Method and apparatus to estimate downtime and cost of downtime in an information technology infrastructure

• US 20030187967A1
• Filed: 03/28/2002
• Published: 10/02/2003
• Est. Priority Date: 03/28/2002
• Status: Abandoned Application

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Compal Information Kunshan Company Limited (Compal Electronics Incorporated)
• Inventors: Walsh, John B., Sudarsky, Alexander, Rockall, Alan
• Application Number:
  US10/109,277
• Publication Number:
  US 20030187967A1
• Time in Patent Office: Days
• US Class Current: 709/223
• CPC Class Codes: H04L 41/0661 by reconfiguring faulty entities
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 41/147 for predicting network behaviour

Abstract

An availability analysis software tool for estimating the downtime and cost of downtime in an information technology network. The tool can create a computer element model of software and hardware components in the network. The elements are combinable into logical group models and element and group models are further combinable into a model tree to simulate the network. Each element is assigned a workload and the sum of element workloads determine group and model workloads. Simulated element failures reduce workload in the group and model tree. Cost per unit workload lost during an element failure are assignable, wherein the estimated cost of downtime caused by element failures is determined by multiplying the amount of workload that is lost from the simulated element failures by the cost per unit workload.

Claims

1. A method of estimating the cost of downtime in an information technology network comprising:

creating a computer model of individual components in the information technology network;

assigning a numerical workload to each component in the information technology network;

simulating component failures in the computer model;

calculating the amount of workload that is lost from the simulated component failures; and

assigning a cost per unit workload lost during a component failure;

wherein the estimated cost of downtime caused by component failures is determined by multiplying the amount of workload that is lost from the simulated component failures by the cost per unit workload.

2. The method of claim 1 wherein step of creating a computer model of individual components in the information technology network comprises:

identifying functionally separable components in the information technology network;

creating an element model for each components in the information technology network;

combining element models into logical group models to simulate real-world configurations; and

creating a hierarchical model tree of element and group models to simulate the information technology network.

wherein the element models are assigned a numerical workload and are combinable within the group models in a serial or parallel manner.

3. The method of claim 2 wherein when element models are combined in a serial manner in a group model, the failure of any element model in the group model causes the group model to fail.

4. The method of claim 2 wherein when element models are combined in a parallel manner in a group model, the sum of the workloads assigned to the individual element models determine the overall workload for the group model.

5. The method of claim 4 wherein the group models are assigned a minimum workload and wherein if failures of element models within the group cause the total workload for the group to fall equal to or below the minimum workload, the group model fails.

6. An network availability analysis software tool comprising:

a network modeling function comprising element and group models to represent network components;

a business mission editor for creating variable business missions, each mission representing a grouping of adjacent time slots that are each assigned an expected network workload and network downtime cost;

a user interface for creating a sequence of the variable business missions; and

a failure simulator that generates failure points and repair times for the models based on historical reliability of the network components;

wherein the failure points and repair times are mapped against the sequence of business missions to determine which variable business mission is impacted by the failure point.

7. The network availability analysis software tool of claim 6 wherein the failure simulator further generates failure points and repair times for the models based on availability of remedial service coverage to effect repairs when failures occur;

and

wherein the failure points and repair times are mapped against a calendar of available remedial service coverage to determine how repair time is impacted by the failure point.

8. The network availability analysis software tool of claim 7 wherein the failure points and repair times are compared to the expected network workload and network downtime cost assigned to the time slot during which the failure occurs to calculate a downtime cost associated with each failure.

9. The network availability analysis software tool of claim 8 wherein the user interface allows a software user to enter a maximum expected network workload and network downtime cost.

10. The network availability analysis software tool of claim 9 wherein the business mission editor allows a software user to enter an expected network workload and a network downtime cost to each time slot as a percentage of the maximum expected workload and maximum network downtime cost.

11. The network availability analysis software tool of claim 10 wherein the variable business missions are one week long and the time slots are two hours long.

12. A method of cost estimating software failures in a network simulation tool comprising:

modeling a software application as a software element in a network model, said software element producing a workload when operating but which produces no workload when failed;

creating a business mission comprising adjacent time slots, each time slot characterized by an expected network workload and network downtime cost;

assigning a future failure time to the element based on a mean time between crash (MTBC) value for the software application;

assigning a repair time to the element based on a mean time to repair (MTTR) value for the software application; and

estimating the cost of the software failure by

i. placing the future failure time in the appropriate time slot in the business mission and if the workload lost by the failure of the software element impacts the expected network workload for that time slot,

ii. calculating the cost of the software failure from the network downtime cost for that time slot and the expected repair time for the software element.

13. The method of claim 12 further comprising adjusting the future failure time based on user-definable software stability factors.

14. The method of claim 13 wherein the software stability factors comprise:

proactive management factor;

a patch management factor;

a software maturity factor;

a software stability factor; and

a support training factor;

wherein each of the software stability factors are adjustable to delay a future failure time if existing business practices represented by the factors lead to a more stable software application, and

wherein each of the software stability factors are adjustable to accelerate a future failure time if existing business practices represented by the factors lead to a less stable software application.

