|Number of watchers on Github||1897|
|Number of open issues||9|
|Average time to close an issue||4 months|
|Average time to merge a PR||2 months|
|Open pull requests||4+|
|Closed pull requests||19+|
|Last commit||about 2 years ago|
|Repo Created||over 8 years ago|
|Repo Last Updated||over 1 year ago|
|Organization / Author||etsy|
|Do you use logster? Leave a review!|
|View open issues (9)|
|View logster activity|
|View on github|
|Fresh, new opensource launches 🚀🚀🚀|
Trendy new open source projects in your inbox! View examples
Logster is a utility for reading log files and generating metrics to configurable outputs. It is ideal for visualizing trends of events that are occurring in your application/system/error logs. For example, you might use logster to graph the number of occurrences of HTTP response code that appears in your web server logs.
Logster maintains a cursor, via a tailer, on each log file that it reads so that each successive execution only inspects new log entries. In other words, a 1 minute crontab entry for logster would allow you to generate near real-time trends in the configured output for anything you want to measure from your logs.
This tool is made up of a framework script, logster, and parsing classes that are written to accommodate your specific log format. Sample parsers are included in this distribution. The parser classes essentially read a log file line by line, apply a regular expression to extract useful data from the lines you are interested in, and then aggregate that data into metrics that will be submitted to the configured output. The sample parsers should give you some idea of how to get started writing your own. A list of available parsers can be found on the Parsers page.
Graphite, Ganglia, Amazon CloudWatch, Nagios, StatsD and stdout outputs are provided, and Logster also supports the use of third-party output classes. A list of available output classes can be found on the Outputs page.
The logster project was created at Etsy as a fork of ganglia-logtailer (https://bitbucket.org/maplebed/ganglia-logtailer). We made the decision to fork ganglia-logtailer because we were removing daemon-mode from the original framework. We only make use of cron-mode, and supporting both cron- and daemon-modes makes for more work when creating parsing scripts. We care strongly about simplicity in writing parsing scripts -- which enables more of our engineers to write log parsers quickly.
Logster supports two methods for gathering data from a logfile:
By default, Logster uses the
logtail utility that can be obtained from the
logcheck package, either from a Debian package manager or from source:
RPMs for logcheck can be found here:
PygtailPython module instead of logtail. You can install Pygtail using pip
$ pip install pygtail
To use Pygtail, supply the
--tailer=pygtail option on the Logster
Also, Logster supports two methods for locking files (which it has to do):
By default, Logster uses
Optionally, Logster can use the
Portalocker Python module instead of fcntl
(which is not available on Windows). You can install Portalocker using pip,
similar to Pygtail above.
To use Portalocker, supply the
--locker=portalocker option on the
Once you have logtail or Pygtail installed, install Logster using the
$ sudo python setup.py install
You can test logster from the command line. The --dry-run option will allow you to see the metrics being generated on stdout rather than sending them to your configured output.
$ sudo /usr/bin/logster --dry-run --output=ganglia SampleLogster /var/log/httpd/access_log $ sudo /usr/bin/logster --dry-run --output=graphite --graphite-host=graphite.example.com:2003 SampleLogster /var/log/httpd/access_log
You can use the provided parsers, or you can use your own parsers by passing the complete module and parser name. In this case, the name of the parser does not have to match the name of the module (you can have a logster.py file with a MyCustomParser parser). Just make sure the module is in your Python path - via a virtualenv, for example.
$ /env/my_org/bin/logster --dry-run --output=stdout my_org_package.logster.MyCustomParser /var/log/my_custom_log
Additional usage details can be found with the -h option:
$ logster -h Usage: logster [options] parser logfile Tail a log file and filter each line to generate metrics that can be sent to common monitoring packages. Options: -h, --help show this help message and exit -t TAILER, --tailer=TAILER Specify which tailer to use. Options are logtail and pygtail. Default is "logtail". --logtail=LOGTAIL Specify location of logtail. Default "/usr/sbin/logtail2" -p METRIC_PREFIX, --metric-prefix=METRIC_PREFIX Add prefix to all published metrics. This is for people that may multiple instances of same service on same host. -x METRIC_SUFFIX, --metric-suffix=METRIC_SUFFIX Add suffix to all published metrics. This is for people that may add suffix at the end of their metrics. --parser-help Print usage and options for the selected parser --parser-options=PARSER_OPTIONS Options to pass to the logster parser such as "-o VALUE --option2 VALUE". These are parser-specific and passed directly to the parser. -s STATE_DIR, --state-dir=STATE_DIR Where to store the tailer state file. Default location /var/run -l LOG_DIR, --log-dir=LOG_DIR Where to store the logster logfile. Default location /var/log/logster --log-conf=LOG_CONF Logging configuration file. None by default -o OUTPUT, --output=OUTPUT Where to send metrics (can specify multiple times). Choices are statsd, stdout, cloudwatch, graphite, ganglia, nsca or a fully qualified Python class name -d, --dry-run Parse the log file but send stats to standard output. -D, --debug Provide more verbose logging for debugging.
If you have questions, you can find us on IRC in the
#codeascraft channel on Freenode.