Methods and Systems of Predictive Monitoring of Objects in a Distributed Network System

• US 20140214745A1
• Filed: 03/15/2013
• Published: 07/31/2014
• Est. Priority Date: 01/28/2013
• Status: Active Grant

• Current Assignee: Rackspace US Incorporated (Apollo Global Management, Inc.)
• Original Assignee: Rackspace US Incorporated (Apollo Global Management, Inc.)
• Inventors: Walsh, Alexander Leonard
• Granted Patent: US 9,483,334 B2
• Time in Patent Office: Days
• US Class Current: 706/46
• CPC Class Codes: G06F 11/008 Reliability or availability analysis
• CPC Class Codes: G06F 11/3006 where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems multiprogramming arrangements G06F9/46; allocation of resources G06F9/50
• CPC Class Codes: G06F 11/3041 where the computing system component is an input/output interface interconnection of, or transfer of information or other signals between, memories, input/output devices or central processing units G06F13/00
• CPC Class Codes: G06F 11/3051 Monitoring arrangements for monitoring the configuration of the computing system or of the computing system component, e.g. monitoring the presence of processing resources, peripherals, I/O links, software programs verification or detection of system hardware configuration G06F11/2247
• CPC Class Codes: G06F 2009/45591 Monitoring or debugging support
• CPC Class Codes: G06F 2201/865 Monitoring of software
• CPC Class Codes: G06F 2209/547 Messaging middleware
• CPC Class Codes: G06F 2209/548 Queue
• CPC Class Codes: G06F 9/45558 Hypervisor-specific management and integration aspects
• CPC Class Codes: G06F 9/465 Distributed object oriented systems remote method invocation [RMI] G06F9/548
• CPC Class Codes: G06F 9/546 Message passing systems or structures, e.g. queues
• CPC Class Codes: H04L 41/069 using logs of notifications; Post-processing of notifications
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 41/5096 wherein the managed service relates to distributed or central networked applications

Abstract

Predictive monitoring of objects in a distributed network system providing cloud services is disclosed. In one embodiment, the methods and systems observing one or more update messages sent and received among components of the distributed network system, the update messages comprising information associated with a state of an object on the distributed network system, determine the state of the object in response to the one or more update messages, and reference a predictive object state model to predict occurrence of an artifact in response to the state of the object. Advantageously, the present embodiments provide advanced warning of potential failures in a distributed network systems, which may enable a system administrator or dynamic process to resolve the failure before it ever occurs. Additional benefits and advantages of the present embodiments will become evident in the following description.

Claims

1. A method of predictive monitoring of processes in a distributed network system providing cloud services, the method comprising:

observing one or more update messages sent and received among components of the distributed network system, the update messages comprising information associated with a state of an object on the distributed network system;

determining the state of the object in response to the one or more update messages; and

referencing a predictive object state model to predict occurrence of an artifact in response to the state of the object.

2. The method of claim 1, further comprising generating the predictive object state model in response to observations of one or more artifact occurrences associated with an object state.

3. The method of claim 2, further comprising generating the predictive object state model in response to observations of one or more artifact occurrences associated with a sequence of sequential object states leading to the object state.

4. The method of claim 2, wherein generating the predictive object state model comprises defining relationships between states and artifacts prior to observing the one or more updated messages.

5. The method of claim 2, wherein generating the predictive object state model comprises dynamically defining relationships between states and artifacts in response to a plurality of update messages observed over time.

6. The method of claim 1, further comprising updating the predictive object state model in response to the one or more update messages observed.

7. The method of claim 1, further comprising assigning a probability that the one or more artifacts will occur in response to the predictive object state model and the state of the object.

8. The method of claim 1, further comprising generating a notification in response to predicting the occurrence of the artifact.

9. A distributed network system comprising:

a plurality of service components;

an Application Program Interface (API) configured to receive a request for a system state change; and

an monitoring service component configured to;

observe one or more update messages sent and received among components of the distributed network system, the update messages comprising information associated with a state of an object on the distributed network system;

determine the state of the object in response to the one or more update messages; and

reference a predictive object state model to predict occurrence of an artifact in response to the state of the object.

10. The distributed network system of claim 9, wherein the monitoring service is further configured to generate the predictive object state model in response to observations of one or more artifact occurrences associated with an object state.

11. The distributed network system of claim 10, wherein the monitoring service is further configured to generate the predictive object state model in response to observations of one or more artifact occurrences associated with a sequence of sequential object states leading to the object state.

12. The distributed network system of claim 10, wherein generating the predictive object state model comprises defining relationships between states and artifacts prior to observing the one or more updated messages.

13. The distributed network system of claim 10, wherein generating the predictive object state model comprises dynamically defining relationships between states and artifacts in response to a plurality of update messages observed over time.

14. The distributed network system of claim 9, wherein the monitoring service is further configured to update the predictive object state model in response to the one or more update messages observed.

15. The distributed network system of claim 9, wherein the monitoring service is further configured to assign a probability that the one or more artifacts will occur in response to the predictive object state model and the state of the object.

16. The distributed network system of claim 9, wherein the monitoring service is further configured to generate a notification in response to predicting the occurrence of the artifact.

17. A non-transitory computer-accessible storage medium storing program instructions that, when executed by a data processing device, cause the data processing device to implement operations for failure monitoring in a distributed network system providing cloud services, the operations comprising:

observe one or more update messages sent and received among components of the distributed network system, the update messages comprising information associated with a state of an object on the distributed network system;

determine the state of the object in response to the one or more update messages; and

reference a predictive object state model to predict occurrence of an artifact in response to the state of the object.

18. The computer-accessible storage medium of claim 17, further comprising generating the predictive object state model in response to observations of one or more artifact occurrences associated with an object state.

19. The computer-accessible storage medium of claim 18, further comprising generating the predictive object state model in response to observations of one or more artifact occurrences associated with a sequence of sequential object states leading to the object state.

20. The computer-accessible storage medium of claim 18, wherein generating the predictive object state model comprises defining relationships between states and artifacts prior to observing the one or more updated messages.

21. The computer-accessible storage medium of claim 18, wherein generating the predictive object state model comprises dynamically defining relationships between states and artifacts in response to a plurality of update messages observed over time.

22. The computer-accessible storage medium of claim 17, further comprising updating the predictive object state model in response to the one or more update messages observed.

23. The computer-accessible storage medium of claim 17, further comprising assigning a probability that the one or more artifacts will occur in response to the predictive object state model and the state of the object.

24. The computer-accessible storage medium of claim 17, further comprising generating a notification in response to predicting the occurrence of the artifact.