Orchestrating computing resources between different computing environments

• US 10,171,377 B2
• Filed: 04/18/2017
• Issued: 01/01/2019
• Est. Priority Date: 04/18/2017
• Status: Active Grant

• Current Assignee: Kyndryl Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Gao, Xue Feng, Shi, Hui Qing, Zhang, Qing Feng, Zhao, Zhi Feng
• Primary Examiner(s): Boutah, Alina A
• Application Number:
  US15/489,901
• Publication Number:
  US 20180302335A1
• Time in Patent Office: 623 Days
• Field of Search: 709223-224, 709226-227
• CPC Class Codes: H04L 41/12 Discovery or management of network topologies
• CPC Class Codes: H04L 41/122 of virtualised topologies, e.g. software-defined networks [SDN] or network function virtualisation [NFV]
• CPC Class Codes: H04L 41/40 using virtualisation of network functions or resources, e.g. SDN or NFV entities
• CPC Class Codes: H04L 41/5077 wherein the managed service relates to simple transport services, i.e. providing only network infrastructure
• CPC Class Codes: H04L 43/0876 Network utilisation, e.g. volume of load or congestion level
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 43/20 the monitoring system or the monitored elements being virtualised, abstracted or software-defined entities, e.g. SDN or NFV
• CPC Class Codes: H04L 47/788 Autonomous allocation of resources
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46

Abstract

An approach is provided for orchestrating computing resources between different computing environments. Data from first and second computing environments is monitored. The data specifies utilization of infrastructure, middleware, software testing tools, integrated development environments (IDEs), relationships among nodes, utilization of the nodes, and user behavior in the first and second computing environments. Based on the utilization of the infrastructure, middleware, tools, IDEs, node relationships and utilization, and user behavior, a pattern decision tree is updated. Based on the updated pattern decision tree and a user request that specifies requirements of the computing resources, an orchestration topology is generated that specifies a placement of the computing resources in the first and second computing environments. Based on the orchestration topology, computing resource(s) are automatically deployed in the first computing environment and other computing resource(s) are automatically deployed in the second computing environment.

Claims

1. A method of orchestrating computing resources between different computing environments, the method comprising the steps of:

a computer monitoring data from a first computing environment and a second computing environment, the data specifying a utilization of infrastructure of the first and second computing environments, middleware running on the first and second computing environments, software testing tools running on the first and second computing environments, integrated development environments (IDEs) running on the first and second computing environments, relationships among nodes of the first and second computing environments and utilization of the nodes, and user behavior in the first and second computing environments;

based on the utilization of the infrastructure, the middleware, the software testing tools, the IDEs, the relationships among the nodes, the utilization of the nodes, and the user behavior, the computer updating a pattern decision tree;

based on the updated pattern decision tree and a user request that specifies requirements of the computing resources, the computer generating an orchestration topology that specifies a placement of the computing resources in the first and second computing environments; and

based on the orchestration topology, the computer automatically deploying one or more computing resources included in the computing resources in the first computing environment and automatically deploying one or more other computing resources included in the computing resources in the second computing environment.

2. The method of claim 1, wherein the step of monitoring the data includes monitoring data from an infrastructure as a service (IaaS) cloud environment and monitoring other data from a container as a service (CaaS) cloud environment, wherein the step of updating the pattern decision tree is based on the monitored data from the IaaS cloud environment and the monitored other data from the CaaS cloud environment, wherein the step of deploying the one or more computing resources in the first computing environment includes deploying the one or more computing resources in the IaaS cloud environment, and wherein the step of deploying the one or more other computing resources in the second computing environment includes deploying the one or more other computing resources in the CaaS cloud environment.

3. The method of claim 1, further comprising the steps of:

the computer receiving user requirements specifying a business purpose, a central processing unit (CPU), a memory, a disk, middleware, a software testing tool, an integrated development environment, and a duration of the computing resources in the first or second computing environment; and

based on the received user requirements, the computer selecting a pattern in the pattern decision tree,

wherein the step of generating the orchestration topology is further based on the received user requirements and the selected pattern.

