Software logistic for learning applications
Implementations of the present disclosure include methods, systems, and computer-readable storage mediums for concurrent production use of an application and training of a modified application. Actions include receiving a change request that provides at least one application change for an application executed by a production system, retrieving, from the production system, a portion of production data associated to the at least one application change, executing training of a model of the application using the one or more production data to generate a trained model of the application, testing the trained model of the application to generate test results, extending the change request by adding the trained model, and providing, by the production system, the extended change request to deploy the at least one application change and the trained model to the production system.
1. A computer-implemented method for concurrent production use of an application and training of a modified application, the method being executed using one or more processors and comprising:
receiving, by the one or more processors, a change request that provides at least one application change for an application executed by a production system;
retrieving, by the one or more processors from the production system, a portion of production data associated to the at least one application change;
executing, by the one or more processors, training of a model of the application using the portion of production data to generate a trained model of the application;
testing, by the one or more processors, the trained model of the application to generate test results;
generating, by the one or more processors, based on the test results an extended change request comprising the trained model; and
providing, by the one or more processors to the production system, the extended change request to deploy the at least one application change and the trained model to the production system.
2. The computer-implemented method of claim 1 , wherein the portion of the production data associated to the at least one application change is smaller than a whole set of the production data.
3. The computer-implemented method of claim 1 , wherein the portion of the production data is selected from a production database of the production system based on a comparison to old production data previously stored in a training database of a training system.
4. The computer-implemented method of claim 1 , wherein retrieving the portion of the production data comprises reformatting the portion of the production data.
5. The computer-implemented method of claim 1 , wherein concurrent execution of the training of the model of the application is performed without interfering with production use of the application.
6. The computer-implemented method of claim 1 , wherein the change request comprises a change to at least one of a model configuration and a model software.
7. The computer-implemented method of claim 1 , further comprising:
determining, by the one or more processors, an accuracy of the trained model of the application;
comparing, by the one or more processors, the accuracy to a set threshold; and
in response to determining that the accuracy exceeds the set threshold, testing, by the one or more processors, the trained model of the application to generate test results.
8. A non-transitory computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for concurrent production use of an application and training of a modified application, the operations comprising:
receiving a change request that provides at least one application change for an application executed by a production system;
retrieving, from the production system, a portion of production data associated to the at least one application change;
executing training of a model of the application using the portion of production data to generate a trained model of the application;
testing the trained model of the application to generate test results;
generating an extended change request comprising the trained model; and
providing, by the production system, the extended change request to deploy the at least one application change and the trained model to the production system.
9. The non-transitory computer-readable storage medium of claim 8 , wherein the portion of the production data associated to the at least one application change is smaller than a whole set of the production data.
10. The non-transitory computer-readable storage medium of claim 8 , wherein the portion of the production data is selected from a production database of the production system based on a comparison to old production data previously stored in a training database of a training system.
11. The non-transitory computer-readable storage medium of claim 8 , wherein retrieving the portion of the production data comprises reformatting the portion of the production data.
12. The non-transitory computer-readable storage medium of claim 8 , wherein concurrent execution of the training of the model of the application is performed without interfering with production use of the application.
13. The non-transitory computer-readable storage medium of claim 8 , wherein the change request comprises a change to at least one of a model configuration and a model software.
14. The non-transitory computer-readable storage medium of claim 8 , wherein operations further comprise:
determining an accuracy of the trained model of the application;
comparing the accuracy to a set threshold; and
in response to determining that the accuracy exceeds the set threshold, testing the trained model of the application to generate test results.
15. A computer-implemented system, comprising:
a client-side computing device; and
a computer-readable storage device coupled to the client-side computing device and having instructions stored thereon which, when executed by the client-side computing device, cause the client-side computing device to perform operations for concurrent production use of an application and training of a modified application, the operations comprising:
receiving a change request that provides at least one application change for an application executed by a production system;
retrieving, from the production system, a portion of production data associated to the at least one application change;
executing training of a model of the application using the portion of production data to generate a trained model of the application;
testing the trained model of the application to generate test results;
generating an extended change request by adding the trained model; and
providing, by the production system, the extended change request to deploy the at least one application change and the trained model to the production system.
16. The computer-implemented system of claim 15 , wherein the portion of the production data associated to the at least one application change is smaller than a whole set of the production data.
17. The computer-implemented system of claim 15 , wherein the portion of the production data is selected from a production database of the production system based on a comparison to old production data previously stored in a training database of a training system.
18. The computer-implemented system of claim 15 , wherein retrieving the portion of the production data comprises reformatting the portion of the production data.
19. The computer-implemented system of claim 15 , wherein concurrent execution of the training of the model of the application is performed without interfering with production use of the application.
20. The computer-implemented system of claim 19 , wherein the change request comprises a change to at least one of a model configuration and a model software.