Airbnb Engineering » Tech Talks http://nerds.airbnb.com Nerds Fri, 24 Jul 2015 00:02:05 +0000 en-US hourly 1 http://wordpress.org/?v=320 Netflix Algorithms Are Key to the ‘Future of Internet Television’ http://nerds.airbnb.com/netflix-algorithms-are-key-to-the-future-of-internet-television/ http://nerds.airbnb.com/netflix-algorithms-are-key-to-the-future-of-internet-television/#comments Fri, 24 Jul 2015 00:02:05 +0000 http://nerds.airbnb.com/?p=176595119 When Netflix’s 60 million subscribers log in to the streaming video service, their home page is populated with TV show and movie recommendations. The recommendations are key to Netflix’s success, as they drive two out of every three hours of video streamed.   The user’s home page “is where all our algorithms for recommending TV […]

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When Netflix’s 60 million subscribers log in to the streaming video service, their home page is populated with TV show and movie recommendations. The recommendations are key to Netflix’s success, as they drive two out of every three hours of video streamed.

 

The user’s home page “is where all our algorithms for recommending TV shows and movies come together,” said Carlos Gomez Uribe, Netflix VP of Innovation. In his recent OpenAir 2015 talk, Gomez Uribe said over 100 engineers are focused on developing algorithms to help Netflix meet its business goal of “inventing the future of Internet television.”

 

One Netflix algorithm organizes the entire video catalog in a personalized way for users. Another looks for similarities between all content Netflix offers. A master algorithm “looks at all the other algorithms to decide which videos make it onto a user’s home page,” said Gomez Uribe.

 

Keyword searches drive 20 percent of video streaming hours, so Netflix’s search algorithm is tied into its recommendations and other algorithms. When users search for a title Netflix doesn’t have, the search results will display recommendations for similar shows. “We try to recommend movies related to a search, even though it’s not exactly what you wanted. All this requires a large number of algorithms,” Gomez Uribe said.

 

Personalization is important because it’s more likely to drive higher engagement with Netflix content vs. simply showing a user what’s popular. When Netflix organizes videos by popularity on user home pages, the “take rate” (the percentage of suggested videos that are actually watched) is “OK,” Gomez Uribe said. “But when we personalize recommendations, the take rate goes way up.” (Go to 5:00 in the video to hear more.)

 

Algorithms also help Netflix perform long-term A/B testing on its user interface, providing alternate ways to organize and display recommendations to users, said Gomez Uribe. In turn, the A/B testing can help Netflix measure subscriber cancellation rates more effectively. Cancellations are an easier metric to track than new member sign-ups because the latter are often fueled by word of mouth—which is notoriously difficult to track.

 

A/B testing has enabled Netflix to “stand our ground” on occasion, Gomez Uribe added. In 2011, Netflix.com unveiled a new user interface. A/B test results influenced the design, as the data showed that the new look-and-feel decreased cancellations and increased hours streamed.

 

Netflix was “so proud” of the new interface that it ran a blog post about it, “New Look and Feel for the Netflix Website” (June 8, 2011). But in short order, Netflix received a considerable number of snarky comments about the new look. Wrote one displeased subscriber: “Please inform your employers that a drunken dyslexic monkey would be a more acceptable design lead for your web concepts.”

 

Data from the A/B tests told Netflix that, despite the snark, “the majority of users were better off” with the new interface. And so, rather than rolling back to old the UI, Netflix moved forward with the new one, continuing to fine-tune it along the way. (Discussion begins around 10:40 in the video.)

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Recap of OpenAir http://nerds.airbnb.com/recap-of-openair/ http://nerds.airbnb.com/recap-of-openair/#comments Mon, 06 Jul 2015 16:04:20 +0000 http://nerds.airbnb.com/?p=176595098 Three weeks ago we hosted OpenAir 2015, our second technology conference. We had an amazing turnout of bright minds from across the industry, more than doubling attendance from 2014. A new generation of companies are emerging whose customers aren’t judging them by their apps and websites but on the experiences and content the products connect […]

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Three weeks ago we hosted OpenAir 2015, our second technology conference. We had an amazing turnout of bright minds from across the industry, more than doubling attendance from 2014.

