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Request-log-analyzer (r-l-a) is a command line tool to analyze request log files. Its purpose is to find what requests are best candidates for optimization. It parses the provided log files and aggregates the parsed information to build a performance report. See Sample output for an example of this report.
Use the issues tracker, or send me a message on my GitHub account if you have questions, ideas, feature requests, bug reports, etc. Or, read some Testimonials of our users and send one in yourself!
Designed and written by Bart ten Brinke (github, twitter) & Willem van Bergen (github, twitter)
| File format | Command line option |
|---|---|
| Rails request log | --format rails, --format rails3, or use --rails-format <format> for more parsing options |
| Merb request log | --format merb |
| Rack CommonLogger log | --format rack |
| DelayedJob log | --format delayed_job |
| Apache access log | --apache-format <format string> |
| Amazon S3 access log | --format amazon_s3 |
| MySQL slow query log | --format mysql |
| NGINX log | --format nginx |
| PostgreSQL query log | --format postgresql |
| Oink log | --format oink |
| HAProxy httplog format | --format haproxy |
Moreover, you can easily create your own file formats easily or adapt one of the out-of-the-box formats for your own needs. See Creating your own file format definition for more information and instructions.
For the built-in formats, request-log-analyzer auto-detects the file format for you, so you do not have to specify a --format command line option. You can always do so if the auto-detection fails.
Use RubyGems to install request-log-analyzer on your computer:
$ gem install request-log-analyzer
Now you can run request-log-analyzer to analyze a log file:
$ request-log-analyzer log/production.log
- Performance measurement basics: get introduced quickly to the performance measurement basics.
- Basic usage: get a performance report using your application’s request log files.
- Configure logging: configure logging correctly for your application to get the best results out of r-l-a (now with munin !).
- In-depth analysis: use filtering options to drill down to the cause of the performance issues.
- Creating a request database: create an SQLite 3 database with all parsed request information and perform analyses using SQL queries.
- Creating your own file format definition: gear the log analyzer towards your application and get more detailed results
- As a Scout plugin
- As a Munin plugin
- See Using request-log-analyzer as a library for more information about the r-l-a API.
- Check out the Development page if you want to help out on this project.
- The Changelog documents what has changed over the different releases.