Method and system for performing intelligent orchestration within a hybrid cloud

Patent metadata

Field	Value
Publication number	US-10880194-B2
Application number	US-201815940501-A
Country	US
Kind code	B2
Filing date	Mar 29, 2018
Priority date	Mar 29, 2018
Publication date	Dec 29, 2020
Grant date	Dec 29, 2020

Abstract

This disclosure relates generally to orchestration, and more particularly to method and system for performing intelligent orchestration within a hybrid cloud environment. In one embodiment, a method of performing intelligent orchestration within a hybrid cloud environment including a plurality of end-point computing devices is disclosed. The method may include monitoring a capacity and an availability of each of the plurality of end-point computing devices, predicting an ability to successfully execute a requested orchestration workflow along with a confidence score, based on the capacity and the availability, by querying an intelligent database that includes historical execution data of past orchestration workflows, and effecting an execution of the requested orchestration workflow based on the ability and the confidence score.

First claim

What is claimed is:

1. A method of performing intelligent orchestration within a hybrid cloud environment comprising a plurality of end-point computing devices, the method comprising:
monitoring, by an orchestration device, a capacity and an availability of each of the plurality of end-point computing devices;
predicting, by the orchestration device, an ability to successfully execute a requested orchestration workflow along with a confidence score, based on the capacity and the availability, by querying an intelligent database that comprises historical execution data of past orchestration workflows, wherein the confidence score is representative of a possibility of completing the requested orchestration workflow, if executed;
effecting, by the orchestration device, an execution of the requested orchestration workflow based on the ability and the confidence score;
building a machine learning model to analyze the intelligent database, and to respond to a query by the orchestration device; and
providing a feedback to a user based on the ability and the confidence score, wherein the feedback comprises a notification of a probable failure in execution of the requested workflow or in execution of the requested workflow as per a service level agreement.

2. The method of claim 1 , wherein predicting comprises predicting the ability to successfully execute the requested orchestration workflow as per a service level agreement.

3. The method of claim 1 , wherein the intelligent database further comprises at least one of historical troubleshooting data to resolve failure of past orchestration workflows, historical network performance data of the hybrid cloud environment, historical performance data of the plurality of end-point computing devices, scheduled maintenance data of the plurality of end-point computing devices, or dynamic performance data of the plurality of end-point computing devices.

4. The method of claim 1 , further comprising storing data with respect to the execution of the requested orchestration workflow in the intelligent database.

5. The method of claim 1 , wherein the hybrid cloud comprises a private cloud that comprises a data center infrastructure.

6. A system for performing intelligent orchestration within a hybrid cloud environment comprising a plurality of end-point computing devices, the system comprising:
an orchestration device comprising at least one processor and a computer-readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
monitoring a capacity and an availability of each of the plurality of end-point computing devices;
predicting an ability to successfully execute a requested orchestration workflow along with a confidence score, based on the capacity and the availability, by querying an intelligent database that comprises historical execution data of past orchestration workflows, wherein the confidence score is representative of a possibility of completing the requested orchestration workflow, if executed;
effecting an execution of the requested orchestration workflow based on the ability and the confidence score;
building a machine learning model to analyze the intelligent database, and to respond to a query by the orchestration device; and
providing a feedback to a user based on the ability and the confidence score, wherein the feedback comprises a notification of a probable failure in execution of the requested workflow or in execution of the requested workflow as per a service level agreement.

7. The system of claim 6 , wherein the intelligent database further comprises at least one of historical troubleshooting data to resolve failure of past orchestration workflows, historical network performance data of the hybrid cloud environment, historical performance data of the plurality of end-point computing devices, scheduled maintenance data of the plurality of end-point computing devices, or dynamic performance data of the plurality of end-point computing devices.

8. The system of claim 6 , wherein the operations further comprise storing data with respect to the execution of the requested orchestration workflow in the intelligent database.

9. A non-transitory computer-readable medium storing computer-executable instructions for:
monitoring a capacity and an availability of each of a plurality of end-point computing devices within a hybrid cloud environment;
predicting an ability to successfully execute a requested orchestration workflow along with a confidence score, based on the capacity and the availability, by querying an intelligent database that comprises historical execution data of past orchestration workflows, wherein the confidence score is representative of a possibility of completing the requested orchestration workflow, if executed;
effecting an execution of the requested orchestration workflow based on the ability and the confidence score;
building a machine learning model to analyze the intelligent database, and to respond to a query by the orchestration device; and
providing a feedback to a user based on the ability and the confidence score, wherein the feedback comprises a notification of a probable failure in execution of the requested workflow or in execution of the requested workflow as per a service level agreement.

10. The non-transitory computer-readable medium of claim 9 , wherein the intelligent database further comprises at least one of historical troubleshooting data to resolve failure of past orchestration workflows, historical network performance data of the hybrid cloud environment, historical performance data of the plurality of end-point computing devices, scheduled maintenance data of the plurality of end-point computing devices, or dynamic performance data of the plurality of end-point computing devices.

11. The non-transitory computer-readable medium of claim 9 , further storing computer-executable instructions for storing data with respect to the execution of the requested orchestration workflow in the intelligent database.

Assignees

• Wipro Ltd

Inventors

• Avdesh Khanna Vijay

Classifications

• G06F9/5072 Primary

  Grid computing · CPC title

• H04L67/10

  in which an application is distributed across nodes in the network (software deployment G06F8/60; multiprogramming arrangements G06F9/46) · CPC title

• H04L43/0876 Primary

  Network utilisation, e.g. volume of load or congestion level · CPC title

• H04L41/5019

  Ensuring fulfilment of SLA · CPC title

• G06F11/008

  Reliability or availability analysis · CPC title