Microservice catalog generation and inference based selection of microservices

A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed in a data processing system, causes the data processing system to:

• generate a plurality of application graph data structures, wherein each node in an application graph data structure specifies a corresponding microservice and has corresponding microservice attribute information, and wherein each edge between nodes in the application graph data structure specifies a microservice functionality between microservices of nodes connected by the edge;
• execute a data transformation operation on the application graph data structures to generate, for each node in each application graph data structure, a corresponding microservice document specifying microservice attributes of the corresponding microservice;
• execute a machine learning training operation on an embedding computer model based on a plurality of the microservice documents, wherein the machine learning training operation trains the embedding computer model to learn a representation vector space for representing microservices as vector representations;
• execute the trained embedding computer model on the plurality of microservice documents to generate corresponding vector representations;
• compile the vector representations into entries of a microservice index data structure;
• and
• process queries for microservices based on the vector representations in the entries of the microservice index data structure.

An apparatus comprising:

• at least one processor;
• and
• at least one memory coupled to the at least one processor, wherein the at least one memory comprises instructions which, when executed by the at least one processor, cause the at least one processor to:
• generate a plurality of application graph data structures, wherein each node in an application graph data structure specifies a corresponding microservice and has corresponding microservice attribute information, and wherein each edge between nodes in the application graph data structure specifies a microservice functionality between microservices of nodes connected by the edge;
• execute a data transformation operation on the application graph data structures to generate, for each node in each application graph data structure, a corresponding microservice document specifying microservice attributes of the corresponding microservice;
• execute a machine learning training operation on an embedding computer model based on a plurality of the microservice documents, wherein the machine learning training operation trains the embedding computer model to learn a representation vector space for representing microservices as vector representations;
• execute the trained embedding computer model on the plurality of microservice documents to generate corresponding vector representations;
• compile the vector representations into entries of a microservice index data structure;
• and
• process queries for microservices based on the vector representations in the entries of the microservice index data structure.