Finding configuration and use issues which rob your system of optimal performance can be difficult even under optimal conditions. For this session, we will be leveraging big data practices to examine HTTP access logs for common issues related to use and configuration which result in slow client response times.
The class will present an overview of concepts and techniques for the examination of HTTP logs to find performance defects in both production and QA environments. Lectures will be complemented with hands on labs to apply the concepts to logs captured for examination.
Users are encouraged to bring logs for their own website to apply the same analytical techniques used in the class and labs against their own web solutions. It is recommended that the logs be in the w3c log format with the w3c time-taken field included.
These techniques covered in this workshop can be applied in both Agile and Waterfall shops, as well as in production environments for the tuning of existing applications.
This workshop takes a performance engineering approach to analyze and identify HTTP architecture applications for known performance antipatterns.