A new generation of companies are emerging whose customers aren’t judging them by their apps and websites but on the experiences and content the products connect them with. With that in mind the theme for OpenAir 2015 was scaling human connection and we focused on online to offline and the better matching that enables it.

Throughout the day we learned how Instagram helps their users discover new content that inspires them; how Stripe helps people transact across borders, how LinkedIn used data to power their social network, how Periscope came to life on Android, and of course, how Airbnb helps turns strangers into friends.

Behind all of these challenges there are central concepts that we as a tech industry need to understand better – trust, personalization and the data that enables both.

With that in mind, Airbnb open-sourced two new tools for wrangling data. The first is called Airflow which is a sophisticated tool to programmatically author, schedule and monitor data pipelines. People in the industry will know this work as ETL engineering. The second was Aerosolve. Aerosolve is a machine learning package for Apache Spark. It’s designed to combine high capacity to learn with an accessible workflow that encourages iteration and deep understanding of underlying patterns on a human level. Since we launched these tools they have gotten over 2000 stars on GitHub – we can’t wait to see how people use and contribute to them.

We also announced a new tool for our hosts called Price Tips, which is powered by Aerosolve. Price Tips creates ongoing tips for our hosts on how to price their listing, not just for one day, but for each day of the year. This pricing is fully dynamic — it takes into account demand, location, travel trends, amenities, type of home and much more. There are hundreds of signals that go into the model to produce each price tip. We believe that better pricing will be a great way to further empower our hosts to meet their personal goals through hosting.

Finally we closed out the opening keynote morning with the launch of our brand new Gift Cards website. Now anyone in the US can give their family, friends, colleagues, frenemies, whomever, the gift of travel on Airbnb. And for those lucky folks in the audience, we gave everyone a $100 gift card.

We will be following up with more videos from the event, so keep your eyes on this space.

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Android Frameworks from Airbnb and Square http://nerds.airbnb.com/android-frameworks-from-airbnb-and-square/ http://nerds.airbnb.com/android-frameworks-from-airbnb-and-square/#comments Thu, 16 Apr 2015 19:09:01 +0000 http://nerds.airbnb.com/?p=176594918 We wrapped up the month of March with with the theme of android development. It was exciting to host Pierre-Yves Ricau from Square and feature Airbnb engineers, Eric Petzel and Nick Adams. Mapstraction Many mobile applications today require some form of an interactive map as part of their user interface. Google provides a native package […]

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We wrapped up the month of March with with the theme of android development. It was exciting to host Pierre-Yves Ricau from Square and feature Airbnb engineers, Eric Petzel and Nick Adams.

Mapstraction

Many mobile applications today require some form of an interactive map as part of their user interface. Google provides a native package and experience with Google Play Services to satisfy this need, but the questions remains of how one creates interactive maps for devices without Play Services.

In some countries, the majority of devices are sold without Google Play Services. Device manufacturers who ship their devices without Play Services are continuing to gain popularity worldwide. We have built a package that solves these problems, letting developers remain agnostic of manufacturer while providing a consistent map experience to users.

Speaker Bio

Eric Petzel: Software Engineer on the Android team at Airbnb where he focuses on building features for our hosts and guests, as well as tools to share with the Android community. Previously to Airbnb, he worked at Skype on their Android client

Nick Adams: Software Engineer on the Android team at Airbnb. He focuses on building features that improve the quality of the app and expanding to new form factors. Before Airbnb he was a student at the University of British Columbia in Canada.

Crash Fast: Square’s approach to Android crashes

The Square Register Android app has few crashes. Getting there requires a systematic approach: coding defensively, gathering information, measuring impact and improving architecture.

This talk presents our concrete steps towards lowering the crash rate, from the general philosophy to the tools we use, together with real crash examples.

Speaker Bio

Pierre-Yves Ricau: Android baker at Square. I started having fun with Java & Android as a consultant in Paris, then joined a startup in Barcelona and finally joined Square in San Francisco to work with some of the best engineers in the world. I like good wine & low entropy code.

