IP Library Granted Patent US 9,459,942
Granted Patent B2
US 9,459,942 · App. 12/870,428 · Granted Oct 4, 2016

Correlation of metrics monitored from a virtual environment

Inventor: Assaf Dagan (Yehud, IL)
Assignee: Hewlett Packard Enterprise Development LP
G06F11/0712G06F11/079G06F11/0754G06F11/301G06F11/3006G06F11/328H04L41/064H04L43/0817
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 9,459,942
App. No.
12/870,428
Filed
Aug 27, 2010
Granted
Oct 4, 2016
Kind
B2
Art Unit
2645
USPC
709/224
Abstract

Correlation of metrics monitored from a virtual environment is described herein. A method for detecting correlations between metrics monitored from a virtual environment includes monitoring network operation metrics of network devices in the virtual environment. Network operation metric irregularities exceeding a threshold are detected. A first network operation metric irregularity is selected from the detected network operation metric irregularities. A time frame of the first network operation metric irregularity is identified for analysis. A second network operation metric irregularity is selected from the detected network operation metric irregularities. The first network operation metric irregularity and the second network operation metric irregularity can be compared to determine a correspondence between the first network operation metric irregularity and the second network operation metric irregularity using a comparison engine and based on a predetermined analysis method.

Claims (46)

1. A method for detecting correlations between metrics monitored from a virtual environment, comprising:

monitoring a plurality of network operation metrics of network devices in the virtual environment;

detecting a plurality of network operation metric irregularities for the network devices exceeding a threshold;

selecting a first network operation metric irregularity from the plurality of network operation metric irregularities;

identifying a time frame of the first network operation metric irregularity for analysis;

selecting a second network operation metric irregularity from the plurality of network operation metric irregularities; and

comparing the first network operation metric irregularity and the second network operation metric irregularity to determine a correspondence between the first network operation metric irregularity and the second network operation metric irregularity using a comparison engine and based on a predetermined analysis method.

2. A method as in claim 1 , further comprising determining a degree of correlation between the first network operation metric irregularity and the second network operation metric irregularity based on the comparing of the first network operation metric irregularity and the second network operation metric irregularity.

3. A method as in claim 1 , wherein the time frame comprises a first time frame and the method further comprises identifying a second time frame of the second network operation metric irregularity for analysis.

4. A method as in claim 3 , wherein analyzing correspondence further comprises chronologically analyzing the correspondence between the first network operation metric irregularity and the second network operation metric irregularity such that a point in the first time frame is compared against a same absolute point in time from the second time frame.

5. A method for correlating network operation metrics monitored from network devices operating in a virtual environment, comprising:

collecting operation data for at least one metric for the network devices using a data collector;

maintaining a time stamp of the operation data using a timer;

monitoring the operation data for operation data exceeding a threshold using a monitoring device;

identifying a metric related to the operation data exceeding the threshold;

creating a list of metrics exceeding the threshold;

selecting a plurality of metrics from the list of metrics for comparison;

identifying a time frame for the comparison from at least one of the plurality of metrics; and

comparing the plurality of metrics for correlation during the time frame identified using a processor.

6. A method as in claim 5 , further comprising:

identifying a start time of when the operation data exceeded the threshold; and

displaying the start time to a user via a display device.

7. A method as in claim 6 , further comprising:

displaying a preview of graphs of the plurality of metrics selected from the list of metrics; and

enabling the user to select at least one of the plurality of metrics for full-view display of a graph simultaneously with the preview of the graphs.

8. A method as in claim 7 , further comprises:

displaying a baseline sleeve of the at least one of the plurality of metrics selected for full-view display in the full-view display; and

enabling the user to graphically identify a time frame on the full-view display for correlation with at least one other of the plurality of metrics.

9. A method as in claim 8 , further comprising:

displaying the metric and a preview of the time frame identified for the metric on the full-view display in a correlation window;

enabling the user to select a correlation method from a plurality of correlation methods;

selecting the at least one other of the plurality of metrics to correlate with metric displayed in the correlation window;

displaying the selected at least one other of the plurality of metrics in a comparison window;

determining a percentage of correlation between the metric displayed in the correlation window and the metric displayed in the comparison window based on a selected correlation method and using a processor; and

displaying the percentage of correlation to the user via the display device.

