Optimizing web servers for high throughput and low latency


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.

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Memory-Efficient Image Passing in the Document Scanner

In our previous blog posts on Dropbox’s document scanner (Part 1, Part 2 and Part 3), we focused on the algorithms that powered the scanner and on the optimizations that made them speedy. However, speed is not the only thing that matters in a mobile environment: what about memory? Bounding both peak memory usage and memory spikes is important, since the operating system may terminate the app outright when under memory pressure. In this blog post, we will discuss some tweaks we made to lower the memory usage of our iOS document scanner.

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Improving the Responsiveness of the Document Detector

In our previous blog posts (Part 1, Part 2), we presented an overview of various parts of Dropbox’s document scanner, which helps users digitize their physical documents by automatically detecting them from photos and enhancing them. In this post, we will delve into the problem of maintaining a real-time frame rate in the document scanner even in the presence of camera movement, and share some lessons learned.

Document scanning as augmented reality

Dropbox’s document scanner shows an overlay of the detected document over the incoming image stream from the camera.

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Lepton image compression: saving 22% losslessly from images at 15MB/s

We are pleased to announce the open source release of Lepton, our new streaming image compression format, under the Apache license.

Lepton achieves a 22% savings reduction for existing JPEG images, by predicting coefficients in JPEG blocks and feeding those predictions as context into an arithmetic coder. Lepton preserves the original file bit-for-bit perfectly. It compresses JPEG files at a rate of 5 megabytes per second and decodes them back to the original bits at 15 megabytes per second, securely, deterministically, and in under 24 megabytes of memory.

We have used Lepton to encode 16 billion images saved to Dropbox,

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Lossless compression with Brotli in Rust for a bit of Pied Piper on the backend

Written by Daniel Reiter Horn and Mehant Baid, Serving Infrastructure team at Dropbox.

In HBO’s Silicon Valley, lossless video compression plays a pivotal role for Pied Piper as they struggle to stream HD content at high speed.

John P. Johnson/HBO

Inspired by Pied Piper, we created our own version of their algorithm Pied Piper at Hack Week. In fact, we’ve extended that work and have a bit-exact, lossless media compression algorithm that achieves extremely good results on a wide array of images. (Stay tuned for more on that!)

However,

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Inside LAN Sync

Dropbox LAN Sync is a feature that allows you to download files from other computers on your network, saving time and bandwidth compared to downloading them from Dropbox servers. As the number of companies and offices using Dropbox has increased, the use cases for LAN Sync have grown, and the feature was recently rewritten and improved. Here’s a look inside how it works.

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