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Introduction
How They SRE is a curated knowledge repository of best practices, tools, techniques, and culture of SRE adopted by the leading technology or tech-savvy organizations.

Many organizations regularly come forward and share their best practices, tools, techniques and offer an insight into engineering culture on various public platforms like engineering blogs, conferences & meetups. The content is curated from these avenues and shared in this repository.

Note to readers: This list refers to some of the articles, posts, videos, tools, and techniques published before 2015. Please use such material with caution as there may be recent advances in technology and practices which offer better alternatives and perspectives.

Data Extensions
Data extensions provide a mechanism for attaching arbitrary data to an interface to avoid bloat in core platform data models. For data extensions, we leverage Protobuf’s Any functionality so that teams can add arbitrary data to requests. Services will often store this data or pass it to a logic extension so that the core platform is never responsible for deserializing (and thus “knowing about”) this arbitrary context. Protobuf’s Any implementation comes with some infrastructure overhead in exchange for stronger typing. For a simpler implementation, one could just as easily use a JSON string to represent arbitrary data.

Discover the best python libraries for your projects.

These rough-and-ready individuals looked and acted so wonderfully unstereotypical in their work boots and bush clothes, their muddy pickups with ATVS in the back, their talk of hunting season and snow machines, and I realized that these Canadians absolutely were “natives” now, in every sense, fully adapted to their environment. For the first time it was clear to me that when we try to classify others by stereotypes of race, what we really mean is culture. The modes of behavior, dress, and habits of “The Other” that we find strange and exotic, or sometimes contemptible, are cultural patterns developed over hundreds of generations in a specific locale, under local influences of weather, livelihood, diet, and daily customs.

Something I had long felt instinctively, without being able to articulate it, could finally be put into words. I saw that it was plain wrong to evaluate people according to race, for it was clear that culture was the real divider among peoples. Given enough time, a generation or two, we could all become “The Other,” no more different in behavior from our neighbors and peers than they were from each other. Even the cosmetic differences would disappear in the course of a few more generations of “assimilation,” adopting the local diet, mores, and chromosomes, and eventually dissolving into the gene pool.

The word race comes from the same Latin root as the French word rascin – root. Hence the English word deracinated, “to be uprooted.” Exiled, perhaps. Well, exile is better than imprisonment, after all, and it seems to me that roots are highly overrated anyway. But racemus is Latin for “bunch of grapes,” and perhaps those are sour ones. I no longer had any roots; I only had the road.

Python Data, Leaflet.js Maps
folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the Leaflet.js library. Manipulate your data in Python, then visualize it in a Leaflet map via folium.

Cutter goal is to be an advanced FREE and open-source reverse-engineering platform while keeping the user experience at mind. Cutter is created by reverse engineers for reverse engineers.

https://cutter.re/