Traffic pattern detection and presentation in container-based cloud computing architecture

• US 10,693,734 B2
• Filed: 12/17/2018
• Issued: 06/23/2020
• Est. Priority Date: 03/04/2016
• Status: Active Grant

• Current Assignee: Vmware LLC (Broadcom, Inc.)
• Original Assignee: VMware, Inc. (Broadcom, Inc.)
• Inventors: Rastogi, Gaurav, Iyer, Sreeram
• Primary Examiner(s): Wasel, Mohamed A.
• Application Number:
  US16/222,843
• Publication Number:
  US 20190123970A1
• Time in Patent Office: 554 Days
• 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 41/0896 Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities flow or congestion control using dynamic resource allocation, e.g. in-call renegotiation, H04L47/76
• CPC Class Codes: H04L 41/12 Discovery or management of network topologies
• CPC Class Codes: H04L 41/122 of virtualised topologies, e.g. software-defined networks [SDN] or network function virtualisation [NFV]
• CPC Class Codes: H04L 41/40 using virtualisation of network functions or resources, e.g. SDN or NFV entities
• CPC Class Codes: H04L 43/04 Processing captured monitoring data, e.g. for logfile generation
• 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 43/20 the monitoring system or the monitored elements being virtualised, abstracted or software-defined entities, e.g. SDN or NFV
• CPC Class Codes: H04L 63/205 involving negotiation or determination of the one or more network security mechanisms to be used, e.g. by negotiation between the client and the server or between peers or by selection according to the capabilities of the entities involved negotiation of communication capabilities H04L69/24
• 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

Abstract

Determining and presenting traffic patterns includes: obtaining a first set of traffic metrics pertaining to network traffic associated with a plurality of containers of a container-based cloud computing platform, wherein: the plurality of containers supports a plurality of microservices; and a microservice has one or more corresponding microservice instances that execute on one or more of the plurality of containers; transforming the first set of traffic metrics into a second set of traffic metrics, the second set of traffic metrics comprising network traffic information pertaining to at least some of the plurality of microservices, the transformation being based at least in part on information pertaining to the plurality of containers and the plurality of microservices supported by the plurality of containers; constructing a microservice map based on the second set of traffic metrics; and outputting the microservice map.

Claims

1. A system, comprising:

one or more processors configured to;

obtain a first set of traffic metrics pertaining to network traffic associated with a plurality of containers of a container-based cloud computing platform, wherein;

the plurality of containers support a plurality of microservices; and

a microservice has one or more corresponding microservice instances that execute in one or more of the plurality of containers;

transform the first set of traffic metrics into a second set of traffic metrics, the second set of traffic metrics comprising network traffic information pertaining to at least some of the plurality of microservices, the transformation being based at least in part on information pertaining to the plurality of containers and the plurality of microservices supported by the plurality of containers;

construct a microservice map based on the second set of traffic metrics; and

output the microservice map; and

one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions.

2. The system of claim 1, wherein the one or more processors are further configured to:

determine a network policy based on the microservice map; and

apply the network policy.

3. The system of claim 1, wherein the one or more processors are further configured to:

determine a network policy based on the microservice map; and

apply the network policy;

wherein

the network policy includes a firewall rule.

4. The system of claim 1, wherein the first set of traffic metrics includes information pertaining to:

a container associated with a corresponding microservice that is supported by the container, a source address associated with a traffic flow, a destination address associated with the traffic flow, and metric data of the traffic flow.

5. The system of claim 1, wherein the first set of traffic metrics is gathered by a plurality of service engines that are distributed on a plurality of host devices and that perform load balancing on traffic sent by instances of the plurality of microservices.

6. The system of claim 1, wherein to transform the first set of traffic metrics into the second set of traffic metrics includes to:

transform the first set of traffic metrics into a set of modified traffic metrics associated with individual microservices of the plurality of microservices; and

aggregate the set of modified traffic metrics according to their respective microservices to generate the second set of traffic metrics;

wherein

the second set of traffic metrics includes microservice-level metrics.

