Method, system and apparatus for managing, modeling, predicting, allocating and utilizing resources and bottlenecks in a computer network
View Patent ↗A method and apparatus for managing, modeling, predicting, allocating and utilizing resources and bottlenecks in a computer network managing, predicting and displaying of capacity, allocating and utilizing of resources, as well as actual and potential performance-degrading resource shortages in a computer network, is provided. Specifically, exemplary implementations of the present invention provide a method, system and apparatus for calculating, detecting, predicting, and presenting resource allocation, utilization, capacity bottlenecks and availability information, in a computer network, particularly in a virtualized computer environment.
1. A method for managing utilization of resources on a computer network, the method comprising:
identifying, by a device, a virtual machine utilizing a plurality of resources shared by a plurality of virtual machines in a virtualized environment on a computer network;
obtaining, by the device, first data indicative of at least one of current and historical utilization of the resources by the virtual machine;
determining, by the device, from the first data an average utilization by the virtual machine of a resource of the plurality of resources based on a sum of usage of the resource by the virtual machine for each sub-period in a predetermined period divided by a number of subperiods;
determining, by the device, a total usage of the resource by the virtual machine for the period based on the average utilization;
creating, by the device, an extrapolation of the total usage to predict a next period at which a predetermined threshold of the resource is reached; and
generating, by the device responsive to the prediction, second data indicative of a future utilization bottleneck of the resource of the plurality of resources by the virtual machine based on the first data.
2. The method of claim 1 , further comprising:
selectively generating a notification based on at least one criteria associated with at least one of the first and second data.
3. The method of claim 2 , wherein the generating of the notification comprises providing at least one of a display via a graphical user interface, a report or an alert, wherein the notification comprises information indicative of the virtual machine and utilization of the resources associated with the virtual machine.
4. The method of claim 3 , wherein the generating of the notification comprises:
communicating of the notification to one or more recipients via at least one of the following: an internet, an extranet, a wireless connection, a cellular network, and a wired connection.
5. The method of claim 3 , where the generating of the notification comprises at least one of the following:
generating the notification based on the first data, the at least one criteria comprising a threshold associated with the first data;
generating the notification based on the second data, the at least one criteria comprising a threshold associated with the second data; and
predicting at least one of performance and utilization of the resources on the computer network and generating the notification based on the predicting.
6. The method of claim 1 , further comprising:
predicting at least one of performance and utilization of the resources on the computer network, wherein the utilization comprises at least one of information indicative of resource capacity bottlenecks, resource capacity availability or computing objects utilizing the resources.
7. The method of claim 6 , wherein each virtual machine of the plurality of virtual machines belongs to at least one of the following: a host, a cluster or a pool of resources.
8. The method of claim 6 , wherein the information indicative of the resource capacity availability comprises an indication of availability on the computer network of at least one of hosts, clusters and resource pools.
9. The method of claim 6 further comprising:
migrating computing objects from one resource to another based on the predicting.
10. The method of claim 9 , wherein the migrating comprises assigning computing objects to resources to optimize the utilization of the resources on the computer network.
11. The method of claim 9 , further comprising:
scheduling migration of computing objects from one resource to another based on the predicting, wherein the migrating of the computing objects from one resource to another is performed according to said scheduling.
12. The method of claim 1 , wherein the identifying, obtaining and generating are selectively repeated, the method further comprising selectively monitoring and evaluating the current, historical and future utilization of the resources.
13. The method of claim 1 , wherein the obtaining further comprises obtaining the first data for a first time period, and the generating comprises generating of the second data for a second time period.
14. The method of claim 13 , wherein at least one of the first and second time periods is selectable via a user interface.
15. The method of claim 14 , wherein the user interface comprises a graphic object indicative of the at least one of the first and second time period and allowing selection of the at least one of the first and second time period.
16. The method of claim 1 , wherein the resources comprise at least one of the following: a central processing unit, a memory unit, a storage unit, and an input/output unit.
17. The method of claim 1 , further comprising obtaining, by the device, statistics about use of a resource by the virtual machine within a predetermined time period, splitting the predetermined time period into sub-periods, determining a usage of the resource for each of the sub-periods and determining an average utilization of the resource over the predetermined time period based on a summation of the usage for each of the sub-periods.
18. The method of claim 17 , further comprising extrapolating, by the device, the average utilization of the resource to determine a future utilization of the resource each day up until a maximum number of days.
19. The method of claim 18 , further comprising comparing, by the device, the future utilization for each day to a plurality of predetermined thresholds and identifying predicted number of days to reach a first predetermined threshold of the plurality of predetermined thresholds.
