Application monitoring for cloud-based architectures

Patent metadata

Field	Value
Publication number	US-9819729-B2
Application number	US-201313900441-A
Country	US
Kind code	B2
Filing date	May 22, 2013
Priority date	Dec 21, 2012
Publication date	Nov 14, 2017
Grant date	Nov 14, 2017

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.

First claim

What is claimed is:

1. A computer-implemented method comprising:
receiving, at a monitoring station, a plurality of data streams that include real-time operational data of a plurality of application instances of an application hosted on a cloud network, each application instance being hosted on a corresponding node from a plurality of nodes 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, wherein each of the nodes hosting the application instances includes a server instance in the cloud network;
deploying a meter on the server instance;
capturing, via the meter, the data streams that include the operational data of the application instances;
processing the plurality of data streams corresponding to the plurality of application instances to generate real-time performance data for the application hosted on the cloud network, the real-time performance data including one or more performance metrics describing the performance of the application instances hosted 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: grouping the plurality of data streams corresponding to the plurality of application instances as being associated with the application.

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

4. The computer-implemented method of claim 1 , further comprising:
analyzing the plurality of data streams across a plurality of entities;
generating insights across the plurality of entities based on the analyzing; and
including the insights across the plurality of entities in the real-time performance data of the application.

5. The computer-implemented method of claim 4 , wherein the entities include one or more cloud computing platforms and one or more customers, and wherein the insights across the plurality of entities include comparative insights that compare a performance of one or more aspects of the cloud computing platforms and customers, the aspects including one or more of an application, an infrastructure, a network, an Internet Protocol (IP) service, an operating system, a platform stack, an architecture, and a geographical region.

6. 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
indicating that the event has occurred.

7. The computer-implemented method of claim 6 , wherein the determining the event and the setting the threshold include automatically monitoring the data streams over time to determine an application trend and setting the threshold based on the application trend.

8. A computer program product comprising a non-transitory 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 of a corresponding plurality of application instances of an application hosted on a cloud network, each application instance being hosted on a corresponding node from a plurality of nodes 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, wherein each of the nodes hosting the application instances includes a server instance in the cloud network;
deploying a meter on the server instance;
capturing, via the meter, the data streams that include the operational data of the application instances;
process the plurality of data streams corresponding to the plurality of application instances to generate real-time performance data for the application hosted on the cloud network, the real-time performance data including one or more performance metrics describing the performance of the application instances hosted in the cloud network; and
stream the real-time performance data to a display station.

9. The computer program product of claim 8 , wherein the computer-readable program, when executed on the computer, further causes the computer to:
group the plurality of data streams corresponding to the plurality of application instances as being associated with the application.

10. The computer program product of claim 8 , wherein to process the plurality of data streams to generate the real-time performance data the computer generates a dynamic application topology, using network traffic data included in the data streams, wherein the dynamic application topology automatically maps resources being used by the application and identifies changes to the application topology as the changes occur.

11. The computer program product of claim 8 , 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 insights across the plurality of entities based on the analyzing, wherein the real-time performance data includes the insights across the plurality of entities.

12. The computer program product of claim 11 , wherein the entities include one or more cloud computing platforms and one or more customers, and wherein the insights across the plurality of entities include comparative insights that compare a performance of one or more aspects of the cloud computing platforms and customers, the aspects including one or more of an application, an infrastructure, a network, an Internet Protocol (IP) service, an operating system, a platform stack, an architecture, and a geographical region.

13. The computer program product of claim 8 , 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
indicate that the event has occurred.

14. The computer program product of claim 13 , wherein to determine the event and to set the threshold include automatically monitoring the data streams over time to determine an application trend and setting the threshold based on the application trend.

15. 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 of a plurality of application instances of an application hosted 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, wherein each of the nodes hosting the application instances includes a server instance in the cloud network;
deploying a meter on the server instance;
capturing, via the meter, the data

Assignees

• Bmc Software Inc

Inventors

• Moon Cliff
• Black Benjamin

Classifications

• G06F11/3006

  where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems (multiprogramming arrangements G06F9/46; allocation of resources G06F9/50) · CPC title

• H04L67/10 Primary

  in which an application is distributed across nodes in the network (software deployment G06F8/60; multiprogramming arrangements G06F9/46) · CPC title

• G06F11/302

  where the computing system component is a software system · CPC title

• G06F2201/805

  Real-time · CPC title

• G06F11/3428

  Benchmarking · CPC title