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CSS Frameworks and The Evolution of Airbnb’s Frontend http://nerds.airbnb.com/css-frameworks-evolution-airbnbs-frontend/ http://nerds.airbnb.com/css-frameworks-evolution-airbnbs-frontend/#comments Tue, 10 Mar 2015 23:50:54 +0000 http://nerds.airbnb.com/?p=176594802 The theme for the month of february was front-end engineering. Engineers, Spike Brehm and Fiona Tay spoke on behalf of Airbnb and we welcomed Jessica Dillon from Bugsnag. The Evolution of Airbnb’s Frontend Over the last few years, Airbnb’s frontend architecture has evolved to keep pace with the rapid advancement happening the JavaScript world. Starting […]

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The theme for the month of february was front-end engineering. Engineers, Spike Brehm and Fiona Tay spoke on behalf of Airbnb and we welcomed Jessica Dillon from Bugsnag.

The Evolution of Airbnb’s Frontend

Over the last few years, Airbnb’s frontend architecture has evolved to keep pace with the rapid advancement happening the JavaScript world. Starting as a humble Rails 2 + Prototype.js app in 2008, the frontend stack powering airbnb.com has gone through a few revisions, including a push towards single-page app architecture with Backbone.js and Handlebars.js, an adventure into isomorphic JavaScript with Rendr (our library for using Node.js to server-render Backbone SPAs), and most recently, a move toward React.js and a re-envisioning of our build pipeline to take advantage of CommonJS, ES6, and a Node.js-based transform system. Spike Brehm, software engineer on the @AirbnbNerds team, will walk through how we approached and executed on these changes. Plus, get excited to see a preview of our new approach to isomorphic JavaScript, allowing us to server-render React components from our Rails app.

Speaker Bio

Spike Brehm is a software engineer at Airbnb who specializes in building rich web experiences. As a JavaScript nerd, he has spent the last few years shipping web apps and prototyping Airbnb’s front-end stack, experimenting with “isomorphic JavaScript” — apps that have the flexibility to run on both the client and sever using the same codebase.

O2: The Life of A CSS Framework

In 2012, a small startup added Bootstrap to our site as a stopgap to make things look better. Never could we have expected that in just 3 years, Airbnb would explode and our design would evolve dramatically. But what’s stayed constant, helping to keep our code sane, is our internal CSS framework. In this talk, I’ll discuss when and why we forked Bootstrap and how maintaining our own system enables beautiful, on-brand design. I’ll also discuss how we’ve rolled out drastic changes for a rebrand and later, a responsive overhaul of a desktop site, using versioning best practices.

Speaker Bio

Fiona Tay is an engineer on the Core Web team at Airbnb, where she develops strategy and build tooling for the web platform. She’s architected engineering strategy for our rebrand across web and email. She’s currently working on making airbnb.com responsive. She’s a fan of design, performance and testing.

Implementing a visual CSS testing framework

Working with large CSS codebases can be hard. Large-scale refactors, or even just tweaking styles on our more general elements, could end up having unintended consequences on the rest of the site. To catch these problems we would manually check every page on our site, which is a slow and error-prone approach. We needed a better way to test our CSS.

We looked up various ways to test CSS, including trying libraries like Huxley. Although some of it was what we needed, the frameworks ultimately didn’t end up integrating well enough for what we wanted to do. After looking at the minimal amount of support each framework was adding, we decided it would be best to rollout our own visual diffing system for our specific needs. We decided to outline a plan that included the components we’d need, and figure out from there the right tools for the job.

In this talk, I’ll walk through how we at Bugsnag implemented a visual CSS testing framework using RSpec & Selenium, using automatic screenshot comparison to catch style regressions.

Speaker Bio

Jessica Dillon is a self taught full-stack software engineer in the heart of San Francisco. She works at Bugsnag, the leading real-time crash detection service for mobile and web applications. Her expertise runs the gamut from developing rich in-browser applications to building service-oriented backends. When not coding or playing games, she likes to hang out with her dog named Boo.

