ABNORMALITY DETECTION IN LOG ENTRY COLLECTION

Log entries and baseline log entries have timestamps, and can be structured over columns of respective data types. Temporal inconsistency can be identified by comparing a probability distribution of time differences between the timestamps of the log entries with a probability distribution of time differences between the timestamps of the baseline log entries. Data type inconsistency can be identified by comparing a data type of each column of the log entries with a data type of a corresponding column of the baseline log entries. Columnar inconsistency can be identified by comparing a number of the columns of the log entries with a number of the columns of the baseline log entries. In response to identification of temporal, data type, and/or columnar inconsistency, that an abnormality exists in collecting the log entries is detected.