GCGC uses a Jupyter notebook interface to analyze GC log files.
There are 17 generated plots, which analyze latency, concurrent and STW events, heap information, allocation rates, frequencies of events, and event summaries, comparing any number of log files and external data sources. The tool uses Jupyter notebook data visualization allows for easy customization of provided plots.
The analysis is built into a provided notebook, and generates plots and tables from collected GC information. The collected data for each log is parsed into a python pandas 'event log'. Then, using the event logs as a persistent database, the event information can be sorted, filtered, and grouped in both pre-set and customizable ways to display relevant trends and outliers.
Currently supports collectors in JDK11 & JDK 16.
Installation explained here: docs/setup.md
Follow the instructions in docs/how-to-run.md
Note: The following edge cases are known and not handled automatically:
Creating a log file is quite easy, just add these logging flags to your appllication.
-Xlog:gc*:./filename.log
More detailed logging can be added, but the tool should be able to handle the gc log reported using the above Java runtime flags.
Jupyter Notebook
97.8%
Python
2.1%
GCGC uses a Jupyter notebook interface to analyze GC log files.
There are 17 generated plots, which analyze latency, concurrent and STW events, heap information, allocation rates, frequencies of events, and event summaries, comparing any number of log files and external data sources. The tool uses Jupyter notebook data visualization allows for easy customization of provided plots.
The analysis is built into a provided notebook, and generates plots and tables from collected GC information. The collected data for each log is parsed into a python pandas 'event log'. Then, using the event logs as a persistent database, the event information can be sorted, filtered, and grouped in both pre-set and customizable ways to display relevant trends and outliers.
Currently supports collectors in JDK11 & JDK 16.
Installation explained here: docs/setup.md
Follow the instructions in docs/how-to-run.md
Note: The following edge cases are known and not handled automatically:
Creating a log file is quite easy, just add these logging flags to your appllication.
-Xlog:gc*:./filename.log
More detailed logging can be added, but the tool should be able to handle the gc log reported using the above Java runtime flags.
Jupyter Notebook
97.8%
Python
2.1%