7. The system of claim 1, wherein:

the one or more processors are further configured to receive a request for traffic information pertaining to at least one microservice among the plurality of microservices; and

the request for traffic information includes a time range specification, and the first set of traffic metrics is obtained according to the time range specification.

8. The system of claim 1, wherein the first set of traffic metrics includes a set of container-level metrics, and the second set of traffic metrics includes a set of microservice-level metrics.

9. The system of claim 1, wherein the microservice map includes a directed graph.

10. The system of claim 1, wherein the construction of the microservice map includes performing a breadth-first search.

11. The system of claim 1, wherein the microservice map represents traffic information pertaining to at least some of the plurality of microservices during a specified time period.

12. A method, comprising:

obtaining a first set of traffic metrics pertaining to network traffic associated with a plurality of containers of a container-based cloud computing platform, wherein;

the plurality of containers support a plurality of microservices; and

a microservice has one or more corresponding microservice instances that execute in one or more of the plurality of containers;

transforming the first set of traffic metrics into a second set of traffic metrics, the second set of traffic metrics comprising network traffic information pertaining to at least some of the plurality of microservices, the transformation being based at least in part on information pertaining to the plurality of containers and the plurality of microservices supported by the plurality of containers;

constructing a microservice map based on the second set of traffic metrics; and

outputting the microservice map.

13. The method of claim 12, further comprising:

determining a network policy based on the microservice map; and

applying the network policy.

14. The method of claim 12, further comprising:

determining a network policy based on the microservice map; and

applying the network policy;

wherein

the network policy includes a firewall rule.

15. The method of claim 12, wherein the first set of traffic metrics includes information pertaining to:

a container associated with a corresponding microservice that is supported by the is container, a source address associated with a traffic flow, a destination address associated with the traffic flow, and metric data of the traffic flow.

16. The method of claim 12, wherein the first set of traffic metrics is gathered by a plurality of service engines that are distributed on a plurality of host devices and that perform load balancing on traffic sent by instances of the plurality of microservices.

17. The method of claim 12, wherein the transforming of the first set of traffic metrics into the second set of traffic metrics includes:

transforming the first set of traffic metrics into a set of modified traffic metrics associated with individual microservices of the plurality of microservices; and

aggregating the set of modified traffic metrics according to their respective microservices to generate the second set of traffic metrics;

wherein

a traffic metric in the second set of traffic metrics pertains to network traffic associated with a corresponding microservice.

18. The method of claim 12, further comprising:

receiving a request for traffic information pertaining to at least one microservice among the plurality of microservices; and

wherein the request for traffic information includes a time range specification, and the first set of traffic metrics is obtained according to the time range specification.

19. The method of claim 12, wherein the first set of traffic metrics includes a set of container-level metrics, and the second set of traffic metrics includes a set of microservice-level metrics.

20. The method of claim 12, wherein the microservice map includes a directed graph.

21. The method of claim 12, wherein the construction of the microservice map includes performing a breadth-first search.

22. The method of claim 12, wherein the microservice map represents traffic information pertaining to at least some of the plurality of microservices during a specified time period.

23. A computer program product embodied in a tangible non-transitory computer readable storage medium and comprising computer instructions for:

obtaining a first set of traffic metrics pertaining to network traffic associated with a plurality of containers of a container-based cloud computing platform, wherein;

the plurality of containers support a plurality of microservices; and

a microservice has one or more corresponding microservice instances that execute in one or more of the plurality of containers;

transforming the first set of traffic metrics into a second set of traffic metrics, the second set of traffic metrics comprising network traffic information pertaining to at least some of the plurality of microservices, the transformation being based at least in part on information pertaining to the plurality of containers and the plurality of microservices supported by the plurality of containers;

constructing a microservice map based on the second set of traffic metrics; and

outputting the microservice map.