The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 16, 2011

Filed:

Dec. 21, 2005
Applicants:

Waheed Qureshi, Pleasanton, CA (US);

Tanvir Hassan, Alameda, CA (US);

Kelly Brian Roach, Palo Alto, CA (US);

Gregory Paul Bala, Morgan Hill, CA (US);

Inventors:

Waheed Qureshi, Pleasanton, CA (US);

Tanvir Hassan, Alameda, CA (US);

Kelly Brian Roach, Palo Alto, CA (US);

Gregory Paul Bala, Morgan Hill, CA (US);

Assignee:

Zenprise, Inc., Redwood City, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 9/44 (2006.01); G06F 9/45 (2006.01); G06F 9/445 (2006.01);
U.S. Cl.
CPC ...
Abstract

Computer systems and methods are disclosed for managing a deployment of a software application. One system includes an application model describing the deployment, the application model comprising a representation of physical and logical objects in a domain of the deployment, configuration data about the objects, and information about relationships between the objects. The system also includes a root cause analysis module configured to identify one or more problematic objects of the application model, and to use pattern-recognition on the application model to find root cause candidates that may be a root cause of one or more problems associated with the problematic objects. The root cause analysis module can be further configured to apply diagnostic unit tests on one or more objects associated with the root cause candidates, the diagnostic unit tests configured to narrow down a list of possible root causes of the problems. Various pattern-recognition techniques are disclosed, including looking for recent property or configurational changes in the application model, clustering of problematic objects, examining links between objects in the application model, comparisons between pairs of non-problematic objects as well as between problematic objects and non-problematic objects, temporal comparisons of the state of the application model, and examining objects that are near the problematic objects in the application model.


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