公开(公告)号：US20210073656A1

公开(公告)日：2021-03-11

申请号：US16561164

申请日：2019-09-05

Applicant: International Business Machines Corporation

Inventor： Tian Ming Pan ,  Bo Chen Zhu ,  Peng Fei Tian ,  Chu Yun Tong ,  Dan Hui Fan

IPC: G06N5/04 ,  G06N20/00

Abstract: Aspects of the invention include a computer-implemented method by executing, via a processor, a bottleneck model training process for microservices in a microservice system, wherein for each of the microservices the bottleneck model training process filters out a subset of training data based at least in part on a current situation setting. Building, via the processor, a bottleneck indicator model for each of the microservices using information from the bottleneck model training process, convergence points for an expected response time. Executing, via the processor, a bottleneck identification process for providing system alerts when a bottleneck is identified, wherein the bottleneck identification process uses analysis to monitor a data stream according to the bottleneck indicator model which uses the convergence points for response times.

公开(公告)号：US20210064507A1

公开(公告)日：2021-03-04

申请号：US16550472

申请日：2019-08-26

Applicant: International Business Machines Corporation

Inventor： Al Chakra ,  Tian Ming Pan ,  Peng Fei Tian ,  Chu Yun Tong ,  Fan Zhang ,  Cheng Fang Wang ,  Bo Chen Zhu

IPC: G06F11/34 ,  G06K9/62

Abstract: Aspects of the invention include detecting and predicting application performance. A non-limiting example computer-implemented method includes receiving source code and generating a first model of the source code by labeling a word of the source code. The computer implemented method optimizes the first model of the source code by assembling the first model of the source code with a plurality of models generated by a model generation module into a second model of the source code and extracts at least two basic features from the second model of the source code. The computer-implemented method provides an estimated performance of the source code based on historical data of the basic features extracted from the second model of the source code.