This project provides a series of functions to analyze system log data in terms of event causality.

• Classify log data with its output format
• Generate DAG with PC algorithm (using pcalg/gsq package)
• Process log incrementally and notify troubles <- work in progress

• pcalg https://github.com/keiichishima/pcalg
• gsq https://github.com/keiichishima/gsq

You can generate pseudo log dataset for testing functions.

$ python testlog.py > test.temp

First, you need to put a configuration file for whole system. Copy default file, and edit it if necessary.

$ cp config.conf.default config.conf

Then classify dataset and register them with database. Classification works with log template generation inside this command.

$ python log_db.py

You can see log templates found in log messages with following command.

$ python lt_edit.py show

If found log template do not make reasonable event group, Following command may be useful.

$ python lt_edit.py [breakdown, merge, separate]

Finally analyze causal relations generating DAG. (This step requires much time. If your machine have enough performance, we recommend you to use -p options for multithreading.)

$ python pc_log.py

You can check result DAG with following command.

$ python pcresult.py -g graph.pdf pc_output/all_21120901