Ever open a file on dropbox.com, or click a shared link your coworker sent you? Chances are you didn’t need to download the file to see it—you saw it right in the browser. This is the work of the Previews team at Dropbox.
Previews are part of the core Dropbox experience. They allow architects to access their entire portfolios on dropbox.com while at the job site to show their work. Designers can send work-in-progress to clients without worrying about whether they have the correct software installed. Office managers can review, comment, and annotate new office design proposals,
In the past few months, we have gradually enabled IPv6 for all user-facing services in Dropbox edge network. We are serving about 15% of daily user requests in IPv6 globally. In this article, we share our experiences and lessons from enabling IPv6 in the edge network. We will cover the IPv6 design in the edge, the changes we made to support IPv6, how IPv6 was tested and rolled out to users, and issues we encountered. Note that this article is not about enabling IPv6 for internal services in our data centers, but rather focuses on making IPv6 available to users.
In our previous post, we provided an overview of the global edge network that we deployed to improve performance for our users around the world. We built this edge network over the last two years as part of a strategy to deliver the benefits of Magic Pocket.
Alongside our edge network, we launched a global backbone network that connects our data centers in North America not only to each other, but also to the edge nodes around the world. In this blog, we’ll first review how we went about building out this backbone network and then discuss the benefits that it’s delivering for us and for our users.
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.
In this post we will take you behind the scenes on how we built a state-of-the-art Optical Character Recognition (OCR) pipeline for our mobile document scanner. We used computer vision and deep learning advances such as bi-directional Long Short Term Memory (LSTMs), Connectionist Temporal Classification (CTC), convolutional neural nets (CNNs), and more. In addition, we will also dive deep into what it took to actually make our OCR pipeline production-ready at Dropbox scale.
In previous posts we have described how Dropbox’s mobile document scanner works. The document scanner makes it possible to use your mobile phone to take photos and “