  Logs are one of the most critical data for service management. It contains
rich runtime information for both services and users. Since size of logs are
often enormous in size and have free handwritten constructions, a typical
log-based analysis needs to parse logs into structured format first. However,
we observe that most existing log parsing methods cannot parse logs online,
which is essential for online services. In this paper, we present an automatic
online log parsing method, name as LogStamp. We extensively evaluate LogStamp
on five public datasets to demonstrate the effectiveness of our proposed
method. The experiments show that our proposed method can achieve high accuracy
with only a small portion of the training set. For example, it can achieve an
average accuracy of 0.956 when using only 10% of the data training.