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Surviving at Scale: Lessons from Airbnb and LinkedIn http://nerds.airbnb.com/surviving-scale-lessons-airbnb-linkedin/ http://nerds.airbnb.com/surviving-scale-lessons-airbnb-linkedin/#comments Thu, 29 Jan 2015 17:45:06 +0000 http://nerds.airbnb.com/?p=176594732 We are super excited to host our first tech talk of 2015! With the new year comes a new schedule of tech talks happening once a month. Each talk will be carefully curated with multiple speakers and a cohesive theme. The theme this month is scaling and infrastructure with Airbnb engineers, Ben Hughes and Jon […]

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We are super excited to host our first tech talk of 2015! With the new year comes a new schedule of tech talks happening once a month. Each talk will be carefully curated with multiple speakers and a cohesive theme. The theme this month is scaling and infrastructure with Airbnb engineers, Ben Hughes and Jon Tai and the co-founder and head of engineering at Confluent, Neha Narkhede.

Scaling Things That Don’t Scale: Scalability and Reliability at Airbnb

Paul Graham says to do things that don’t scale, and this advice has served us very well at Airbnb. By 2012, guests had booked more than 10 million nights in 192 countries. Years of exponential growth were great for our business, but hard on our infrastructure.

In early 2013, scaling issues began to affect our user experience. As peak summer travel season ramped up, external services took longer to respond, background tasks overwhelmed our database, and memory usage grew unchecked. We started having downtime several days a week, and responding to incidents was consuming more and more engineers’ time.

A small group of us started on a journey to improve reliability and scalability. We added instrumentation, got scientific about timeouts, fixed bad queries, and threw a lot of hardware at the problem. By the end of the year, not only did we have more users and bookings than ever before, but we had improved our response time and uptime as well. We didn’t accomplish this by doing a major rewrite, removing functionality, or disrupting other teams; we accomplished this by dedicating a small team to work on application reliability, focusing on fundamentals, and working to better understand our systems.

In this talk we will share what we did to improve reliability and scalability, how we shifted from tactics to strategy, and the lessons we learned along the way.

Speaker Bio

Ben Hughes is a Software Engineer at Airbnb focusing on reliability and scalability. He was previously a cofounder of NabeWise, a neighborhood information startup that was acquired by Airbnb in 2012. Jon Tai is a Software Engineer on the Production Infrastructure team at Airbnb. Beyond scaling software systems, he works to build tooling and evangelize best practices among the engineering team. Prior to Airbnb, Jon was an engineer at IGN Entertainment, where he helped re-architect and scale out IGN’s media platform.

Real-time stream processing at scale using Apache Kafka and Samza

We are enjoying something of a renaissance in data infrastructure. The old workhorses like MySQL and Oracle still exist but they are complemented by new specialized distributed data systems like Cassandra, Redis, Druid, and Hadoop. At the same time what we consider data has changed too–user activity, stock tickers, gaming events, monitoring, logging and other event data are becoming first class citizens for data driven companies. Taking full advantage of all these systems and the relevant data creates a massive data integration problem. This problem is important to solve as these specialized systems are not very useful in the absence of a complete and reliable data flow.

One of the most powerful ways of solving this data integration problem is by restructuring your digital business logic around a centralized firehose of immutable events. Once a company’s data is captured and available as real-time streams, processing this data becomes the next challenge. Stream processing is an essential part of real-time data systems today, and is used for building news feeds, real-time analytics, metrics, alerts and monitoring.

At LinkedIn, we successfully moved virtually all data flow (500 billions events a day) to real-time structured logs using Apache Kafka. This architecture has influenced a lot of companies worldwide in doing the same and Apache Kafka is used in production at hundreds of companies [https://cwiki.apache.org/confluence/display/KAFKA/Powered+By] for similar use cases.

In this talk, I will share our experience of successfully building LinkedIn’s data pipeline infrastructure around real-time streams on top of Apache Kafka and Apache Samza. These lessons are hugely relevant to anyone building a data driven company.

Speaker Bio

Neha Narkhede is co-founder and head of engineering at Confluent. Previously, she was responsible for LinkedIn’s petabyte scale streaming infrastructure supporting hundreds of billions of events per day. She is also one of the initial authors of Apache Kafka and serves as a PMC member and committer for the project. In the past she has worked on search within the database at Oracle and holds a Masters in Computer Science from Georgia Tech.

