This session will cover the challenges of creating a production application performance monitoring system for Python. It includes an overview of the architecture of the system, as well as how it hooks into Django and captures details about web transactions, database transactions, memcache requests, exceptions and much more.
This session provides a technical review of the challenges associated with instrumenting Python for production monitoring. How do you place monitoring hooks into code that cannot be modified directly in order to collect meaningful performance data? Concepts covered in this session will include:
The talk includes real-world examples of how these mechanisms have been used to add instrumentation to the Django web framework in order to collect actionable performance data.
C/C++ and Python developer. Interested in Apache, WSGI, Python web hosting and Python web frameworks. bio from Twitter
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