Model management using containers

A system comprising:

• a network;
• one or more processors;
• and
• a memory storing instructions that, when executed by at least one processor among the one or more processors, cause the at least one processor to perform operations comprising:
• receiving a first request to deploy a first machine learning model, the first request including information indicating an identifier associated with the first machine learning model;
• determining, based at least in part on the first machine learning model, a set of dependent machine learning models;
• comparing computing resource requirements of the first machine learning model and the set of dependent machine learning models with available computing resources of a set of candidate clusters configured for execution of different machine learning models;
• selecting, from a set of candidate clusters, a first container environment comprising at least one cluster of the set of candidate clusters to deploy the first machine learning model and the set of dependent machine learning models, wherein the selection is based on an amount of computing resources associated with this deployment;
• and
• based on the selected first container environment, executing an instance of an application in the selected first container environment, the first machine learning model and the set of dependent machine learning models being deployed as part of the instance of the application.

A non-transitory machine-readable medium comprising instructions which, when read by a machine, cause the machine to perform operations comprising:

• receiving a first request to deploy a first machine learning model, the first request including information indicating an identifier associated with the first machine learning model;
• determining, based at least in part on the first machine learning model, a set of dependent machine learning models;
• comparing computing resource requirements of the first machine learning model and the set of dependent machine learning models with available computing resources of a set of candidate clusters configured for execution of different machine learning models;
• selecting, from a set of candidate clusters, a first container environment comprising at least one cluster of the set of candidate clusters to deploy the first machine learning model and the set of dependent machine learning models, wherein the selection is based on an amount of computing resources associated with this deployment;
• and
• based on the selected first container environment, executing an instance of an application in the selected first container environment, the first machine learning model and the set of dependent machine learning models being deployed as part of the instance of the application.