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Debugging Python Applications in Production

Description

Due to dynamic and interpreted nature of Python applications it's not hard to employ a limited set of debugging techniques in development and use a variety of debugging tools. However all nasty bugs tend to happen only in production, the very constrained environment without possibilities to edit code, restart, freeze or reconfigure in runtime to suspend services or scare the bug away. This talk is going to cover a set of techniques of debugging, tracing and profiling production Python code in Linux and Solaris environments (with focus on Linux). I'm going to show how to take advantage of GDB, strace, kernel memory, tcpdump, DTrace, SystemTap and all the related software tools to fully introspect what's going on in the Python-powered system.

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