Generation of microservices from a monolithic application based on runtime traces
摘要
說明書
Model component 108 can learn cluster assignments of classes in the monolithic application and/or graph embeddings of such classes in the monolithic application using causal sequences of one or more causal graphs generated based on the runtime traces that can be produced by executing test cases on the monolithic application as described above. In an example, model component 108 can simultaneously learn such cluster assignments and graph embeddings described above using causal sequences of one or more causal graphs that can be generated (e.g., by second model component 204 as described below with reference to
To facilitate such learning by model component 108 described above, microservice generation system 102 can train model component 108. For example, model component 108 can comprise an artificial intelligence (AI) and/or a machine learning (ML) model such as, for instance, a neural network (e.g., model 400) that can be trained by microservice generation system 102 to learn the cluster assignments and/or graph embeddings described above using the causal sequences of the one or more causal graphs described above. For instance, microservice generation system 102 can train model component 108 to learn the cluster assignments and/or graph embeddings described above by implementing the training procedure described below.
