Infrastructure integration framework and migration system
Various aspects of the disclosure relate to infrastructure integration and migration of computing services between different computing infrastructure platforms. A system may utilize artificial intelligence (AI) and/or machine learning (ML) models configured to resolve a problem with allocating services between a monolithic infrastructure and one or more cloud computing systems. The infrastructure integration framework and migration system gathers data from a plurality of sources and consolidating the results in a central database. The infrastructure integration framework and migration system analyzes existing architecture operation of the enterprise network to gather information to be stored in the central database. The AI and/or ML models may be trained using the cloud system information and/or the existing architecture information. Automated predictions are ranked and migration may automatically be initiate by the infrastructure integration framework and migration system when certain threshold conditions are met.
1. A system comprising:
a first computing infrastructure system local to an enterprise network and processing a service;
a second computing infrastructure system communicatively coupled to the enterprise network; and
an infrastructure integration framework and migration system comprising:
a processor; and
memory storing computer-readable instructions that, when executed by the at processor, cause the infrastructure integration framework and migration system to:
aggregate service parameter values for each parameter of a plurality of service parameters corresponding to operation of the service within a current computing environment;
generate, via a machine learning model, predicted parameter values for each of the plurality of service parameters corresponding to a monolithic computing infrastructure operating the service;
generate, via a rules-based model, predicted parameter values for each of the plurality of service parameters corresponding to a monolithic computing infrastructure operating the service; and
initiate, automatically based on each predicted parameter value meeting a predetermined threshold, migration of the service from the first computing infrastructure system to the second computing infrastructure system.
2. The system of claim 1 , wherein the service parameter values comprise two or more of a lowest cost parameter threshold, a lowest computational power use parameter threshold, a computational efficiency parameter threshold, a communication speed parameter threshold, and a latency parameter threshold.
3. The system of claim 1 , wherein the machine learning model comprises a combination of an adaboosting model and a random forest model.
4. The system of claim 3 , wherein output of the adaboosting model and the random forest model is stacked and ranked.
5. The system of claim 1 , wherein the first computing infrastructure system is a monolithic computing infrastructure and the second computing infrastructure system is a cloud computing infrastructure.
6. The system of claim 1 , wherein the first computing infrastructure system is a cloud computing infrastructure and the second computing infrastructure system is a monolithic computing infrastructure.
7. The system of claim 6 , wherein the instructions cause the infrastructure integration framework and migration system to present, via a user interface device, a ranked presentation of computing infrastructure environments.
8. A method comprising:
aggregating service parameter values for each parameter of a plurality of service parameters corresponding to operation of a service within a current computing environment;
generating, via a machine learning model, predicted parameter values for each of the plurality of service parameters corresponding to a monolithic computing infrastructure operating the service;
generating, via a rules-based model, predicted parameter values for each of the plurality of service parameters corresponding to a monolithic computing infrastructure operating the service; and
initiating, automatically based on each predicted parameter value meeting a predetermined threshold, migration of the service from a first computing infrastructure system to a second computing infrastructure system.
9. The method of claim 8 , wherein the service parameter values comprise two or more of a lowest cost parameter threshold, a lowest computational power use parameter threshold, a computational efficiency parameter threshold, a communication speed parameter threshold, and a latency parameter threshold.
10. The method of claim 8 , wherein the machine learning model comprises a combination of an adaboosting model and a random forest model.
11. The method of claim 10 , wherein output of the adaboosting model and the random forest model is stacked and ranked.
12. The method of claim 8 , wherein the first computing infrastructure system is a monolithic computing infrastructure and the second computing infrastructure system is a cloud computing infrastructure.
13. The method of claim 8 , further comprising presenting, via a user interface device, a ranked presentation of computing infrastructure environments.
14. The system of claim 1 , wherein the first computing infrastructure system is a cloud computing infrastructure and the second computing infrastructure system is a monolithic computing infrastructure.
15. An infrastructure integration framework and migration system comprising:
a processor; and
memory storing computer-readable instructions that, when executed by the at processor, cause the infrastructure integration framework and migration system to:
aggregate service parameter values for each parameter of a plurality of service parameters corresponding to operation of a service within a current computing environment;
generate, via a machine learning model, predicted parameter values for each of the plurality of service parameters corresponding to a monolithic computing infrastructure operating the service;
generate, via a rules-based model, predicted parameter values for each of the plurality of service parameters corresponding to a monolithic computing infrastructure operating the service; and
initiate, automatically based on each predicted parameter value meeting a predetermined threshold, migration of the service from a first computing infrastructure system to a second computing infrastructure system.
16. The infrastructure integration framework and migration system of claim 15 , wherein the service parameter values comprise two or more of a lowest cost parameter threshold, a lowest computational power use parameter threshold, a computational efficiency parameter threshold, a communication speed parameter threshold, and a latency parameter threshold.
17. The infrastructure integration framework and migration system of claim 15 , wherein the machine learning model comprises a combination of an adaboosting model and a random forest model.
18. The infrastructure integration framework and migration system of claim 17 , wherein output of the adaboosting model and the random forest model is stacked and ranked.
19. The infrastructure integration framework and migration system of claim 15 , wherein the first computing infrastructure system is a monolithic computing infrastructure and the second computing infrastructure system is a cloud computing infrastructure.
20. The infrastructure integration framework and migration system of claim 15 , wherein the instructions cause the infrastructure integration framework and migration system to present, via a user interface device, a ranked presentation of computing infrastructure environments.