CPC G06N 5/04 (2013.01) [G06N 20/00 (2019.01)] | 19 Claims |
1. A method for implementing microservices using a shiftleft topology construction, the method comprises:
determining, based on collected datasets, operational characteristics associated with different microservices in a microservice framework to create predictive results for constructing topologies for the different microservices, wherein the determining further comprises training and using a machine learning model to retrieve the collected datasets and learn the operational characteristics;
extracting topological entities from the collected datasets using the machine learning (ML) model, wherein extracting the topological entities includes using machine learning algorithms associated with the machine learning model to identify keywords and topics that are distributed among the collected datasets and to determine pertinent topics among the identified topics associated with the different microservices;
correlating a plurality of data from the topological entities, wherein the correlating further comprises matching a same topological entity from a plurality of different sources associated with the collected datasets and identifying a correlation of the topological entities between the different microservices and to application program interface (API) routes;
mapping the topological entities, wherein the mapping further comprises mapping the topological entities to source code and identifying relationships from the mapped topological entities;
marking entry points for a plurality of subgraphs of the topological entities;
based on the correlating, the mapping, and the marking of the entry points for the topological entities, constructing an entire topology graph using the machine learning model, wherein nodes represent service endpoints and edges represent dependencies between the service endpoints; and
implementing the microservices using the constructed entire topology graph, wherein the implementing further comprises using the machine learning model to detect changes to the microservices based on updated datasets, updating the constructed entire topology graph based on the updated datasets, and subsequently predicting construction of other entire topology graphs and dependencies between the microservices.
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