Application Monitoring for Cloud-Based Architectures

• US 20150358391A1
• Filed: 05/22/2013
• Published: 12/10/2015
• Est. Priority Date: 12/21/2012
• Status: Active Grant

• Current Assignee: BMC Software Incorporated (KKR & Co., Inc.)
• Original Assignee: BMC Software Incorporated (KKR & Co., Inc.)
• Inventors: Moon, Cliff, Black, Benjamin
• Granted Patent: US 9,819,729 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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 11/302 where the computing system component is a software system
• CPC Class Codes: G06F 11/34 Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3428 Benchmarking
• CPC Class Codes: G06F 2201/805 Real-time
• CPC Class Codes: G06F 2201/81 Threshold
• CPC Class Codes: G06F 2201/86 Event-based monitoring
• CPC Class Codes: G06F 2201/865 Monitoring of software
• CPC Class Codes: G06F 2201/875 Monitoring of systems including the internet
• CPC Class Codes: H04L 43/08 Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/125 involving control of end-device applications over a network

Abstract

An example system may include one or more collectors, an analyzer, and a presentation module. The one or more collectors receive a plurality of data streams that include operational data for a plurality of application nodes. The plurality of data streams are captured and provided by a plurality of meters deployed on at least one cloud computing platform to respectively meter the plurality application nodes. The analyzer processes the plurality of data streams to generate real-time performance data for an application associated with the plurality of application nodes. The presentation module streams the real-time performance data to at least one stakeholder of the application for display via a dashboard. The real-time performance data includes one or more performance metrics describing the performance of plurality of the application nodes of the application.

Claims

1. A computer-implemented method comprising:

receiving, at a monitoring station, a plurality of data streams that include real-time operational data for a corresponding plurality of application instances of an application launched on a cloud network, each application instance being hosted on a corresponding node in the cloud network, the operational data including operational data sent and received by each of the nodes hosting the application instances in the cloud network;

processing the plurality of data streams corresponding to the plurality of application instances to generate real-time performance data for the application launched on the cloud network, the real-time performance data including one or more performance metrics describing the performance of the nodes hosting the application instances in the cloud network; and

streaming the real-time performance data to a display station.

2. The computer-implemented method of claim 1, further comprising:

deploying a plurality of meters on a plurality of server instances included in the cloud network, the plurality of server instances hosting the plurality of application instances, respectively; and

capturing, via the plurality of meters, the plurality of data streams that include the operational data for the plurality of application instances.

3. The computer-implemented method of claim 1, further comprising:

grouping the plurality of data streams as being associated with the application.

4. The computer-implemented method of claim 1, wherein the processing the plurality of data streams to generate the real-time performance data includes generating, using network traffic data included in the data streams, a dynamic application topology that automatically maps resources being used by the application and identifies changes to the application topology as they occur.

5. The computer-implemented method of claim 1, further comprising:

analyzing the plurality of data streams across a plurality of entities; and

generating cross-entity insights based on the analyzing, wherein the real-time performance data includes the cross-entity insights.

6. The computer-implemented method of claim 5, wherein the entities include different cloud computing platforms, customers, or cloud computing platforms and customers, and the cross-entity insights include comparative insights that compare a performance of one or more aspects of the cloud computing platforms, customers, or the cloud computing platforms and customers, the aspects including one or more of an application, an infrastructure, a network, an IP service, an operating system, a platform stack, an architecture, and a geographical region.

7. The computer-implemented method of claim 1, further comprising:

determining an event to monitor for the application;

setting a threshold for the event;

monitoring the plurality of data streams for one or more instances of the event;

determining the threshold to be satisfied by the one or more instances of the event; and

notifying a stakeholder of the application that the event has occurred.

8. The computer-implemented method of claim 7, wherein the determining the event and the setting the threshold further include automatically monitoring the data streams over time to determine an application trend, and determining the event and setting the threshold based on the application trend.

9. A computer program product comprising a computer usable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to:

receive, at a monitoring station, a plurality of data streams that include real-time operational data for a corresponding plurality of application instances of an application launched on a cloud network, each application instance being hosted on a corresponding node in the cloud network, the operational data including operational data sent and received by each of the nodes hosting the application instances in the cloud network;

process the plurality of data streams corresponding to the plurality of application instances to generate real-time performance data for the application launched on the cloud network, the real-time performance data including one or more performance metrics describing the performance of the nodes hosting the application instances in the cloud network; and

stream the real-time performance data to a display station.

