computing system and the second computing system belong to the first computing cluster group and to which other clusters the first computing cluster group is related.
14 . The system of claim 10 , the instructions to apply an application configuration standard further comprising instructions to:
select the application configuration standard from a plurality of configuration standards.
15 . The system of claim 14 , the instructions to apply the standard application configuration variables to the first computing system and the second computing system further comprising instructions to:
update, for components of the application, configuration variable values for the first computing system and the second computing system.
16 . The system of claim 15 , before application of a second application configuration standard for the application to the first computing cluster group further comprising instructions that cause the at least one processor to perform operations to:
determine that a second configuration variable value for a second configuration variable of a component of the application is uniform across the first computing system and the second computing system; and based on the determination, prevent the application of the second application configuration standard.
17 . At least one non-transitory machine-readable medium including instructions for computing cluster standardization that, when executed by at least one processor, cause the at least one processor to perform operations to:
train a configuration matching machine learning model using a machine learning algorithm by extracting features from first configuration data for a first computing system; collect second configuration data for a second computing system, the second configuration data comprising configuration variables for an application executing on the second computing system; evaluate the second configuration data using the configuration matching machine learning model to calculate a match probability for the second computing system; upon determination that the match probability is within a threshold, assign the first computing system and the second computing system to a first computing cluster group; and apply an application configuration standard for the application to the first computing cluster group, the application configuration standard comprises instructions to apply standard application configuration variables to the first computing system and the second computing system.
18 . The at least one non-transitory machine-readable medium of claim 17 , the instructions to collect second configuration data further comprising instructions to:
a configuration collector to scan the second computing system for configuration information.
19 . The at least one non-transitory machine-readable medium of claim 17 , wherein the calculation of the match probability for the second computing system is based on weights for the configuration variables for an application executing on the second computing system.
20 . The at least one non-transitory machine-readable medium of claim 17 , the instructions to apply an application configuration standard further comprising instructions to:
select the application configuration standard from a plurality of configuration standards.
21 . The at least one non-transitory machine-readable medium of claim 20 , the instructions to apply the standard application configuration variables to the first computing system and the second computing system further comprising instructions to:
update, for components of the application, configuration variable values for the first computing system and the second computing system.
22 . The at least one non-transitory machine-readable medium of claim 21 , before application of a second application configuration standard for the application to the first computing cluster group further comprising instructions that cause the at least one processor to perform operations to:
determine that a second configuration variable value for a second configuration variable of a component of the application is uniform across the first computing system and the second computing system; and based on the determination, prevent the application of the second application configuration standard.Join the waitlist — get patent alerts
Track US2024028922A1 — get alerts on status changes and closely related new filings.
We store only your email — no account needed. See our privacy policy.