Log representation learning for automated system maintenance

A system, comprising:

• a memory device;
• and
• one or more processor devices operatively coupled with the memory device to:
• transform collected system logs into log templates using an optimized parser;
• tokenize the log templates partitioned into time windows to obtain log template tokens;
• train a language model (LM) with deep learning using the log template tokens to obtain a trained LM;
• detect anomalies from system logs using the trained LM to obtain detected anomalies;
• and
• perform a corrective action to a monitored entity based on the detected anomalies.

A non-transitory computer program product comprising a computer-readable storage medium including program code for log representation learning for automated system maintenance, wherein the program code when executed on a computer causes the computer to:

• transform collected system logs into log templates using an optimized parser;
• tokenize the log templates partitioned into time windows to obtain log template tokens;
• train a language model (LM) with deep learning using the log template tokens to obtain a trained LM;
• detect anomalies from system logs using the trained LM to obtain detected anomalies;
• and
• perform a corrective action to a monitored entity based on the detected anomalies.