System and method for automatically scaling virtual machine vertically using a forecast system within the computing environment
A feature capacity scaling methodology is disclosed. In a computer-implemented method, components of a computing environment are automatically monitored, and have a feature capacity analysis using a forecast performed thereon. Provided the feature capacity analysis determines that features of the components are well utilized, a vertical scaling of the features is performed.
1. A computer-implemented method for automated analysis of features in a computing environment, said method comprising:
automatically monitoring components of said computing environment;
automatically performing a feature capacity utilization analysis of said components of said computing environment; and
provided said feature selection analysis determines that features of said components of said computing environment meet a predefined threshold, performing a resource capacity adjustment while said resource is in operating mode in said computing environment, wherein said computer-implemented method for said automated analysis of said features in said computing environment further comprises:
automatically providing a vertical scaling virtual central processing units (vCPU) to handle resource capacity usage of said components of said computing environment and
wherein said computer-implemented method for said automated analysis of said features in said computing environment does not require an information technology (IT) administrator to manually register the presence or indicate the importance of virtual machines existing in said computing environment.
2. The computer-implemented method of claim 1 wherein said performing a feature capacity utilization analysis of said components of said computing environment further comprises:
performing a vertical scaling of said resource components of said computing environment.
3. The computer-implemented method of claim 1 wherein said performing a feature capacity utilization analysis of said components of said computing environment further comprises:
calculating a maximum capacity threshold value of said components of said computing environment.
4. The computer-implemented method of claim 1 wherein said performing a feature capacity utilization analysis of said components of said computing environment further comprises:
calculating a minimum capacity threshold value of said components of said computing environment.
5. The computer-implemented method of claim 2 wherein said performing automatic vertical scaling of said features of said components of said computing environment based on predefined resource utilization thresholds of said components of said computing environment.
6. The computer-implemented method of claim 5 wherein said performing a vertical scaling of said features of said resources of said computing environment comprises:
automatically configuring said resource while said resource is in operating mode in said computing environment.
7. The computer-implemented method of claim 6 wherein said performing a vertical scaling of said resource further comprises:
automatically monitoring performance metrics of said resource to forecast future capacity requirements of said resource of said computing environment.
8. The computer-implemented method of claim 6 wherein said performing a vertical scaling of a resource further comprises:
Setting a scaling policy for guiding capacity utilization analysis of said resource of said computing environment.
9. The computer-implemented method of claim 8 wherein said scaling policy set upper and lower utilization threshold limits for said resource in order to determine when capacity availability of said resource must be increased or decreased.
10. The computer-implemented method of claim 1 further comprising:
periodically repeating said automated analysis of said features in said computing environment to generate updated results of said automated analysis of said features of said components of said computing environment.
11. The computer-implemented method of claim 10 further comprising:
providing said updated results of said automated analysis of said features of said components of said computing environment to a forecasting system.
12. The computer-implemented method of claim 1 further comprising:
automatically providing said results for said automated analysis of said features of said components of said computing environment without requiring intervention by a system administrator.
13. A computer-implemented method for automated dynamic analysis of features in a computing environment, said method comprising:
automatically monitoring components of said computing environment;
automatically performing a feature capacity analysis of said components of said computing environment, said feature capacity analysis selected from the group comprising available resource capacity utilization; and
dynamically adjusting said resource capacity while said resource is in an operating mode in said computing environment;
and
providing results of said method for automated vertical scaling analysis of said features of said components of said computing environment, wherein said computer-implemented method for said automated dynamic analysis of said features in said computing environment further comprises:
automatically providing a vertical scaling virtual central processing units (vCPU) to handle resource capacity usage of said components of said computing environment; and
wherein said computer-implemented method for said automated dynamic analysis of said features in said computing environment does not require an information technology (IT) administrator to manually register the presence or indicate the importance of virtual machines existing in said computing environment.
14. The computer-implemented method of claim 13 wherein said performing a feature capacity analysis of said components of said computing environment further comprises:
performing a vertical scaling of said resources based on a forecast of resource utilization of said computing environment.
15. The computer-implemented method of claim 14 wherein said performing a vertical scaling of said resources comprises automatically configuring said resource while said resource is in operating mode in said computing environment.
16. The computer-implemented method of claim 13 wherein said automatically monitoring provides performance metrics of said resources to a forecast service to automatically continuously forecast resource requirements in said computing environment.
17. The computer-implemented method of claim 16 wherein said the vertical scaling component periodically invokes forecast requests from the forecast service component for a predefined period of time during the operation of the resource in the computing environment.
18. The computer-implemented method of claim 16 wherein said vertical scaling module, comprises a configuration manager component that take inputs from users to generate an auto scale policy to be applied by the vertical scaling component, wherein the configuration manager component consults with auto scaling service to determine whether a resource can support a dynamic resources update while the resource is in operating mode in said computing environment.