4. The method of claim 1, further comprising the steps of:

based on the monitored data, the computer identifying an unbalanced workload in the first or second computing environment; and

based on the identified unbalanced workload, the computer selecting a pattern in the pattern decision tree,

wherein the step of generating the orchestration topology is further based on the identified unbalanced workload and the selected pattern.

5. The method of claim 1, further comprising the step of the computer determining most common node relationship patterns in the pattern decision tree, wherein the step of generating the orchestration topology is based in part on one of the most common node relationship patterns.

6. The method of claim 1, further comprising the steps of:

the computer determining a utilization threshold amount;

the computer determining whether the utilization of the infrastructure specified by the monitored data exceeds the utilization threshold amount; and

based on the utilization of the infrastructure specified by the monitored data and based on whether the utilization of the infrastructure exceeds the utilization threshold amount, the computer determining a pattern template that specifies a pattern in the pattern decision tree,

wherein the step of updating the pattern decision tree is based in part on the utilization of the infrastructure, whether the utilization of the infrastructure exceeds the utilization threshold amount, and the pattern template.

7. The method of claim 1, further comprising the steps of:

the computer determining a key performance indicator (KPI) threshold value for the user behavior specified by the monitored data;

determining whether the user behavior specified by the monitored data exceeds the KPI threshold value; and

based in part on whether the user behavior exceeds the KPI threshold value, the computer determining a user behavior score,

wherein the step of updating the pattern decision tree is based in part on the user behavior score.

8. The method of claim 1, further comprising the step of:

providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer readable program code in the computer, the program code being executed by a processor of the computer to implement the steps of monitoring the data, updating the pattern decision tree, generating the orchestration topology, automatically deploying the one or more computing resources, and automatically deploying the one or more other computing resources.

9. A computer program product, comprising:

a computer readable storage medium and a computer readable program code stored in the computer readable storage medium, the computer readable program code containing instructions that are executed by a central processing unit (CPU) of a computer system to implement a method of orchestrating computing resources between different computing environments, the method comprising the steps of;

the computer system monitoring data from a first computing environment and a second computing environment, the data specifying a utilization of infrastructure of the first and second computing environments, middleware running on the first and second computing environments, software testing tools running on the first and second computing environments, integrated development environments (IDEs) running on the first and second computing environments, relationships among nodes of the first and second computing environments and utilization of the nodes, and user behavior in the first and second computing environments;

based on the utilization of the infrastructure, the middleware, the software testing tools, the IDEs, the relationships among the nodes, the utilization of the nodes, and the user behavior, the computer system updating a pattern decision tree;

based on the updated pattern decision tree and a user request that specifies requirements of the computing resources, the computer system generating an orchestration topology that specifies a placement of the computing resources in the first and second computing environments; and

based on the orchestration topology, the computer system automatically deploying one or more computing resources included in the computing resources in the first computing environment and automatically deploying one or more other computing resources included in the computing resources in the second computing environment.

10. The computer program product of claim 9, wherein the step of monitoring the data includes monitoring data from an infrastructure as a service (IaaS) cloud environment and monitoring other data from a container as a service (CaaS) cloud environment, wherein the step of updating the pattern decision tree is based on the monitored data from the IaaS cloud environment and the monitored other data from the CaaS cloud environment, wherein the step of deploying the one or more computing resources in the first computing environment includes deploying the one or more computing resources in the IaaS cloud environment, and wherein the step of deploying the one or more other computing resources in the second computing environment includes deploying the one or more other computing resources in the CaaS cloud environment.

11. The computer program product of claim 9, wherein the method further comprises the steps of:

the computer system receiving user requirements specifying a business purpose, a central processing unit (CPU), a memory, a disk, middleware, a software testing tool, an integrated development environment, and a duration of the computing resources in the first or second computing environment; and

based on the received user requirements, the computer system selecting a pattern in the pattern decision tree,

wherein the step of generating the orchestration topology is further based on the received user requirements and the selected pattern.

12. The computer program product of claim 9, wherein the method further comprises the steps of:

based on the monitored data, the computer system identifying an unbalanced workload in the first or second computing environment; and

based on the identified unbalanced workload, the computer system selecting a pattern in the pattern decision tree,

wherein the step of generating the orchestration topology is further based on the identified unbalanced workload and the selected pattern.

