Intelligent logging of microservice failures

A computer system for intelligent logging of microservice failures, the computer system comprising:

• a communication fabric;
• a storage device connected to the communication fabric, wherein the storage device stores program instructions;
• and
• a processor connected to the communication fabric, wherein the processor executes the program instructions to:
• generate, using a rule-based classifier, a classification decision tree based on a plurality of features corresponding to transactions corresponding to an application comprised of a set of microservices in a microservice chain;
• remove a set of features having low importance for the transactions from the classification decision tree using weakest link weight-based pruning to increase accuracy of failure risk classifications by the rule-based classifier;
• reduce variance in predictions for microservice failures for particular failure types by the rule-based classifier utilizing a bagging technique and a boosting technique on the rule-based classifier;
• predict, using the rule-based classifier, that failure of a microservice in the microservice chain will occur during a predicted high-risk failure period for a predicted failure type while performing a transaction corresponding to the application;
• determine a detailed logging level for the microservice to record sufficient information to identify a root cause of the failure of the microservice for the predicted failure type;
• and
• direct the microservice to increase a current logging level of the microservice to the detailed logging level during the predicted high-risk failure period to record sufficient information to identify the root cause of the failure of the microservice.

A computer program product for intelligent logging of microservice failures, the computer program product comprising a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method of:

• generating, by the computer, using a rule-based classifier, a classification decision tree based on a plurality of features corresponding to transactions corresponding to an application comprised of a set of microservices in a microservice chain;
• removing, by the computer, a set of features having low importance for the transactions from the classification decision tree using weakest link weight-based pruning to increase accuracy of failure risk classifications by the rule-based classifier;
• reducing, by the computer, variance in predictions for microservice failures for particular failure types by the rule-based classifier utilizing a bagging technique and a boosting technique on the rule-based classifier;
• predicting, by the computer, using the rule-based classifier, that failure of a microservice in the microservice chain will occur during a predicted high-risk failure period for a predicted failure type while performing a transaction corresponding to the application;
• determining, by the computer, a detailed logging level for the microservice to record sufficient information to identify a root cause of the failure of the microservice for the predicted failure type;
• and
• directing, by the computer, the microservice to increase a current logging level of the microservice to the detailed logging level during the predicted high-risk failure period to record sufficient information to identify the root cause of the failure of the microservice.