Automatic data interpretation and implementation using performance capacity management framework over many servers

• US 7,171,668 B2
• Filed: 12/17/2001
• Issued: 01/30/2007
• Est. Priority Date: 12/17/2001
• Status: Active Grant

• Current Assignee: ServiceNow Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Quesenberry, Gary M, Molloy, Christopher L, Robinson, Robert
• Primary Examiner(s): An; Meng-Al T.
• Assistant Examiner(s): Truong; Camquy
• Application Number:
  US10/023,154
• Publication Number:
  US 20030115244A1
• Time in Patent Office: 1,870 Days
• Field of Search: 395/183.19, 709/226, 718/104, 718/105
• US Class Current: 718/105
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 2201/81 Threshold
• CPC Class Codes: G06F 2201/875 Monitoring of systems including the internet
• CPC Class Codes: G06F 2209/5019 Workload prediction
• CPC Class Codes: G06F 9/505 considering the load

Abstract

An automated method of managing computing resources having a workload of a given type comprises providing resource data collectors for collecting data regarding performance of the resources, such as a server network, in accordance with the type of workload; developing a forecast of utilization of the resources, based on historical performance data; and collecting real-time performance data regarding the resources running under the workload. The method then includes analyzing the performance data and the forecast to identify a critical resource: and automatically adjusting a capacity of the resource to provide steady-state performance of the resource under the workload. Additional hardware resources such as CPUs, computer memory and computer disk storage are initially available to, but unused by, the computing resources.

Claims

1. An automated method of managing server network computing resources having a workload of a given type, the method comprising:

providing additional hardware resources available to, but unused by, the server network computing resources;

providing resource data collectors for collecting data regarding performance of the server network computing resources, in accordance with the type of workload;

developing a forecast of utilization of the server network computing resources, based on historical performance data;

collecting real-time performance data regarding the server network computing resources running under the workload;

analyzing the real-time performance data and the forecast to identify a critical server network computing resource; and

automatically adjusting a capacity of the server network computing resource to provide steady-state performance of said resource under said workload.

2. The method of claim 1 further comprising setting threshold values for said performance data and identifying the server network computing resource in accordance with the threshold values.

3. The method of claim 1 further comprising:

notifying a user of the server network computing resources when the critical resource is a hardware resource; and

notifying the user when the capacity of said hardware resource is adjusted.

4. The method of claim 3 wherein the additional hardware resources are selected from the group consisting of CPUs, computer memory and computer disk storage.

5. The method of claim 1 wherein the additional hardware resources are selected from the group consisting of CPUs, computer memory and computer disk storage.

6. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform an automated method of managing server network computing resources having a workload of a given type, using resource data collectors for collecting data regarding performance of the server network computing resources in accordance with the type of workload, and a forecast of utilization of the server network computing resources based on historical performance data, the server network computing resources further including additional hardware resources available to, but unused by, the computing resources, said method steps comprising:

collecting real-time performance data regarding the server network computing resources running under the workload;

analyzing the real-time performance data and the forecast to identify a critical server network computing resource; and

automatically adjusting a capacity of the server network computing resource to provide steady-state performance of said resource under said workload.

7. The program storage device of claim 6 wherein the method steps further comprise setting threshold values for said performance data and identifying the server network computing resource in accordance with the threshold values.

8. The program storage device of claim 6 wherein the method steps further comprise:

notifying a user of the server network computing resources when the critical resource is a hardware resource; and

notifying the user when the capacity of said hardware resource is adjusted.

9. The program storage device of claim 8 wherein the additional hardware resources are selected from the group consisting of CPUs, computer memory and computer disk storage.

10. The program storage device of claim 6 wherein the additional hardware resources are selected from the group consisting of CPUs, computer memory and computer disk storage.

11. A computer program product for performing an automated method of managing server network computing resources having a workload of a given type, using resource data collectors for collecting data regarding performance of the server network computing resources in accordance with the type of workload, and a forecast of utilization of the server network computing resources based on historical performance data, the server network computing resources further including additional hardware resources available to, but unused by, the server network computing resources, said computer program product having:

computer-readable program code for collecting real-time performance data regarding the server network computing resources running under the workload;

computer-readable program code for analyzing the real-time performance data and the forecast to identify a critical server network computing resource; and

computer-readable program code for automatically adjusting a capacity of the server network computing resource to provide steady-state performance of said resource under said workload.

12. The computer program product of claim 11 wherein the computer program product further comprises computer-readable program code for setting threshold values for said performance data and computer-readable program code for identifying the server network computing resource in accordance with the threshold values.

13. The computer program product of claim 11 wherein the computer program product further comprises:

computer-readable program code for notifying a user of the server network computing resources when the critical resource is a hardware resource; and

computer-readable program code for notifying the user when the capacity of said hardware resource is adjusted.

14. The computer program product of claim 13 wherein the additional hardware resources are selected from the group consisting of CPUs, computer memory and computer disk storage.

15. The computer program product of claim 11 wherein the additional hardware resources are selected from the group consisting of CPUs, computer memory and computer disk storage.