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Friday Blast #13

This is the 13th Friday Blast post. Coincidentally[1] today is also Friday the 13th.

Fature Toggles (2016) - feature toggles is a set of patterns which allows not-yet-ready code to exist in an application, without having any effect. This article describes in a wealth of details usecases, types of toggles, infrastructure support etc. for them.

How to safely store a password (2010) - use a password hash, like bcrypt, scrypt etc. Thereโ€™s more to it than that, as previous links in this series have highlighted, but a quick reminder is always welcome I think.

The binary search of distributed programming (2015) - is generating a strictly increasing sequence of integers/IDs. Which turns out to be pretty hard, in general. Which tells you a lot about distributed systems - something achievable with a single counter and possibly some locks on a single machine becomes very hard in a distributed setting. The author is also the author of Redis, so he know a thing or three. But the algorithm proposed seems to be broken or at least provide some bad guarantees. In any case, a good read about designing these things and what can go wrong.

Take it to the limit: considerations for building reliable systems (2016) - mainly advice on building distributed systems. This time, having to do with โ€œlimitsโ€ and enforcing them. Basically, wherever and whenever thereโ€™s some quantity in the system which might grow unbounded, you should have hard limits on it. Request sizes, queue depths, items to process, child entities for a parent entity, response sizes etc. should all be limited somehow. This protects against malicious agents trying to DoS the system, but also against your own agents doing the same.

A five muntes guide to better typography (2017) - a piece about graphic and typographic design.

Difference between a clustered index see and non-clustered index seek (2016) - a StackOverflow question. There seems to be this misconception that non-clustered indices are slower than clustered ones, since one has to do a seek/scan, then another seek for the data itself. But depending on how large the data is and how compact the non-clustered index manages to be, this might not be the case. Since the first seek/scan might occur completely in memory, or at least touch less pages than the clustered one. Ditto, for counting queries, a non-clustered index might be much faster.

The map of mathematics #video (2017), The map of computer science #video (2017), The map of physics #video (2017), The map of chemestry #video (2017) - a really wonderful set of videos laying out the โ€œbranchesโ€ of the mathematics, computer science, physics and chemestry. Itโ€™s a really big picture view, and as the author himself notes, everything is more or less interconnected within and across fields, but itโ€™s still nice to see all of the pieces of knowledge which are somehow distinct enough to be called something. The animation is really great as well.


[1] Or not :o

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