IP Library Granted Patent US 11,706,115
Granted Patent B2
US 11,706,115 · App. 17/409,778 · Granted Jul 18, 2023

System and method for using real-time packet data to detect and manage network issues

Inventors: Balachander Chandrasekaran (San Ramon, CA); Anand Srinivas (San Francisco, CA); Murtaza Zafer (San Jose, CA)
Assignee: VMWARE, INC.
H04L43/0882H04L41/142H04L43/0811H04L47/11H04L47/28H04L61/103H04L61/4511H04W8/02H04L43/0817H04L43/0829H04L43/0852H04L61/4523H04L61/5014
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Quick Facts
Patent No.
US 11,706,115
App. No.
17/409,778
Granted
Jul 18, 2023
Kind
B2
Abstract

A system and method is disclosed of extracting information from real-time network packet data to analyze connectivity data for client devices in a network. The method includes: detecting when client devices initiate a connectivity event; after detecting a connectivity event, waiting a period of time for the client device to either reach or fail to reach a network connected state; after waiting a period of time, recording connectivity event information; and sending the recorded connectivity event information to an analytics system for network incident and/or network congestion analysis.

Claims (58)

1. A method for analyzing and remediating network incidents, the method comprising:

executing performance calculations on collected network data to compute performance metrics;

detecting a network incident by using the computed performance metrics to correlate with a sequence of other metrics that are associated with symptoms related to network incidents;

identifying a root cause of the detected network incident,

wherein identifying the root cause comprises aggregating correlations of symptoms across a plurality of network incidents over a duration of time and mapping a set of symptom correlations to root causes; and

identifying, and providing for display, remediation of the identified root cause of the detected network incident.

2. The method of claim 1 , wherein the detected incident comprises a network infrastructure incident relating to one or more network infrastructure elements, and the plurality of network incidents comprises a plurality of network infrastructure incidents relating to a plurality of sets of network infrastructure elements.

3. The method of claim 1 , wherein the detected incident comprises a client network incident relating to a particular client, and the plurality of network incidents comprise a plurality of client network incidents relating to a plurality of clients.

4. The method of claim 1 , wherein using the computed performance metrics comprises detecting a presence of a sequence of metric values.

5. The method of claim 1 , wherein using the computed performance metrics comprises detecting a cyclical presence of a sequence of metric values.

6. A method for analyzing and remediating network incidents, the method comprising:

executing performance calculations on collected network data to compute performance metrics;

detecting a network incident by using the computed performance metrics to correlate with a sequence of other metrics that are associated with symptoms related to network incidents,

wherein using the computed performance metrics comprises detecting a proportion of performance metric values crossing a threshold;

identifying a root cause of the detected network incident; and

identifying, and providing for display, remediation of the identified root cause of the detected network incident.

7. A method for analyzing and remediating network incidents, the method comprising:

executing performance calculations on collected network data to compute performance metrics;

detecting a network incident by using the computed performance metrics to correlate with a sequence of other metrics that are associated with symptoms related to network incidents,

wherein detecting the network incident comprises identifying deviations in historical time-series data computed based on network incidents over a duration of time;

identifying changes in the computed historical time-series data and identifying factors contributing to these changes, wherein the identified factors comprise at least two of configuration changes, topology changes, changes and upgrades of the network elements in the network;

identifying a root cause of the detected network incident; and

identifying, and providing for display, remediation of the identified root cause of the detected network incident.

8. A method for analyzing and remediating network incidents, the method comprising:

executing performance calculations on collected network data to compute performance metrics;

detecting a network incident by using the computed performance metrics to correlate with a sequence of other metrics that are associated with symptoms related to network incidents;

identifying a root cause of the detected network incident; and

identifying, and providing for display, remediation of the identified root cause of the detected network incident,

wherein identifying remediation comprises assigning a priority to the detected network incident, wherein the priority is determined based on at least two of a percentage of affected entities, relative deviation from the historical baseline, and presence of important entities within the affected entities.

9. A non-transitory machine readable medium storing a program which when executed by at least one processing unit analyzes and remediates network incidents, the program comprising sets of instructions for:

executing performance calculations on collected network data to compute performance metrics;

detecting a network incident from the performance calculations on the network data by using the computed performance metrics to correlate with a sequence of other metrics that are associated with symptoms related to network incidents;

identifying a root cause of the detected network incident,

wherein the set of instructions for identifying the root cause comprises a set of instructions for aggregating correlations of symptoms across a plurality of network incidents over a duration of time and mapping a set of symptom correlations to root causes; and

identifying, and providing for display, remediation of the identified root cause of the detected network incident.

10. The non-transitory machine readable medium of claim 9 , wherein the detected incident comprises a network infrastructure incident relating to one or more network infrastructure elements, and the plurality of network incidents comprise a plurality of network infrastructure incidents relating to a plurality of sets of network infrastructure elements.

11. The non-transitory machine readable medium of claim 9 , wherein the detected incident comprises a client network incident relating to a particular client and the plurality of network incidents comprise a plurality of client network incidents relating to a plurality of clients.

12. The non-transitory machine readable medium of claim 9 , wherein the set of instructions for using the computed performance metrics comprises a set of instructions for detecting a presence of a sequence of metric values.

13. The non-transitory machine readable medium of claim 9 , wherein the set of instructions for using the computed performance metrics comprises a set of instructions for detecting a cyclical presence of a sequence of metric values.

14. A non-transitory machine readable medium storing a program which when executed by at least one processing unit analyzes and remediates network incidents, the program comprising sets of instructions for:

executing performance calculations on collected network data to compute performance metrics;

detecting a network incident from the performance calculations on the network data by using the computed performance metrics to correlate with a sequence of other metrics that are associated with symptoms related to network incidents;

wherein using the computed performance metrics comprises detecting a proportion of performance metric values crossing a threshold;

identifying a root cause of the detected network incident; and

identifying, and providing for display, remediation of the identified root cause of the detected network incident.

15. A non-transitory machine readable medium storing a program which when executed by at least one processing unit analyzes and remediates network incidents, the program comprising sets of instructions for:

executing performance calculations on collected network data to compute performance metrics;

detecting a network incident from the performance calculations on the network data by correlating a sequence of performance metrics with other composite metrics that define relevant symptoms,

wherein detecting the network incident comprises identifying deviations in historical time-series data computed based on network incidents over a duration of time,

wherein detecting the network incident further comprises identifying changes in the computed historical time-series data and identifying factors contributing to these changes, wherein the identified factors comprise at least two of configuration changes, topology changes, changes and upgrades of the network elements in the network;

identifying a root cause of the detected network incident; and

identifying, and providing for display, remediation of the identified root cause of the detected network incident.

16. A non-transitory machine readable medium storing a program which when executed by at least one processing unit analyzes and remediates network incidents, the program comprising sets of instructions for:

executing performance calculations on collected network data to compute performance metrics;

detecting a network incident from the performance calculations on the network data by correlating a sequence of performance metrics with other composite metrics that define relevant symptoms;

identifying a root cause of the detected network incident; and

identifying, and providing for display, remediation of the identified root cause of the detected network incident,

wherein the set of instructions for identifying remediation comprises a set of instructions for assigning a priority to the detected network incident, wherein the priority is determined based on at least two of a percentage of affected entities, relative deviation from the historical baseline, and presence of important entities within the affected entities.

Assignments (1)
CHANGE OF NAME Recorded Apr 15, 2024
From: VMWARE, INC.
To: VMWARE LLC
Reel/Frame 067102/0395 →