Electronic system for dynamically orchestrating application programming interface calls using quantum computing

A computer program product for dynamically orchestrating application programming interface (API) calls using quantum computing, the computer program product comprising a non-transitory computer-readable medium comprising code causing a first apparatus to:

• receive API calls from clients;
• determine, using a first machine learning model, whether each API call of the API calls is acceptable to obtain acceptable API calls, wherein the first machine learning model is trained using a first quantum computing engine;
• determine, using a second machine learning model, whether each acceptable API call of the acceptable API calls is combinable with another acceptable API call of the acceptable API calls to obtain API call categories, wherein each API call category of the API call categories comprises combinable API calls, and wherein the second machine learning model is trained using a second quantum computing engine;
• determine, using a third machine learning model, whether to route each API call category of the API call categories to a cache or to an endpoint, wherein the third machine learning model is trained using a third quantum computing engine;
• obtain, based on determining to route an API call category of the API call categories to the cache, data from the endpoint, wherein the data comprises responses of the endpoint to the acceptable API calls of the API call category;
• determine, based on determining to route the API call category to the cache and using a fourth machine learning model, a time-to-live for maintaining the data in the cache for the API call category, wherein the fourth machine learning model is trained using a fourth quantum computing engine;
• and
• provide, based on the data in the cache, responses to the acceptable API calls of the API call category.

A method for dynamically orchestrating application programming interface (API) calls using quantum computing, the method comprising:

• receiving API calls from clients;
• determining, using a first machine learning model, whether each API call of the API calls is acceptable to obtain acceptable API calls, wherein the first machine learning model is trained using a first quantum computing engine;
• determining, using a second machine learning model, whether each acceptable API call of the acceptable API calls is combinable with another acceptable API call of the acceptable API calls to obtain API call categories, wherein each API call category of the API call categories comprises combinable API calls, and wherein the second machine learning model is trained using a second quantum computing engine;
• determining, using a third machine learning model, whether to route each API call category of the API call categories to a cache or to an endpoint, wherein the third machine learning model is trained using a third quantum computing engine;
• obtaining, based on determining to route an API call category of the API call categories to the cache, data from the endpoint, wherein the data comprises responses of the endpoint to the acceptable API calls of the API call category;
• determining, based on determining to route the API call category to the cache and using a fourth machine learning model, a time-to-live for maintaining the data in the cache for the API call category, wherein the fourth machine learning model is trained using a fourth quantum computing engine;
• and
• providing, based on the data in the cache, responses to the acceptable API calls of the API call category.