13. The computer program product of claim 9, wherein the method further comprises the step of the computer system determining most common node relationship patterns in the pattern decision tree, wherein the step of generating the orchestration topology is based in part on one of the most common node relationship patterns.

14. The computer program product of claim 9, wherein the method further comprises the steps of:

the computer system determining a utilization threshold amount;

the computer system determining whether the utilization of the infrastructure specified by the monitored data exceeds the utilization threshold amount; and

based on the utilization of the infrastructure specified by the monitored data and based on whether the utilization of the infrastructure exceeds the utilization threshold amount, the computer system determining a pattern template that specifies a pattern in the pattern decision tree,

wherein the step of updating the pattern decision tree is based in part on the utilization of the infrastructure, whether the utilization of the infrastructure exceeds the utilization threshold amount, and the pattern template.

15. The computer program product of claim 9, wherein the method further comprises the steps of:

the computer system determining a key performance indicator (KPI) threshold value for the user behavior specified by the monitored data;

determining whether the user behavior specified by the monitored data exceeds the KPI threshold value; and

based in part on whether the user behavior exceeds the KPI threshold value, the computer system determining a user behavior score,

wherein the step of updating the pattern decision tree is based in part on the user behavior score.

16. A computer system comprising:

a central processing unit (CPU);

a memory coupled to the CPU; and

a computer readable storage medium coupled to the CPU, the computer readable storage medium containing instructions that are executed by the CPU via the memory to implement a method of orchestrating computing resources between different computing environments, the method comprising the steps of;

the computer system monitoring data from a first computing environment and a second computing environment, the data specifying a utilization of infrastructure of the first and second computing environments, middleware running on the first and second computing environments, software testing tools running on the first and second computing environments, integrated development environments (IDEs) running on the first and second computing environments, relationships among nodes of the first and second computing environments and utilization of the nodes, and user behavior in the first and second computing environments;

based on the utilization of the infrastructure, the middleware, the software testing tools, the IDEs, the relationships among the nodes, the utilization of the nodes, and the user behavior, the computer system updating a pattern decision tree;

based on the updated pattern decision tree and a user request that specifies requirements of the computing resources, the computer system generating an orchestration topology that specifies a placement of the computing resources in the first and second computing environments; and

based on the orchestration topology, the computer system automatically deploying one or more computing resources included in the computing resources in the first computing environment and automatically deploying one or more other computing resources included in the computing resources in the second computing environment.

17. The computer system of claim 16, wherein the step of monitoring the data includes monitoring data from an infrastructure as a service (IaaS) cloud environment and monitoring other data from a container as a service (CaaS) cloud environment, wherein the step of updating the pattern decision tree is based on the monitored data from the IaaS cloud environment and the monitored other data from the CaaS cloud environment, wherein the step of deploying the one or more computing resources in the first computing environment includes deploying the one or more computing resources in the IaaS cloud environment, and wherein the step of deploying the one or more other computing resources in the second computing environment includes deploying the one or more other computing resources in the CaaS cloud environment.

18. The computer system of claim 16, wherein the method further comprises the steps of:

the computer system receiving user requirements specifying a business purpose, a central processing unit (CPU), a memory, a disk, middleware, a software testing tool, an integrated development environment, and a duration of the computing resources in the first or second computing environment; and

based on the received user requirements, the computer system selecting a pattern in the pattern decision tree,

wherein the step of generating the orchestration topology is further based on the received user requirements and the selected pattern.

19. The computer system of claim 16, wherein the method further comprises the steps of:

based on the monitored data, the computer system identifying an unbalanced workload in the first or second computing environment; and

based on the identified unbalanced workload, the computer system selecting a pattern in the pattern decision tree,

wherein the step of generating the orchestration topology is further based on the identified unbalanced workload and the selected pattern.

20. The computer system of claim 16, wherein the method further comprises the step of the computer system determining most common node relationship patterns in the pattern decision tree, wherein the step of generating the orchestration topology is based in part on one of the most common node relationship patterns.