白丝美女被狂躁免费视频网站,500av导航大全精品,yw.193.cnc爆乳尤物未满,97se亚洲综合色区,аⅴ天堂中文在线网官网

Generation of microservices from a monolithic application based on runtime traces

專利號(hào)
US11176027B1
公開日期
2021-11-16
申請(qǐng)人
International Business Machines Corporation（US NY Armonk）
發(fā)明人
Jin Xiao; Anup Kalia; Chen Lin; Raghav Batta; Saurabh Sinha; John Rofrano; Maja Vukovic
IPC分類
G06F11/36; G06F11/32
技術(shù)領(lǐng)域
monolithic,or,runtime,can,model,cluster,causal,traces,generation,classes
地域： NY NY Armonk

摘要

Systems, computer-implemented methods, and computer program products to facilitate generation of microservices from a monolithic application based on runtime traces are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a model component that learns cluster assignments of classes in a monolithic application based on runtime traces of executed test cases. The computer executable components can further comprise a cluster component that employs the model component to generate clusters of the classes based on the cluster assignments to identify one or more microservices of the monolithic application.

說明書

Second model component 204 can comprise a neural network. In an example, second model component 204 can comprise a high-order temporal neural network that can generate one or more causal graphs comprising causal sequences based on the runtime traces defined above with reference to FIG. 1 to capture such first order temporal dependencies and/or high order temporal dependencies described above. For example, second model component 204 can comprise a high-order temporal neural network that can generate one or more causal graphs comprising causal sequences based on the runtime traces defined above with reference to FIG. 1 to capture the temporal relations of the paths and to extrapolate highly related call sequences. In an example, such causal graph(s) and/or causal sequences that can be generated by second model component 204 can be used by microservice generation system 102 to train model component 108 to learn the cluster assignments and/or graph embeddings of a monolithic application as described above with reference to FIG. 1.

Refinement component 206 can refine one or more microservices of a monolithic application based on (e.g., using) data dependency of the monolithic application and/or a static call graph of the monolithic application. For example, the clusters of classes that can be generated by cluster component 110 as described above (e.g., via employing model component 108) can be indicative of one or more microservices of the monolithic application (e.g., one or more potential microservice candidates of the monolithic application) that can be further refined by refinement component 206 as described below based on (e.g., using) data dependency of the monolithic application and/or a static call graph of the monolithic application.

權(quán)利要求

1
微信群二維碼
意見反饋