10. The computer program product of claim 9, wherein the computer readable program, when executed on the computer, further causes the computer to:

deploy a plurality of meters on a plurality of server instances included in the cloud network, the plurality of server instances hosting the plurality of application instances, respectively; and

capture, via the plurality of meters, the plurality of data streams that include the operational data for the plurality of application instances.

11. The computer program product of claim 9, wherein the computer readable program, when executed on the computer, further causes the computer to:

group the plurality of data streams as being associated with the application.

12. The computer program product of claim 9, wherein to process the plurality of data streams to generate the real-time performance data includes generating, using network traffic data included in the data streams, a dynamic application topology that automatically maps resources being used by the application and identifies changes to the application topology as they occur.

13. The computer program product of claim 9, wherein the computer readable program, when executed on the computer, further causes the computer to:

analyze the plurality of data streams across a plurality of entities; and

generate cross-entity insights based on the analyzing, wherein the real-time performance data includes the cross-entity insights.

14. The computer program product of claim 13, wherein the entities include different cloud computing platforms, customers, or cloud computing platforms and customers, and the cross-entity insights include comparative insights that compare a performance of one or more aspects of the cloud computing platforms, customers, or the cloud computing platforms and customers, the aspects including one or more of an application, an infrastructure, a network, an IP service, an operating system, a platform stack, an architecture, and a geographical region.

15. The computer program product of claim 9, wherein the computer readable program, when executed on the computer, further causes the computer to:

determine an event to monitor for the application;

set a threshold for the event;

monitor the plurality of data streams for one or more instances of the event;

determine the threshold to be satisfied by the one or more instances of the event; and

notify a stakeholder of the application that the event has occurred.

16. The computer program product of claim 15, wherein to determine the event and to set the threshold further include automatically monitoring the data streams over time to determine an application trend, and determining the event and setting the threshold based on the application trend.

17. A system comprising:

one or more processors;

one or more collectors executable by the one or more processors to

receive a plurality of data streams that include real-time operational data for a corresponding plurality of application instances of an application launched on a cloud network, each application instance being hosted on a corresponding node in the cloud network, the operational data including operational data sent and received by each of the nodes hosting the application instances in the cloud network;

an analyzer executable by the one or more processors to process the plurality of data streams corresponding to the plurality of application instances to generate real-time performance data for the application launched on the cloud network, the real-time performance data including one or more performance metrics describing the performance of the nodes hosting the application instances in the cloud network; and

a presentation module executable by the one or more processors to stream the real-time performance data to a display station.

18. The system of claim 17, further comprising:

a plurality of meters deployable and executable on a plurality of server instances included in the cloud network, the plurality of server instances hosting the plurality of application instances, respectively, and the plurality of meters configured to capture the plurality of data streams that include the operational data for the plurality of application instances.

19. The system of claim 17, further comprising:

a messaging unit executable by the one or more processors to group the plurality of data streams as being associated with the application, the messaging unit coupled to the one or more collectors to receive the data streams and coupled to the analyzer to provide the data streams to the analyzer and receive the real-time performance data from the analyzer.

20. The system of claim 17, wherein the analyzer is further configured to process the plurality of data streams to generate the real-time performance data by generating, using network traffic data included in the data streams, a dynamic application topology that automatically maps resources being used by the application and identifies changes to the application topology as they occur.

21. The system of claim 17, wherein the analyzer is further configured to analyze the plurality of data streams across a plurality of entities and generate cross-entity insights based on the analyzing of the plurality of data streams, wherein the real-time performance data includes the cross-entity insights.

22. The system of claim 21, wherein the entities include different cloud computing platforms, customers, or cloud computing platforms and customers, and the cross-entity insights include comparative insights that compare a performance of one or more aspects of the cloud computing platforms, customers, or the cloud computing platforms and customers, the aspects including one or more of an application, an infrastructure, a network, an IP service, an operating system, a platform stack, an architecture, and a geographical region.

23. The system of claim 17, wherein the presentation module or the analyzer is further configured to determine an event to monitor for the application and set a threshold for the event, the analyzer is further configured to monitor the plurality of data streams for one or more instances of the event and determine the threshold to be satisfied by the one or more instances of the event, and the presentation module is further configured to notify a stakeholder of the application that the event has occurred.

24. The system of claim 23, wherein the analyzer is further configured to determine the event and the set the threshold by automatically monitoring the data streams over time to determine an application trend, and determine the event and set the threshold based on the application trend.