20. A method for analyzing resource utilization in a computer network, the method comprising:
monitoring, by a device, resource utilization by a virtual machine utilizing resources shared by a plurality of virtual machines in a virtualized environment on a computer network;
generating, by the device, resource availability information of a resource used by the virtual machine based on an average usage of the resource by the virtual machine during each sub-period of a predetermined period;
generating, by the device, resource bottleneck information of the resource related to the virtual machine based on determining a total usage of the resource by the virtual machine for the predetermined period based on a sum of the average utilization during each sub period and a limit for the resource; and
generating, by the device, resource utilization trend information of the resource used by the virtual machine based on an extrapolation of the total usage to a plurality of next periods; and
determining, by the device, from the extrapolation a next period of the plurality of next periods at which a future bottleneck of use of the resource by the virtual machine is predicted to occur.
21. The method of claim 20 , wherein the virtual machine belongs to at least one of the following: a host, a cluster and a resource pool in the computer network.
22. The method of claim 20 , further comprising generating resource bottleneck information comprising one of the following: a current bottleneck of the resource or one or more historical bottlenecks of the resource.
23. The method of claim 20 , wherein the resource comprises at least one of the following: a central processing unit (CPU), memory, storage and disk input/output (I/O).
24. The method of claim 20 , wherein the bottleneck is indicative of at least one of a current resource bottleneck or a future resource bottleneck.
25. The method of claim 20 , further comprising: selectively generating a notification based on at least one criteria associated with at least one of the resource utilization, resource availability, resource bottleneck and resource utilization trend.
26. The method of claim 25 , wherein the generating of the resource bottleneck information comprises:
identifying a prediction time period for predicting potential future bottlenecks; and
generating future resource bottleneck information based on the resource utilization trend over a specified historical time period.
27. The method of claim 26 , wherein the method further comprises:
determining a confidence level of the future resource bottleneck information.
28. The method of claim 25 , wherein the at least one criteria comprises a threshold, and the generating of the notification comprises generating an alert when the resource utilization trend indicates exceeding of the threshold.
29. The method of claim 28 , wherein the at least one threshold provides at least one parameter for continuously monitoring the resource utilization trend.
30. The method of claim 25 , wherein the at least one criteria is user defined.
31. The method of claim 20 , wherein bottleneck information comprises at least one of the following: performance constraints, resource slowdown and resource overutilization in the computer network.
32. The method of claim 20 , wherein the generating of the resource availability information comprises:
generating a mapping of the at least one computing object and the at least one computing resource; and
identifying at least one available resource for the computing object.
33. The method of claim 20 further comprising:
determining utilization of resources on a computing network based on at least one of the resource utilization, availability, bottleneck and utilization trend information;
providing at least one option for modifying parameters affecting utilization of the resources; and
selectively executing the at least one option wherein the method comprises determining and outputting information comprising identification of parameters affecting the resources for virtual machines.
34. The method of claim 20 further comprising:
determining which of the resources of virtual machines are not-used and/or are under-used; and
providing a notification comprising information indicative of the not-used and/or under-used resources for at least one virtual machine, wherein parameters for assessing whether at least one of the resources is not-used or under-used are selectively set during an initialization.
35. The method of claim 20 further comprising:
receiving capacity modeling design information comprising parameters descriptive of a resource for at least one virtual machine;
obtaining constraints for analyzing the capacity modeling design information;
storing the capacity modeling design information;
presenting the capacity modeling design information; and
validating the capacity modeling design applicability for virtual machines.
36. The method of claim 35 , wherein designing a model comprises at least one of generating a new capacity model, altering and/or updating an existing capacity model and/or validating alterations to an existing capacity model.
37. The method of claim 20 , further comprising: providing user selectable objects for performing management of the resources for virtual machines, wherein the objects provide for management functions of the resources for the virtual machines.
38. A system comprising:
a computing system comprising a processor and memory, wherein the computing system is operable to manage utilization of resources shared by a plurality of virtual machines in a virtualized environment on a computer network,
the computing system executing sets of instructions comprising:
a first set of instruction for identifying a virtual machine of the plurality of virtual machines utilizing resources on a computer network;
a second set of instruction for obtaining first data indicative of current and historical utilization of the resources by the virtual machine; and
a third set of instruction for determining from the first data an average utilization by the virtual machine of a resource of the plurality of resources based on a sum of usage of the resource by the virtual machine for each sub-period in a predetermined period divided by a number of sub-periods, determining a total usage of the resource by the virtual machine for the period based on the average utilization of the virtual machine during each sub-period, and
creating an extrapolation of the total usage to predict a next period at which a predetermined threshold of the resource is reached; and
wherein the computing system generates, responsive to the prediction, second data indicative of a future utilization bottleneck of the resource of the plurality of resources by the at least one virtual machine based on the first data.