One of the greatest challenges associated with maintaining a complex desktop application like Dropbox is that with hundreds of millions of installs, even the smallest bugs can end up affecting a very large number of users. Bugs inevitably will strike, and while most of them allow the application to recover, some cause the application to terminate. These terminations, or “crashes,” are highly disruptive events: when Dropbox stops, synchronization stops. To ensure uninterrupted sync for our users we automatically detect and report all crashes and take steps to restart our application when they occur.
In 2016, faced with our impending transition to Python 3,
Dropbox is one of the most popular desktop applications in the world: You can install it today on Windows, macOS, and some flavors of Linux. What you may not know is that much of the application is written using Python. In fact, Drew’s very first lines of code for Dropbox were written in Python for Windows using venerable libraries such as
Though we’ve relied on Python 2 for many years (most recently, we used Python 2.7), we began moving to Python 3 back in 2015. This transition is now complete: If you’re using Dropbox today,
Hello everyone, I’m very excited to announce Pyston, a new open-source implementation of Python, currently under development at Dropbox. The goal of the project is to produce a high-performance Python implementation that can push Python into domains dominated by traditional systems languages like C++.
Here at Dropbox, we love Python and try to use it for as much as we can. As we scale and the problems we tackle grow, though, we’re starting to find that hitting our performance targets can sometimes become prohibitively difficult when staying on Python. Sometimes, it can be less work to do a rewrite in another language.
It’s almost time for another Hack Week at Dropbox, and with that in mind I’d like to present one of the projects from our last Hack Week.
A profiler is an indispensable tool for optimizing programs. Without a profiler, it’s hard to tell which parts of the code are consuming enough time to be worth looking at. Python comes with a profiler called cProfile, but enabling it slows things down so much that it’s usually only used in development or simulated scenarios, which may differ from real-world usage.
At our last hack week, I set out to build a profiler that would be usable on live servers without impacting our users.
Hi! I’m Pavel and I interned at Dropbox over the past summer. One of my biggest projects during this internship was optimizing Python for dynamic page generation on the website. By the end of the summer, I optimized many of dropbox.com’s pages to render 5 times faster. This came with a fair share of challenges though, which I’d like to write about today:
Dropbox is a large website with lots of dynamically generated pages. The more pages that are dynamically generated from user input, the bigger the risk becomes for Cross-site scripting attacks.
In this post we will describe the Edge network part of Dropbox traffic infrastructure. This is an extended transcript of our NginxConf 2018 presentation. Around the same time last year we described low-level aspects of our infra in the Optimizing web servers for high throughput and low latency post. This time we’ll cover higher-level things like our points of presence around the world, GSLB, RUM DNS, L4 loadbalancers, nginx setup and its dynamic configuration, and a bit of gRPC proxying.
Dropbox has more than half a billion registered users who trust us with over an exabyte of data and petabytes of corresponding metadata.