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Techniques for building a model for performing diagnostics. In one embodiment, a set of models is determined based upon a topological relationship created upon receiving an alert or a request for which diagnostics are to be performed. An aggregate model is then generated based upon the set of models

Techniques for building a model for performing diagnostics. In one embodiment, a set of models is determined based upon a topological relationship created upon receiving an alert or a request for which diagnostics are to be performed. An aggregate model is then generated based upon the set of models and the topological relationship. The aggregate model is then used for performing the diagnostics.

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1. A non-transitory computer-readable storage medium storing a plurality of instructions for controlling a processor to build a model for diagnostics, the plurality of instructions comprising: instructions that cause the processor to determine a set of models based upon a topological relationship id

1. A non-transitory computer-readable storage medium storing a plurality of instructions for controlling a processor to build a model for diagnostics, the plurality of instructions comprising: instructions that cause the processor to determine a set of models based upon a topological relationship identifying a set of applications, a set of systems configured to execute the set of applications, and relationships between the set of applications and the set of systems; andinstructions that cause the processor to generate a single aggregate model based upon the topological relationship, the aggregate model comprising the set of models and comprising one or more links between one or more of the models in the set of models, the links created based upon the relationships in the topological relationship; andinstructions that cause the processor to use the single aggregate model to perform diagnostics. 2. The non-transitory computer-readable storage medium of claim 1 wherein each model in the set of models is a causal network and each model specifies causal relationships between one or more faults and observations. 3. The non-transitory computer-readable storage medium of claim 2 wherein each model in the set of models is represented by a Bayesian network. 4. The non-transitory computer-readable storage medium of claim 1 wherein the instructions that cause the processor to determine the set of models comprise instructions that cause the processor to determine a model for each system and for each application identified in the topological relationship. 5. The non-transitory computer-readable storage medium of claim 1 wherein: the set of models comprises a first model and a second model; andthe instructions that cause the processor to generate the single aggregate model comprise instructions that cause the processor to create a link between the first model and the second model, andinstructions that cause the processor to assign a probability value to the link between the first model and the second model, the probability value representing a degree of influence between the first model and the second model in the aggregate model. 6. The non-transitory computer-readable storage medium of claim 5 wherein: the first model comprises an output node and the second model comprises an input node; andinstructions that cause the processor to create the link between the first model and the second model comprise instructions that cause the processor to link the output node of the first model to the input node of the second model. 7. The non-transitory computer-readable storage medium of claim 1 wherein: the topological relationship identifies a first application and a first system on which the first application executes;the set of models comprises a first model for the first application and a second model for the first system; andthe instructions that cause the processor to generate the aggregate model comprise instructions that cause the processor to create a link between the first model and the second model. 8. The non-transitory computer-readable storage medium of claim 7 wherein: the topological relationship identifies a second application and a second system on which the second application executes, and a relationship between the first application executing on the first system and the second application executing on the second system;the set of models comprises a third model for the second application and a fourth model for the second system; andthe instructions that cause the processor to generate the aggregate model comprise instructions that cause the processor to create a link between the third model and the fourth model, andinstructions that cause the processor to create a link either between the second model and the third model or between the first model and the fourth model. 9. A system for performing diagnostics, the system comprising: a memory configured to store a topological relationship identifying a set of applications, a set of systems configured to execute the set of applications, and relationships between the set of applications and the set of systems; anda processor coupled to the memory, the processor configured to determine a set of models based upon the topological relationship,generate a single aggregate model based upon the topological relationship, the aggregate model comprising the set of models and comprising one or more links between one or more of the models in the set of models, the links created based upon the relationships in the topological relationship, andinstructions that cause the processor to use the single aggregate model to perform diagnostics. 10. The system of claim 9 wherein each model in the set of models is a causal network and each model specifies causal relationships between one or more faults and observations. 11. The system of claim 10 wherein each model in the set of models is represented by a Bayesian network. 12. The system of claim 9 wherein the processor is configured to determine a model for each system and for each application identified in the topological relationship. 13. The system of claim 9 wherein: the set of models comprises a first model and a second model; andthe processor is configured to create a link between the first model and the second model, andassign a probability value to the link between the first model and the second model, the probability value representing a degree of influence between the first model and the second model in the aggregate model. 14. The system of claim 13 wherein: the first model comprises an output node and the second model comprises an input node; andthe processor is configured to link the output node of the first model to the input node of the second model. 15. The system of claim 9 wherein: the topological relationship identifies a first application and a first system on which the first application executes;the set of models comprises a first model for the first application and a second model for the first system; andthe processor is configured to create a link between the first model and the second model. 16. The system of claim 15 wherein: the topological relationship identifies a second application and a second system on which the second application executes, and a relationship between the first application executing on the first system and the second application executing on the second system;the set of models comprises a third model for the second application and a fourth model for the second system; andthe processor is configured to create a link between the third model and the fourth model, andcreate a link either between the second model and the third model or between the first model and the fourth model. 17. A method for building a model for performing diagnostics, the method comprising: determining, by a processor system, a set of models based upon a topological relationship identifying a set of applications, a set of systems configured to execute the set of applications, and relationships between the set of applications and the set of systems;generating, by the processor system, a single aggregate model based upon the topological relationship, the aggregate model comprising the set of models and comprising one or more links between one or more of the models in the set of models, the links created based upon the relationships in the topological relationship, andusing, by the processor system, the single aggregate model to perform diagnostics. 18. The method of claim 17 wherein each model in the set of models is a causal network and each model specifies causal relationships between one or more faults and observations. 19. The method of claim 17 wherein: the set of models comprises a model for each system and for each application identified in the topological relationship, the set of models comprising a first model and a second model; andgenerating the aggregate model comprises creating a link between the first model and the second model, andassigning a probability value to the link between the first model and the second model, the probability value representing a degree of influence between the first model and the second model in the aggregate model. 20. The method of claim 17 wherein: the topological relationship identifies a first application and a first system on which the first application executes;the topological relationship identifies a second application and a second system on which the second application executes;the topological relationship identifies a relationship between the first application executing on the first system and the second application executing on the second system;the set of models comprises a first model for the first application, a second model for the first system, a third model for the second application, and a fourth model for the second system; andgenerating the aggregate model comprises creating a link between the first model and the second model,creating a link between the third model and the fourth model, andcreating a link either between the second model and the third model or between the first model and the fourth model.