Root-Cause Diagnosis Using Logs Generated by User Actions
Hiroki Ikeuchi, Akio Watanabe, Takehiro Kawata, Ryoichi Kawahara · 2018
Identifying the root cause of failures in a complicated communication system such as a cloud platform is time-consuming for system operators. Although most current diagnosis methods depend on logs that are observed passively, some failures generate quite similar logs and cannot be distinguished from one another with these methods. To overcome this difficulty, we propose a framework in which operators execute user actions and use logs generated by the actions in root-cause analysis. We focus on the fact that even if we do not see any differences between failures in logs observed passively, logs generated by a particular action may change depending on the failure. We also propose two methods for executing such effective actions in a proper order and obtaining informative logs efficiently. With these methods, we can identify the root cause of failures that are indistinguishable with current methods. We experimentally evaluated the effectiveness of our framework in a cloud system constructed with OpenStack.