How Uber Scales Their Real-time Market Platform
Monday, September 14, 2015 at 8:56AM
Todd Hoff in Example

Reportedly Uber has grown an astonishing 38 times bigger in just four years. Now, for what I think is the first time, Matt Ranney, Chief Systems Architect at Uber, in a very interesting and detailed talk--Scaling Uber's Real-time Market Platform---tells us a lot about how Uber’s software works.

If you are interested in Surge pricing, that’s not covered in the talk. We do learn about Uber’s dispatch system, how they implement geospatial indexing, how they scale their system, how they implement high availability, and how they handle failure, including the surprising way they handle datacenter failures using driver phones as an external distributed storage system for recovery.

The overall impression of the talk is one of very rapid growth. Many of the architectural choices they’ve made are a consequence of growing so fast and trying to empower recently assembled teams to move as quickly as possible. A lot of technology has been used on the backend because their major goal has been for teams to get the engineering velocity as high as possible.

After a understandably chaotic (and very successful) start it seems Uber has learned a lot about their business and what they really need to succeed. Their early dispatch system was a typical just make it work type affair that assumed at a deep level it was moving only people. Now that Uber’s mission has grown to handle boxes and groceries as well as people, their dispatch system has been abstracted and put on very solid and smart architectural foundation.

Though Matt thinks their architecture might be a little crazy, the idea of using a consistent hash ring with a gossip protocol seems spot on for their use case.

It’s hard not to be captivated for Matt’s genuine enthusiasm for what he’s working on. When talking about DISCO, their dispatch system, he says in an excited tone that it’s like the traveling salesman problem from school. It’s a cool Computer Science thing. Even though the solution isn’t optimal, it’s the traveling salesman at an interesting scale, in real-time, in the real-world, built out of fault tolerant scalable components. How cool is that?

So let’s see how Uber works on the inside. Here’s my gloss on Matt’s talk:

Stats

Platform

General

Architecture Overview

The Old Dispatch System

The New Dispatch System

Dispatch

Geospatial Index

Routing

Scaling Dispatch

20783449993_8e0e0491df.jpg

Dispatch Availability

Total Datacenter Failure

The Downside

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