Software Engineering Daily

Tinder is a rapidly growing social network for meeting people and dating. In the past few years, Tinder’s userbase has grown rapidly, and the engineering team has scaled to meet the demands of increased popularity.

On Tinder, you are presented with a queue of suggested people that you might match with, and you swipe left or right to indicate that you like or dislike them. Creating that queue of suggestions is a complex engineering problem. Many factors go into the suggestions that Tinder gives you: geotargeting, food preferences, your favorite band, your photos, and the people you have swiped on in the past.

Bryan Li is an engineering manager at Tinder, and he joins the show to describe the interaction between the mobile client, backend servers, and the offline analytics and machine learning. We also talk about managing different teams and how to reorganize smoothly as a company grows.

If you like this episode, we have done other shows about scaling companies like Uber, New Relic, and Giphy. Download the Software Engineering Daily app for iOS and Android to hear all of our old episodes, and easily discover new topics that might interest you. If you don’t like this episode, you can easily find something more interesting by looking at the recommendation engine in the app.

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Playing a video on the Internet seems simple. You press play, the video gets delivered, and boom–you are watching Game of Thrones, right?

It’s a bit more complicated. Unless you have built an application that involves video, you probably have not dealt with the world of codecs, bitrates, and streaming. Depending on the bandwidth between the user and the server, you might want to use different compression rates. Think about all of the different use cases–different connection speeds, device types, operating systems, video players, cloud providers. As a developer, you just want videos in your application to play quickly and reliably. But it takes a lot of engineering, monitoring, and re-engineering to get it right.

Matt McClure and Jon Dahl are the founders of Mux, a company that makes video infrastructure technologies. Previously they built Zencoder, a product for encoding and delivering video. This episode was a fascinating discussion of why building video products for the modern Internet is still so hard.

Download the Software Engineering Daily app for iOS to hear all of our old episodes, and easily discover new topics that might interest you. You can upvote the episodes you like and get recommendations based on your listening history. With 600 episodes, it is hard to find the episodes that appeal to you, and we hope the app helps with that.

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Tinder is a popular dating app where each user swipes through a sequence of other users in order to find a match. Swiping left means you are not interested. Swiping right means you would like to connect with the person. The simple premise of Tinder has led to massive growth, and the app is now also used to discover new friends and create casual meetings.

Every social network knows–if you are not growing, then you are dying. Growth is so important to Tinder, they have a large engineering organization devoted to five facets of growth: new users, activation, retention, dropoff, and anti-spam.

These five segments cover the entire Tinder user lifecycle, and there is a sub-team in charge of each of the five areas. No matter what kind of Tinder user you are, there are growth engineers focused on your experience.

Alex Ross is the director of engineering for the growth team at Tinder. His job requires a mix of data science, data engineering, psychology, and setting proper KPIs (key performance indicators). Each subteam has KPIs that determine how well they are doing with growth–and if the wrong KPI is set, it can create bad incentives. For example, a growth team that is focused only on getting users to spend more time engaging with Tinder would have an incentive to create so-called “dark patterns” that trigger addiction.

If you like this episode, we have done many other shows about data science and data engineering. Download the Software Engineering Daily app for iOS to hear all of our old episodes, and easily discover new topics that might interest you. You can upvote the episodes you like and get recommendations based on your listening history. With 600 episodes, it is hard to find the episodes that appeal to you, and we hope the app helps with that.

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Spotify is a streaming music company with more than 50 million users. Whenever a user listens to a song, Spotify records that event and uses it as input to learn more about the user’s preferences. Listening to a song is one type of event–there are hundreds of others. Opening the Spotify app, skipping a song, sharing a playlist with a friend–all of these are events that provide valuable insights to Spotify.

These are not the only types of events that Spotify cares about. There are also events that occur at the infrastructure level–for example a logging server that runs out of disk space. There are events that are relevant to all the users on Spotify–for example a new album release from Taylor Swift.

An “event” is an object that needs to be registered within a system. Since there are so many events on a platform like Spotify, delivering and processing them reliably requires significant investment.

Modern Internet companies are built by connecting cloud services, databases, and internal tools together. These different systems might respond to different events in different ways. Each system subscribes to the types of events that it wants to hear. Since there are so many events, and they might be received at uneven bursts, a modern architecture has a scalable queueing system to buffer events.

To put an event on the queue, the event producer “publishes” that event to the queue. The event is then received by each “subscriber.” That’s why queueing is often known as pub/sub–publish/subscribe.

Igor Maravic is an engineer with Spotify. In this episode, he explains why pub/sub is a key element of Spotify’s infrastructure–and he describes the migration that Spotify has made from Apache Kafka to Google Cloud Pubsub.

If you like this episode, we have done many other shows about cloud infrastructure. You can check out our back catalog by downloading the Software Engineering Daily app for iOS, where you can listen to all of our old episodes, and easily discover new topics that might interest you. You can upvote the episodes you like and get recommendations based on your listening history. With 600 episodes, it is hard to find the episodes that appeal to you, and we hope the app helps with that.

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