Backstage Blog

• Announcements
• API

The SoundCloud API will be dropping support for offset-based pagination on March 2, 2015, in favor of linked partitioning.

To page through a JSON response, pass the linked_partitioning=1 parameter along with your request and it will return a collection, along with a next_href property if there are additional results. To fetch the next page of results, simply follow that URI. If the response does not contain a next_href property, you have reached the end of the results.

You can read more about linked partitioning in the Pagination section of our HTTP API Guide…

• Announcements
• Open Source
• Monitoring
• Go

In previous blog posts, we discussed how SoundCloud has been moving towards a microservice architecture. Soon we had hundreds of services, with many thousand instances running and changing at the same time. With our existing monitoring set-up, mostly based on StatsD and Graphite, we ran into a number of serious limitations. What we really needed was a system with the following features:

• A multi-dimensional data model, so that data can be sliced and diced at will, along dimensions like instance, service, endpoint, and method.
• Operational simplicity, so that you can spin up a monitoring server where and when you want, even on your local workstation, without setting up a distributed storage backend or reconfiguring the world.
• Scalable data collection and decentralized architecture, so that you can reliably monitor the many instances of your services, and independent teams can set up independent monitoring servers.
• Finally, a powerful query language that leverages the data model for meaningful alerting (including easy silencing) and graphing (for dashboards and for ad-hoc exploration).

All of these features existed in various systems. However, we could not identify a system that combined them all until a colleague started an ambitious pet project in 2012 that aimed to do so. Shortly thereafter, we decided to develop it into SoundCloud’s monitoring system: Prometheus was born.

• Scalding
• Hadoop

Recently we teamed up with Concurrent Inc., the backers of the data-processing framework Cascading, to do a case study of how we use Scalding for some of our data-driven products such as Search. Scalding enables us to iterate quickly, test easily, and it allows for loose coupling of some of our data-processing pipelines.

Check back for future posts about our use of other data-processing tools, and frameworks such as Spark.

• Announcements
• API

The SoundCloud API will be dropping support for Extensible Markup Language (XML) responses. XML will be phased out on the following schedule:

1. XML is currently the default response format for requests without an explicit format specified in the path (e.g. /tracks) or Accept header. This default will be changed to JSON on December 1, 2014.
2. Explicit requests for XML — specified either in the path (e.g. /tracks.xml) or an Accept: application/xml header — will continue to be supported until December 15, 2014. After that point, only JSON responses will be supported.
…

• iOS
• Mobile

When we rebuilt our iOS app, the player was the core focus. The interactive waveform was at the center of the design. It was important both that the player be fast and look good.

Initial implementation

We iterated on the waveform view until it was as responsive as possible. The initial implementation focused on replicating the design, which heavily used CoreGraphics. A single custom view calculates the current bar offset based on its time property. It then draws each of the waveform samples that are in the current visible section of the waveform. Each sample is either rendered as a filled rectangle for unplayed samples, or by adding clip paths to the context then drawing a linear CGGradient…

• iOS
• Mobile

Recently, SoundCloud launched the new iOS application which was a complete rewrite of the existing iOS application. The Mobile engineering team saw this as an opportunity to build a solid foundation for the future of SoundCloud on iOS and to experiment with new technologies and processes at the same time.

In the world of mobile, you deal with data, errors, threads and concurrency a lot. The common scenario starts with a user tapping on the screen. The application jumps off of the main UI thread…

• Data

Here at SoundCloud, in order to provide counts and a time series of counts in real time, we created something called Stitch.

Stitch was initially developed to provide timelines and counts for our stats pages, which are where users can see which of their tracks are played and when.

Stitch is a wrapper around a Cassandra database. It has a web application that provides read access to the counts through an HTTP API. The counts are written to Cassandra in two distinct ways, and it’s possible to use…

• Scala
• Finagle
• Ruby
• Architecture

In the first two parts of this series, we talked about how SoundCloud started breaking away from a monolithic Ruby on Rails application into a microservices architecture. In this part we will talk a bit more about the platforms and languages in which we tend to write these microservices.

At the same time that we started the process of building systems outside the Mothership (our Rails monolith) we started breaking our large team of engineers into smaller teams that focused on one specific area…

• Scala
• Finagle
• Ruby
• Architecture

In the previous post, we talked about how we enabled our teams to build microservices in Scala, Clojure, and JRuby without coupling them with our legacy monolithic Rails system. After the architecture changes were made, our teams were free to build their new features and enhancements in a much more flexible environment. An important question remained, though: how do we extract the features from the monolithic Rails application called Mothership?

Splitting a legacy application is never easy, but…

• Scala
• Finagle
• Ruby
• Architecture

Most of SoundCloud’s products are written in Scala, Clojure, or JRuby. This wasn’t always the case. Like other start-ups, SoundCloud was created as a single, monolithic Ruby on Rails application running on the MRI, Ruby’s official interpreter, and backed by memcached and MySQL.

We affectionately call this system Mothership. Its architecture was a good solution for a new product used by several hundreds of thousands of artists to share their work, collaborate on tracks, and be discovered by the…