This is an expanded version of my talk at NginxConf 2017 on September 6, 2017. As an SRE on the Dropbox Traffic Team, I’m responsible for our Edge network: its reliability, performance, and efficiency. The Dropbox edge network is an nginx-based proxy tier designed to handle both latency-sensitive metadata transactions and high-throughput data transfers. In a system that is handling tens of gigabits per second while simultaneously processing tens of thousands latency-sensitive transactions, there are efficiency/performance optimizations throughout the proxy stack, from drivers and interrupts, through TCP/IP and kernel, to library, and application level tunings.

https://blogs.dropbox.com/tech/2017/09/optimizing-web-servers-for-high-throughput-and-low-latency/

Despite being a voice and text chat app, Discord sees over a hundred million images passing through its tubes every day. While we wish it was as simple as sending them out across the tubes to your friends, delivering these images creates some pretty large technical problems. Linking directly to images would leak users’ IP addresses to image hosts, and large images use up lots of bandwidth. To circumvent these problems, Discord needs an intermediary service to fetch images on behalf of users and then resize them to reduce bandwidth usage.


https://blog.discordapp.com/how-discord-resizes-150-million-images-every-day-with-go-and-c-c9e98731c65d

In information retrieval, Okapi BM25 (BM stands for Best Matching) is a ranking function used by search engines to rank matching documents according to their relevance to a given search query. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson, Karen Spärck Jones, and others.

The name of the actual ranking function is BM25. To set the right context, however, it is usually referred to as "Okapi BM25", since the Okapi information retrieval system, implemented at London's City University in the 1980s and 1990s, was the first system to implement this function.

BM25 and its newer variants, e.g. BM25F (a version of BM25 that can take document structure and anchor text into account), represent state-of-the-art TF-IDF-like retrieval functions used in document retrieval.


https://en.wikipedia.org/wiki/Okapi_BM25
https://inyl.github.io/search_engine/2017/04/01/bm25.html
https://www.slideshare.net/kjmorc/ss-80803233

About Abseil

Abseil is an open-source collection of C++ library code designed to augment the C++ standard library. The Abseil library code is collected from Google’s own C++ code base, has been extensively tested and used in production, and is the same code we depend on in our daily coding lives.

In some cases, Abseil provides pieces missing from the C++ standard; in others, Abseil provides alternatives to the standard for special needs we’ve found through usage in the Google code base. We denote those cases clearly within the library code we provide you.

Abseil is not meant to be competitor to any standard library code; we’ve just found that many of these utilities serve a purpose within our code base, and we now want to provide those resources to the C++ community as a whole.

https://abseil.io/