Jesús Espino

Go is a very performant language, so, normally you don't need to optimize it at all. But what happen when you need it?

This talk is a walk through some techniques and tools that you can use to squeeze that last drops from your functions.

We are going to see tools like pprof or go benchmarks, and explore some of the results.

We are going to explore other topis like escape analysis, function inlining or the garbage collector, that all of them can affect the performance of your application.

Slices, Maps and Channels in go, are first class citizens of the language, they are used widely in our day to day work, but… do you know how they works under the hood? Do you know the implications of adding elements to an slice, or new keys to a map?

Do you know why you can’t relay in maps order? Do you know how channels handle the buffer or the blocked goroutines? If you don’t know about that, this is your talk. I going to access the go runtime memory state of the maps, slices and channels, and show you how they evolve over time while we change them.

I will explain how CPython objects are built, from simple objects like int or None to complex ones like dict. To make it funnier, I will play to change instance data directly using ctypes and do "really bad things" like truncating tuples.