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Payments at Airbnb http://nerds.airbnb.com/payments-airbnb/ http://nerds.airbnb.com/payments-airbnb/#comments Wed, 17 Dec 2014 20:29:18 +0000 http://nerds.airbnb.com/?p=176594675 Talk Abstract Payments at Airbnb is challenging because it operates at the core of a global marketplace to create trust. No single solution exists to meet our needs. Going global involves supporting multiple currencies and payment methods but it also involves nuanced complexities that are unique to local markets. It’s very common for our problems […]

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Talk Abstract

Payments at Airbnb is challenging because it operates at the core of a global marketplace to create trust. No single solution exists to meet our needs. Going global involves supporting multiple currencies and payment methods but it also involves nuanced complexities that are unique to local markets. It’s very common for our problems to cross different domains such as product, compliance, growth, finance, and engineering infrastructure. Airbnb’s two-sided marketplace includes guests and hosts who introduce two different payment problems: collecting and distributing money. Our payments platform also supports other activities in the marketplace such as photographers, translators, trip services, and more in the future.

We’ll talk about building end-to-end systems (upstream and downstream) that process billions of dollars in a reliable and scalable way. Want to know how to change tires while driving in a production environment that has significant money flow? Want to know how to confidently sprint instead of walk with code on a frequent basis? As a result of Airbnb’s rapid growth, its Payments platform has evolved quite a bit and we’d like to talk about it while also providing concrete tips based on our experience.

Speaker Bio

Ian Logan is an Engineering Manager at Airbnb. He joined Airbnb over 3 and a half years ago as the first payments engineer, bringing his experience working in investment banking at BlackRock, Barclays Global Investors, and Morgan Stanley to a new problem of payments in the sharing economy. During his time at Airbnb, Ian worked on all aspects of core payments technology and built its original foundation. Currently, Ian leads the engineering teams responsible for Payments, Trust & Safety, and Internal Products at Airbnb.

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Decentralized Payments with Bitcoin http://nerds.airbnb.com/decentralized-payments-bitcoin/ http://nerds.airbnb.com/decentralized-payments-bitcoin/#comments Wed, 10 Dec 2014 18:54:33 +0000 http://nerds.airbnb.com/?p=176594641 Talk Abstract So you’ve heard of Bitcoin, a global digital currency with an avid following, and a wildly fluctuating price. But the real power of Bitcoin stems from its underlying decentralized ledger, the blockchain. In this talk, Adrian will take a deep dive into the blockchain, and look at how transactions are generated and broadcast […]

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Talk Abstract

So you’ve heard of Bitcoin, a global digital currency with an avid following, and a wildly fluctuating price. But the real power of Bitcoin stems from its underlying decentralized ledger, the blockchain.

In this talk, Adrian will take a deep dive into the blockchain, and look at how transactions are generated and broadcast in a completely trustless peer-to-peer network. He will discuss what role miners play in this network, and whether the blockchain network could exist independent of the Bitcoin currency. Finally, he will look at some of the potential future applications of Bitcoin and the blockchain, including sidechains and decentralized asset tracking.

Speaker Bio

Adrian Macneil is Director of Engineering at Coinbase, the largest bitcoin company in the world. Originally from New Zealand, Adrian has previously been involved with several e-commerce and payments startups, and has seen first hand the difficulties faced by companies looking to innovate using the current financial networks. Adrian moved to the US in early 2014, and has since helped Coinbase grow from 5 to 20 engineers, and launch in 19 countries and 22 languages. In his spare time, Adrian can be found traveling, snowboarding, and spreading the word of bitcoin.

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Randomness and Fraud http://nerds.airbnb.com/randomness-fraud-2/ http://nerds.airbnb.com/randomness-fraud-2/#comments Wed, 03 Dec 2014 23:25:49 +0000 http://nerds.airbnb.com/?p=176594604 Talk Abstract Over the course of three years, we’ve built Stripe from scratch and scaled it to process billions of dollars a year in transaction volume by making it easy for merchants to get set up and start accepting payments. While the vast majority of the transactions we process are legitimate, Stripe does need to […]

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Talk Abstract

Over the course of three years, we’ve built Stripe from scratch and scaled it to process billions of dollars a year in transaction volume by making it easy for merchants to get set up and start accepting payments. While the vast majority of the transactions we process are legitimate, Stripe does need to protect its merchants and itself from rogue individuals and groups seeking to “test” or “cash” stolen credit cards. In this talk, I’ll discuss the two types of fraud Stripe faces—merchant fraud and transaction fraud—and how our approach to both has evolved over time. I’ll then demonstrate how “randomness” helps us combat fraud in the three stages of the model-building process. Specifically, I’ll focus on how fraud often appears less random than legitimate behavior (feature generation), how our in-house, distributed random forest learner allows us to build models on huge data sets with more control over how the random splits are made (model training), and how the introduction of randomness in the production scoring environment allows us to reason about counterfactuals (“what would have happened if we hadn’t intervened?”) and evaluate candidate models without production experiments (model evaluation).

