ACCELERATING RESOURCE ALLOCATION IN VIRTUALIZED ENVIRONMENTS USING WORKLOAD CLASSES AND/OR WORKLOAD SIGNATURES

• US 20130185729A1
• Filed: 03/02/2012
• Published: 07/18/2013
• Est. Priority Date: 01/13/2012
• Status: Abandoned Application

• Current Assignee: Rutgers University, Ecole polytechnique fãdãrale de lausanne epfl (Schweizerische Eidgenossenschaft)
• Original Assignee: Rutgers University, Ecole polytechnique fãdãrale de lausanne epfl (Schweizerische Eidgenossenschaft)
• Inventors: Novakovic, Dejan, Vasic, Nedeljko, Kostic, Dejan, Miucin, Svetozar, Bianchini, Ricardo
• Application Number:
  US13/411,491
• Publication Number:
  US 20130185729A1
• Time in Patent Office: Days
• US Class Current: 718/104
• CPC Class Codes: G06F 11/3442 for planning or managing the needed capacity
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: G06F 2201/83 the solution involving signatures
• CPC Class Codes: G06F 2209/508 Monitor
• CPC Class Codes: G06F 9/5072 Grid computing

Abstract

Systems, methods, and apparatus for managing resources assigned to an application or service. A resource manager maintains a set of workload classes and classifies workloads using workload signatures. In specific embodiments, the resource manager minimizes or reduces resource management costs by identifying a relatively small set of workload classes during a learning phase, determining preferred resource allocations for each workload class, and then during a monitoring phase, classifying workloads and allocating resources based on the preferred resource allocation for the classified workload. In some embodiments, interference is accounted for by estimating and using an “interference index”.

Claims

1. A resource management system usable in distributed computing environments wherein computing resources are allocated among a plurality of applications that would consume those computing resources and are allocated portions of those computing resources, the resource management system comprising:

a monitor operable to receive client requests directed to an application;

a profiler operable to compute a workload signature for each workload of a clone of the application that results from the clone serving the client requests;

a clusterer operable to cluster workloads; and

a tuner operable to map each cluster to a resource allocation.

2. The resource management system of claim 1, further comprising an interference detector that detects interference from collocated workloads.

3. The resource management system of claim 2, wherein the interference detector detects interference by contrasting the performance of the clone with the performance of the application.

4. The resource management system of claim 2, wherein when the interference detector detects interference from collocated workloads, the interference detector generates an index indicating a resource multiplication factor indicative of the amount of resources needed to account for the interference.

5. The resource management system of claim 1, wherein the application is part of a multi-tier service executing on an application server coupled to a database, requests to and answers from the database are stored and used to simulate database requests by the profiler.

6. A resource management system usable in distributed computing environments wherein computing resources are allocated among a plurality of applications that would consume those computing resources and are allocated portions of those computing resources, the resource management system comprising:

a monitor operable to receive client requests directed to an application;

a profiler operable to compute a workload signature for a workload of a clone of the application that results from the clone serving the client requests;

a classifier operable to classify the workload signature using previously defined workload classes; and

a resource allocator operable to cause a number of resources to be allocated to the application defined by a resource allocation associated with a workload class that matches the workload signature.

7. The resource management system of claim 6, further comprising an interference detector operable to detect interference from collocated workloads and adjust the number of resources allocated to the application based on the detected interference.

8. The resource management system of claim 6, wherein resources include one or more of storage space, processor time, and network bandwidth.

9. The resource management system of claim 6, wherein the workload signature is a vector of metrics describing the workload characteristics of the clone.

10. The resource management system of claim 9, wherein the metrics include one or more of:

hardware performance counters, central processing unit, memory, input/output, cache, and bus queue.

11. A method of modeling an application in a distributed computing environment wherein computing resources are allocated among a plurality of applications that would consume those computing resources and are allocated portions of those computing resources, the method comprising:

receiving client requests at a computing device;

serving the client requests using an application at the computing device;

computing workload signatures for the application;

generating at least one workload class based on the workload signatures; and

determining resource allocations for each workload class.

12. The method of claim 11, wherein the application is a clone of an application to which the client requests are directed.

13. The method of claim 11, wherein only the received client requests are only a portion of all client requests communicated to the application during a specified time period.

14. The method of claim 11 wherein the workload signatures are computed using at least one hardware characteristic of a computing device which the application is executing on.

15. The method of claim 11 wherein generating at least one workload class includes clustering the workload signatures.

16. A method of allocating resources to an application in a distributed computing environment wherein computing resources are allocated among a plurality of applications that would consume those computing resources and are allocated portions of those computing resources, the method, comprising:

receiving a client request at a computing device;

serving the client request using the application at the computing device;

computing a workload signature for the application;

comparing the workload signature to at least one workload class associated with the application; and

causing resources to be allocated to the application based on the comparison.

17. The method of claim 16, wherein comparing the workload signature to at least one workload class associated with the application includes executing a classification algorithm that classifies the workload signature.

18. The method of claim 16, further comprising determining a certainty level indicating an amount of certainty with which the workload signature matches a workload class.

19. The method of claim 16, wherein causing resources to be allocated to the application includes reading a stored resource allocation associated with a workload class that matches the workload signature.

20. The method of claim 16, wherein causing resources to be allocated to the application includes, when the workload signature does not match any of the at least one workload class, performing steps selected from the group consisting of:

additional modeling of the application;

sandboxed experimentation;

online experiment; and

deploying a full capacity configuration for the application.