Orchestration engine blueprint aspects for hybrid cloud composition

US12003390B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-12003390-B2
Application numberUS-202117214053-A
CountryUS
Kind codeB2
Filing dateMar 26, 2021
Priority dateDec 14, 2017
Publication dateJun 4, 2024
Grant dateJun 4, 2024

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  1. Title

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  2. Abstract

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  5. First independent claim

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Abstract

Official abstract text for this publication.

Techniques that facilitate orchestration engine blueprint aspects for hybrid cloud composition are provided. In one example, a system includes a blueprint component and a hybrid cloud composition component. The blueprint component determines one or more blueprint-level aspects for a blueprint associated with a cloud-based computing platform. The one or more blueprint-level aspects are indicative of encoded information for one or more features associated with one or more computing resources for the cloud-based computing platform. The hybrid cloud composition component determines a set of resource definitions for the cloud-based computing platform based on the one or more blueprint-level aspects.

First claim

Opening claim text (preview).

What is claimed is: 1. A system, comprising: a memory that stores computer executable components; a processor that executes computer executable components stored in the memory, wherein the computer executable components comprise: a blueprint component that automatically determines one or more blueprint-level aspects for a blueprint associated with a cloud-based computing platform, wherein the one or more blueprint-level aspects are indicative of encoded information for one or more features associated with computing resources for the cloud-based computing platform; a hybrid cloud composition component that dynamically populates a set of resource definitions for the cloud-based computing platform based on the one or more blueprint-level aspects and modifies the blueprint to include the resource definitions; estimating a risk level associated with a resource of the computing resources, wherein the estimated risk level is a multidimensional vector and includes a confidence value; and a learning component that alters the resource of the computing resources from the resource to a second resource distinct from the resource and modifies the blueprint to remove the resource and include the second resource and wherein an altering the resource is based on the estimated risk level, wherein the learning component comprises an inference component that enhances the one or more blueprint-level aspects of the learning component utilizing inference based schemes to learn the one or more features associated with the computing resources. 2. The system of claim 1 , wherein the blueprint component extracts the one or more blueprint-level aspects from the blueprint, and wherein the blueprint is indicative of a machine-readable representation of the one or more computing resources, and wherein the one or more resources comprise a property value implicitly set via a reference to an input parameter to the blueprint, and wherein the inference-based schemes employ machine-learning based techniques. 3. The system of claim 1 , wherein the computer executable components further comprise: a computing resource component that modifies a previous version of the computing resources to generate the computing resources for the cloud-based computing platform, wherein the one or more resources comprises a property value explicitly set to a defined value and wherein the one or more resources are uniquely named within the blueprint. 4. The system of claim 3 , wherein the computing resource component generates the computing resources for a hybrid cloud-based computing platform, a public cloud-based computing platform, or a private cloud-based computing platform. 5. The system of claim 1 , wherein the blueprint component determines the one or more blueprint-level aspects for a resource definition portion within the blueprint based on historical data associated with a second cloud-based computing platform that is different from the cloud-based computing platform, wherein the historical data comprises previously determined performance data associated with the second cloud-based computing platform. 6. The system of claim 1 , wherein the blueprint component determines encoded data within the one or more blueprint-level aspects from a group consisting of service level agreement data, software data, deployment environment data, cost data, security data, response time data, dependency data, deadline data, description data, benchmark data, and maintainer data. 7. The system of claim 1 , wherein the blueprint component determines the one or more blueprint-level aspects based on historical data associated with the cloud-based computing platform or another cloud-based computing platform. 8. The system of claim 1 , wherein the blueprint component determines the one or more blueprint-level aspects based on previously determined performance data associated with the cloud-based computing platform or another cloud-based computing platform. 9. The system of claim 1 , wherein the hybrid cloud composition component determines the set of resource definitions to facilitate improved performance for the cloud-based computing platform. 10. The system of claim 1 , wherein the estimated risk level associated with the resource is based on reliability of the resource. 11. The system of claim 1 , wherein the learning component alters one or more parameters of one or more blueprint level aspects to monitor workload performance of the cloud-based computing platform. 12. A computer-implemented method, comprising: automatically determining, by a system operatively coupled to a processor, one or more blueprint-level aspects for a blueprint associated with a cloud-based computing platform, wherein the one or more blueprint-level aspects are indicative of encoded information for one or more features associated with computing resources for the cloud-based computing platform; dynamically populating, by the system, a set of resource definitions for the cloud-based computing platform based on the one or more blueprint-level aspects; modifying, by the system, the blueprint to include the resource definitions; estimating a risk level associated with a resource of the computing resources, wherein the estimated risk level is a multidimensional vector and includes a confidence value; altering, by the system, the resource of the computing resources from the resource to a second resource distinct from the resource and modifies the blueprint to remove the resource and include the second resource and wherein an altering the resource is based on the estimated risk level associated with the resource; and enhancing, by the system, the one or more blueprint-level aspects of the learning component utilizing inference based schemes to learn the one or more features associated with the computing resources. 13. The computer-implemented method of claim 12 , further comprising: extracting, by the system, the one or more blueprint-level aspects from the blueprint, and wherein the blueprint is indicative of a machine-readable representation of the one or more computing resources, and wherein the one or more resources comprise a property value implicitly set via a reference to an input parameter to the blueprint, and wherein the inference based schemes employ machine-learning based techniques. 14. The computer-implemented method of claim 12 , further comprising: modifying, by the system, a previous version of the computing resources to generate the computing resources for the cloud-based computing platform, wherein the one or more resources comprises a property value explicitly set to a defined value and wherein the one or more resources are uniquely named within the blueprint. 15. The computer-implemented method of claim 14 , further comprising: generating, by the system, the computing resources for a hybrid cloud-based computing platform, a public cloud-based computing platform, or a private cloud-based computing platform. 16. A computer program product facilitating an orchestration engine process, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: extract, by the processor, one or more blueprint-level aspects from a blueprint formatted with information for computing resources of a cloud-based computing platform; determine, by the processor, a set of resource definitions for the cloud-based computing platform based on the one or more blueprint-level aspects, comprising determine a resource definition of the set of resource definitions compris

Assignees

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Classifications

  • Automatic or semi-automatic definitions, e.g. definition templates · CPC title

  • Logical partitioning of resources; Management or configuration of virtualized resources (specific details on emulation or internal functioning of virtual machines G06F9/455) · CPC title

  • the condition being updates or upgrades of network functionality · CPC title

  • by keeping history of different configuration generations or by rolling back to previous configuration versions · CPC title

  • involving simulating, designing, planning or modelling of a network · CPC title

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What does patent US12003390B2 cover?
Techniques that facilitate orchestration engine blueprint aspects for hybrid cloud composition are provided. In one example, a system includes a blueprint component and a hybrid cloud composition component. The blueprint component determines one or more blueprint-level aspects for a blueprint associated with a cloud-based computing platform. The one or more blueprint-level aspects are indicativ…
Who is the assignee on this patent?
Kyndryl Inc
What technology area does this patent fall under?
Primary CPC classification H04L41/5048. Mapped technology areas include Electricity.
When was this patent published?
Publication date Tue Jun 04 2024 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 12 related publications on this page (citations in our corpus or others sharing the same primary CPC).