10. A system for correlating network operation metrics monitored from network devices operating in a virtual environment, comprising:

a problem isolation server in communication with the network devices and configured to receive operation data for at least one metric for the network devices;

a timer configured to maintain a time stamp for the operation data received on the problem isolation server;

a data collector in communication with the problem isolation server configured to collect metric identifications and associated time stamps of operation data breaching a baseline sleeve in a metrics list;

a comparison engine configured to compare operation data from a plurality of metric identifications;

an analysis module configured to analyze the compared operation data from the plurality of metric identifications to determine correlations between the plurality of metric identifications.

11. A system as in claim 10 , further comprising display module configured to graphically display the at least one of the plurality of metric identifications in a network device operation graph and to enable a user to drag one or more selected metrics from the metrics list to a correlation window.

12. A system as in claim 11 , further comprising a baseline module configured to monitor normal network device operation to determine the baseline sleeve and to display the baseline sleeve on the network device operation graph simultaneously with the graphically displayed at least one of the plurality of metric identifications.

13. A system as in claim 12 , further comprising a time slider configured to adjust a time view of the network device operation graph by sliding the time view forward or backward in time, wherein sliding the displayed time view forward or backward comprises redrawing the network device operation graph and the baseline sleeve to accurately depict characteristics of the metric displayed on the network device operation graph during the adjusted time view.

14. A system as in claim 13 , further comprising a graphical time selection module configured to enable graphical selection of one or more time frames from the network device operation graph.

15. A system as in claim 10 , further comprising a ranking module configured to rank the plurality of metric identifications according to a degree of correlation.

Assignments (8)
RELEASE OF SECURITY INTEREST REEL/FRAME 044183/0718 Recorded Feb 2, 2023
From: JPMORGAN CHASE BANK, N.A.
To: MICRO FOCUS LLC (F/K/A ENTIT SOFTWARE LLC); BORLAND SOFTWARE CORPORATION; MICRO FOCUS (US), INC.; SERENA SOFTWARE, INC; ATTACHMATE CORPORATION; MICRO FOCUS SOFTWARE INC. (F/K/A NOVELL, INC.); NETIQ CORPORATION
Reel/Frame 062746/0399 →
RELEASE OF SECURITY INTEREST REEL/FRAME 044183/0577 Recorded Feb 2, 2023
From: JPMORGAN CHASE BANK, N.A.
To: MICRO FOCUS LLC (F/K/A ENTIT SOFTWARE LLC)
Reel/Frame 063560/0001 →
CHANGE OF NAME Recorded Aug 8, 2019
From: ENTIT SOFTWARE LLC
To: MICRO FOCUS LLC
Reel/Frame 050004/0001 →
SECURITY INTEREST Recorded Oct 11, 2017
From: ENTIT SOFTWARE LLC; ARCSIGHT, LLC
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 044183/0577 →
SECURITY INTEREST Recorded Oct 11, 2017
From: ATTACHMATE CORPORATION; BORLAND SOFTWARE CORPORATION; NETIQ CORPORATION; MICRO FOCUS (US), INC.; MICRO FOCUS SOFTWARE, INC.; ENTIT SOFTWARE LLC; ARCSIGHT, LLC; SERENA SOFTWARE, INC.
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 044183/0718 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 9, 2017
From: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
To: ENTIT SOFTWARE LLC
Reel/Frame 042746/0130 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 9, 2015
From: HEWLETT-PACKARD DEVELOPMENT COMPANY, L.P.
To: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Reel/Frame 037079/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 10, 2010
From: DAGAN, ASSAF
To: HEWLETT-PACKARD DEVELOPMENT COMPANY, L.P.
Reel/Frame 024970/0426 →
Continuity (1)
Related Publication 20120054331A1 · Mar 1, 2012