Autonomous cloud design and control

Patent metadata

Field	Value
Publication number	US-11539581-B2
Application number	US-201816113826-A
Country	US
Kind code	B2
Filing date	Aug 27, 2018
Priority date	Aug 27, 2018
Publication date	Dec 27, 2022
Grant date	Dec 27, 2022

Abstract

The autonomous cloud design system may determine a design that may appropriately mix emerging technologies and operations to provide a versatile and cost-effective or efficient solution for a given cloud site.

First claim

What is claimed:

1. A server comprising:
a processor; and
a memory coupled with the processor, the memory comprising executable instructions that when executed by the processor facilitate performance of operations comprising:
obtaining a network design template;
obtaining space and power constraints for use in design of a network site, wherein the network design template is provided by a template engine in communication with the processor, wherein the template engine obtains definitions of network faults and actions, the actions including a closed loop control procedure to resolve at least one of the network faults;
based on the network design template, space constraints, and power constraints, creating a plurality of candidate site designs based on a machine learning cycle that optimizes design options used to create the plurality of candidate site designs;
based on a first site design of the plurality of candidate site designs being within a threshold cost, selecting the first site design, wherein the threshold cost comprises cost information for a power cost and wherein the threshold cost is a determined maximum power cost to operate the network in accordance with the first site design;
sending instructions to automatically implement the first site design by initiating an automated site build plan, the initiating based on a predetermined trigger, resulting in a first site;
monitoring the first site;
determining that a first performance of the first site is below a performance threshold;
based on the determining, automatically generating a second site design; and
determining that the second site design provides a second performance meeting the performance threshold.

2. The server of claim 1 , the operations further comprising:
updating the network design template to an updated network design template,
wherein the second site design is based on the updated network design template.

3. The server of claim 2 , wherein the performance threshold may be based on amount of errors within a period.

4. The server of claim 1 , wherein the network design template further comprises leaf switch type or number of leaf switches.

5. The server of claim 1 , the operations further comprising based on the first site design of the plurality of candidate site designs being within the threshold cost, providing instructions to generate a 3D generated model of the first site design.

6. The server of claim 1 , the operations further comprising displaying an interactive 3D virtual model of the first site design.

7. The server of claim 1 , wherein the machine learning cycle improves creating the plurality of candidate site designs using previous site installation information and technology cost trend information.

8. A method comprising:
obtaining, by a processing system including a processor, a network design template;
obtaining, by the processing system, space and power constraints for use in design of a network site, wherein the network design template is provided by a template engine in communication with the processing system, wherein the template engine obtains definitions of network faults and actions, the actions including a closed loop control procedure to resolve at least one of the network faults;
based on the network design template, space constraints, and power constraints, creating, by the processing system, a plurality of candidate site designs based on a machine learning cycle that optimizes design options used to create the plurality of candidate site designs;
based on a first site design of the plurality of candidate site designs being within a threshold cost, selecting, by the processing system, the first site design, wherein the threshold cost comprises cost information for a power cost, and wherein the threshold cost is a determined maximum power cost to operate the network in accordance with the first site design;
sending, by the processing system, instructions to automatically implement the first site design by initiating an automated site build plan, the initiating based on a predetermined trigger, resulting in a first site;
monitoring, by the processing system, the first site;
determining, by the processing system, that a first performance of the first site is below a performance threshold;
automatically generating, by the processing system based on the determining, a second site design; and
determining, by the processing system, that the second site design provides a second performance meeting the performance threshold.

9. The method of claim 8 , further comprising:
updating, by the processing system, the network design template to an updated network design template,
wherein the second site design is based on the updated network design template.

10. The method of claim 9 , wherein the performance threshold may be based on amount of errors within a period.

11. The method of claim 8 , wherein the network design template comprises number of compute resources or type of compute resources.

12. The method of claim 8 , wherein the network design template comprises number of leaf switches.

13. The method of claim 8 , further comprising:
based on the first site design of the plurality of candidate site designs being within the threshold cost, providing, by the processing system, instructions to generate a 3D generated model of the first site design.

14. The method of claim 8 , further comprising displaying, by the processing system, an interactive 3D virtual model of the first site design.

15. A non-transitory machine-readable medium comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations comprising:
obtaining a network design template;
obtaining space and power constraints for use in designing a network site, wherein the network design template is provided by a template engine in communication with the processing system, wherein the template engine obtains definitions of network faults and actions, the actions including a closed loop control procedure to resolve at least one of the network faults;
based on the network design template, space constraints, and power constraints, creating a plurality of candidate site designs based on a machine learning cycle that optimizes design options used to create the plurality of candidate site designs;
based on a first site design of the plurality of candidate site designs being within a threshold cost, selecting the first site design, wherein the threshold cost is a determined maximum power cost to operate the network in accordance with the first site design;
sending instructions to automatically implement the first site design by initiating an automated site build plan, the initiating based on a predetermined trigger, resulting in a first site;
monitoring the first site;
determining that a first performance of the first site is below a performance threshold;
based on the determining, automatically generating a second site design; and
determining that the second site design provides a second performance meeting the performance threshold.

16. The non-transitory machine-readable medium of claim 15 , the operations further comprising:
updating the network design template to an updated network design template, wherein the performance threshold may be based on amount of errors within a period, and wherein the second site design is based on the updated network design template.

17. The non-transitory machine-readable medium of claim 15 , wherein the network design template comprises type of compute resources.

Assignees

• At & T Ip I Lp

Inventors

• Dome George
• Oetting John
• Chen Chuxin

Classifications

• H04L41/5025

  by proactively reacting to service quality change, e.g. by reconfiguration after service quality degradation or upgrade · CPC title

• G06T19/006

  Mixed reality (object pose determination, tracking or camera calibration for mixed reality G06T7/00) · CPC title

• H04L41/145 Primary

  involving simulating, designing, planning or modelling of a network · CPC title

• H04L41/5054

  Automatic deployment of services triggered by the service manager, e.g. service implementation by automatic configuration of network components · CPC title

• H04L41/5096

  wherein the managed service relates to distributed or central networked applications · CPC title