15. The method of claim 12 further comprising adjusting the expected repair time based on user-definable repair adjustment factors.

16. The method of claim 15 wherein the repair adjustment factors comprise:

whether a software auto-restart function is enabled;

the percentage of time a restart initiated by an enabled auto restart function fixes a software failure;

the percentage of time software failures are categorized as severe;

the percentage of time software failures are categorized as repairable;

the percentage of time a manual service intervention fixes a software failure; and

an estimated manual software restart time;

wherein if the software auto-restart function is enabled and a simulated failure is repaired by a restart initiated by the enabled auto restart function, the expected repair time is defined as the manual software restart time.

17. The method of claim 16 wherein if a simulated failure is not repaired by a restart initiated by the enabled auto restart function, the expected repair time is increased to account for a more extensive repair effort.

18. The method of claim 17 wherein if the simulated failure is categorized as severe, the expected repair time is increased by adding an extensive repair and recovery time.

19. The method of claim 18 wherein if the simulated failure is categorized as repairable by a manual service intervention, the expected repair time is increased by adding the estimated manual restart time, the time calculated based on availability of remedial service coverage and the element MTTR.

20. The method of claim 19 wherein if the simulated failure is categorized as repairable, but not by a manual service intervention, the expected repair time is increased by adding the estimated manual restart time and further adding an estimated repair time based on available remedial service coverage.

21. An network availability analysis software tool comprising:

a network modeling function that uses element and group model members to create a simulated network, said element model members representing components in the simulated network and said group model members comprising at least two element model members;

a failure simulator that generates failure points and repair times for the element and group model members based on historical reliability of the network components and availability of remedial service coverage,

wherein the network modeling function establishes correlated references between a slave reference model member and a master referenced model member that permit sharing of the same model member in different portions of the simulated network and wherein the failure simulator generates failure points and repair times for the master referenced model member, but not for the slave reference model member.

22. The network availability analysis software tool of claim 21 wherein failure points and repair times generated for the master referenced model member are imparted onto the slave reference model member.

23. The network availability analysis software tool of claim 22 wherein the failure simulator further generates recovery times for the model members based on an expected time needed to return to pre-failure operating capacity following a failure and repair.

24. The network availability analysis software tool of claim 23 wherein recovery times for correlated slave reference and master referenced group model members are independently simulated.

25. A method of estimating the cost of downtime in an information technology network comprising:

creating a computer element model of individual software and hardware components in the information technology network;

combining element models into logical group models to simulate real-world configurations;

creating a model tree of element and group models to simulate the information technology network.

assigning an element workload to each element in the information technology network, said element workloads being summable to determine group and model tree workloads;

simulating element failures in the model tree that reduce workload generated by a failed element;

omitting from the total group or model tree workloads the workload loss that is contributed by the simulated element failures; and

assigning a cost per unit workload lost at the model tree;

wherein the estimated cost of downtime in the model tree caused by element failures is determined by multiplying the amount of workload that is lost in the model tree times the cost per unit workload.

26. The method of claim 25 wherein the step of simulating element failures in the model tree further comprises:

generating failure points, repair times, and recovery times for the element models based on historical trends for the network components represented by the element models and availability of remedial service coverage;

applying user-definable workload factors to increase or decrease the workload loss encountered by the group or model tree during a simulated element failure.

27. The method of claim 26 further comprising:

defining an element failure workload factor that increases or decreases the workload loss encountered by the group or model tree during the time a simulated element fails, but before the element is repaired.

28. The method of claim 27 further comprising:

defining an element recovery workload factor that increases or decreases the workload loss encountered by the group or model tree during the time after which a simulated element failure is repaired, but before the element has recovered.

29. The method of claim 28 further comprising:

defining a group recovery workload factor that increases or decreases the workload loss encountered by the group or model tree during the time after which a simulated element has recovered from a failure, but before the group in which the failed element resides has recovered.

30. A method of estimating downtime in an information technology network comprising:

creating a computer element model of individual software and hardware components in the information technology network;

combining element models into logical group models to simulate real-world configurations;

creating a model tree of element and group models to simulate the information technology network.

assigning an element workload to each element in the information technology network, said element workloads being summable to determine group and model tree workloads;

simulating element failures in the model tree that reduce workload produced by a failed element;

simulating group failures if element failures within a group model cause the group workload to fall below a predetermined group workload minimum;

omitting from the model tree workload the workload loss that is contributed by the simulated element and group failures; and

wherein the estimated downtime in the information technology network is determined by comparing the simulated model tree workload to an expected network workload.

31. The method of claim 30 wherein the expected network workload is a user-definable business mission comprising adjacent time slots, each time slot characterized by an expected network workload.

32. The method of claim 31 wherein the estimated downtime in the information technology network accrues whenever the simulated model tree workload falls to zero.

33. The method of claim 31 wherein the estimated downtime in the information technology network accrues whenever the simulated model tree workload falls below the expected network workload.