Discovering and grouping application endpoints in a network environment

• US 9,781,004 B2
• Filed: 10/16/2014
• Issued: 10/03/2017
• Est. Priority Date: 10/16/2014
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Danait, Sachin Waman, Ponnuswamy, Kannan, Lesiak, Paul John
• Primary Examiner(s): Keehn, Richard G
• Assistant Examiner(s): MCADAMS, BRAD
• Application Number:
  US14/516,354
• Publication Number:
  US 20160112270A1
• Time in Patent Office: 1,083 Days
• CPC Class Codes: H04L 41/0853 by actively collecting configuration information or by backing up configuration information
• CPC Class Codes: H04L 41/0893 Assignment of logical groups to network elements
• CPC Class Codes: H04L 41/0894 Policy-based network configuration management
• CPC Class Codes: H04L 41/122 of virtualised topologies, e.g. software-defined networks [SDN] or network function virtualisation [NFV]
• CPC Class Codes: H04L 41/142 using statistical or mathematical methods

Abstract

An example method for discovering and grouping application endpoints in a network environment is provided and includes discovering endpoints communicating in a network environment, calculating affinity between the discovered endpoints, and grouping the endpoints into separate endpoint groups (EPGs) according to the calculated affinity, each EPG comprising a logical grouping of similar endpoints for applying common forwarding and policy logic according to logical application boundaries. In specific embodiments, the affinity includes a weighted average of network affinity, compute affinity and user specified affinity.

Claims

1. A method executed by a network element in network environment, comprising:

discovering endpoints communicating in a network environment;

calculating affinity between the discovered endpoints;

grouping the endpoints into separate endpoint groups (EPGs) according to the calculated affinity, each EPG comprising a logical grouping of similar endpoints for applying common forwarding and policy logic according to logical application boundaries, wherein grouping the endpoints comprises;

creating a peer relationship matrix comprising the discovered endpoints;

sorting the endpoints in the peer relationship matrix according to a total number of connected peers;

selecting a specific endpoint as a seed;

sequentially comparing affinity of the seed with other endpoints in the peer relationship matrix; and

grouping the other endpoints having affinity greater than a predetermined threshold into a same EPG as the seed; and

generating, using the grouped endpoints, application profiles, to allow for stateless network policy definition and enforcement free from dependencies on locality and forwarding.

2. The method of claim 1, wherein the affinity comprises a weighted average of network affinity, compute affinity and user specified affinity.

3. The method of claim 2, wherein the network affinity comprises a percentage of server peers and client peers and associated traffic attributes common between each pair of discovered endpoints.

4. The method of claim 2, wherein the compute affinity comprises a percentage of process and socket attributes common between each pair of discovered endpoints.

5. The method of claim 2, wherein the user specified affinity comprises a percentage of common user specified attributes between each pair of discovered endpoints.

6. The method of claim 1, wherein the EPGs are used to generate application profiles comprising a collection of EPGs, connections among the EPGs, and the policies associated with the connections.

7. The method of claim 1, wherein grouping the endpoints further comprises:

editing the peer relationship matrix to remove the grouped endpoints;

selecting another specific endpoint in the edited peer relationship matrix as a next seed; and

repeating the sequentially comparing affinity, grouping, and selecting the next seed until all endpoints in the peer relationship matrix are grouped into the separate EPGs.

8. The method of claim 1, wherein the endpoints in the peer relationship matrix are sorted in an order according to the total number of connected peers.

9. The method of claim 1, wherein the network element includes a collection engine, a grouping analysis module, and a reporting module, wherein the collection engine securely captures configuration information of the endpoints, wherein the grouping analysis module analyzes communication patters among the endpoints and groups the endpoints, wherein the reporting module arranges grouping results in a user presentable form.

10. A non-transitory tangible media that includes instructions for execution, which when executed by a processor of a network element, is operable to perform operations comprising:

discovering endpoints communicating in a network environment;

calculating affinity between the discovered endpoints;

grouping the endpoints into separate EPGs according to the calculated affinity, each EPG comprising a logical grouping of similar endpoints for applying common forwarding and policy logic according to logical application boundaries, wherein grouping the endpoints comprises;

creating a peer relationship matrix comprising the discovered endpoints;

sorting the endpoints in the peer relationship matrix according to a total number of connected peers;

selecting a specific endpoint as a seed;

sequentially comparing affinity of the seed with other endpoints in the peer relationship matrix; and

grouping the other endpoints having affinity greater than a predetermined threshold into a same EPG as the seed; and

generating, using the grouped endpoints, application profiles, to allow for stateless network policy definition and enforcement free from dependencies on locality and forwarding.

11. The media of claim 10, wherein the affinity comprises a weighted average of network affinity, compute affinity and user specified affinity.

12. The media of claim 10, wherein the EPGs are used to generate application profiles comprising a collection of EPGs, connections among the EPGs, and the policies associated with the connections.

13. The media of claim 10, wherein grouping the endpoints further comprises:

editing the peer relationship matrix to remove the grouped endpoints;

selecting another specific endpoint in the edited peer relationship matrix as a next seed; and

repeating the sequentially comparing affinity, grouping, and selecting the next seed until all endpoints in the peer relationship matrix are grouped into the separate EPGs.

14. An apparatus, comprising:

a collection engine;

a grouping analysis module;

a reporting module;

a memory element for storing data; and

discovering endpoints communicating in a network environment;

calculating affinity between the discovered endpoints;

grouping the endpoints into separate EPGs according to the calculated affinity, each EPG comprising a logical grouping of similar endpoints for applying common forwarding and policy logic according to logical application boundaries, wherein grouping the endpoints comprises;

creating a peer relationship matrix comprising the discovered endpoints;

sorting the endpoints in the peer relationship matrix according to a total number of connected peers;

selecting a specific endpoint as a seed;

sequentially comparing affinity of the seed with other endpoints in the peer relationship matrix; and

grouping the other endpoints having affinity greater than a predetermined threshold into a same EPG as the seed; and

generating, using the grouped endpoints, application profiles, to allow for stateless network policy definition and enforcement free from dependencies on locality and forwarding.

15. The apparatus of claim 14, wherein the affinity comprises a weighted average of network affinity, compute affinity and user specified affinity.

16. The apparatus of claim 14, wherein the EPGs are used to generate application profiles comprising a collection of EPGs, connections among the EPGs, and the policies associated with the connections.

17. The apparatus of claim 14, wherein grouping the endpoints further comprises:

editing the peer relationship matrix to remove the grouped endpoints;

selecting another specific endpoint in the edited peer relationship matrix as a next seed; and

repeating the sequentially comparing affinity, grouping, and selecting the next seed until all endpoints in the peer relationship matrix are grouped into the separate EPGs.