Speaker Bio

Michael Manapat is a Software Engineer on Stripe’s Machine Learning team. He was previously a Software Engineer at Google, a Postdoctoral Fellow in and Lecturer on Applied Mathematics at Harvard, and a graduate student in mathematics at MIT.

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SDK Mindset http://nerds.airbnb.com/sdk-mindset/ http://nerds.airbnb.com/sdk-mindset/#comments Wed, 03 Dec 2014 23:25:30 +0000 http://nerds.airbnb.com/?p=176594599 Talk Abstract Writing software is difficult. Bugs happen. Users find weakness and hit them with their mallets repeatedly. Complexity hides and exponentiates with every new feature. When developing SDKs—that is, code we write to run in others’ systems—these problems are critical and acute. We will talk about a number of scenarios we’ve encountered to highlight […]

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Talk Abstract

Writing software is difficult. Bugs happen. Users find weakness and hit them with their mallets repeatedly. Complexity hides and exponentiates with every new feature. When developing SDKs—that is, code we write to run in others’ systems—these problems are critical and acute. We will talk about a number of scenarios we’ve encountered to highlight the difficulties of building and shipping SDKs: backwards compatibility, flexibility, abstraction, understandability, shippability, adoption, beta partners, communication, etc.

Speaker Bios

Ben Mills is a software developer who works on the Braintree SDKs primarialy on the back-end.

Mickey Reiss is an iOS developer who works on Braintree’s iOS SDK. Braintree is a payments company who’s goal is to provide developers with a foundation to build applications on.

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The Future of App Deployment http://nerds.airbnb.com/future-app-deployment/ http://nerds.airbnb.com/future-app-deployment/#comments Wed, 03 Dec 2014 23:25:07 +0000 http://nerds.airbnb.com/?p=176594596 Talk Abstract Writing an app is one thing, deploying it to a production ready environment and keeping it online in the face of countless potential scenarios of adversity is an entirely different beast. Not only does it currently still involve a fair bit of expertise when it comes to unix-fu, it also involves keeping an […]

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Talk Abstract

Writing an app is one thing, deploying it to a production ready environment and keeping it online in the face of countless potential scenarios of adversity is an entirely different beast. Not only does it currently still involve a fair bit of expertise when it comes to unix-fu, it also involves keeping an eye out on the latest software and configure them properly to combat things like security breaches. This is all generally considered tedious and cumbersome work, and often outside the domain of knowledge of developers. Wouldn’t it be great if we didn’t need to go through as many hoops as we need to do today and make it more developer friendly?

This talk will go over the most important steps currently involved in setting up a production environment for your a web app and will propose alternative approaches as well in the form of new software solutions developed by Phusion. This talk will focus on app deployment, monitoring and server provisioning, but will also touch upon topics such as UI design and UX as the latter plays an important part in making things more accessible. More specifically, we’ll discuss Docker, Polymer, Node, Rails, Phusion Passenger, Union Station and much more.

Speaker Bios

Hongli Lai is the co-founder and CTO of Phusion. His work involves all layers of an application stack. Be it from Phusion Passenger for deployment, to tinkering on Docker baseimage, his work has helped deploy hundreds of thousands of sites.

Tinco Andringa is a full stack software engineer at Phusion. During his time at Phusion he has built Ruby on Rails applications for clients and he is now leading development work on Phusion’s new monitoring solution Union Station. When he is not building Ruby web apps he works on open source software and tinkers on video games.

Goffert van Gool is a Full-Stack Engineer at Phusion, where he works on modern web applications, and high-availability services. He is often experimenting with new technology and how it can be used to improve application architecture.

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