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SoundCloud's web and mobile properties are all built on top of our Public API. While building the user-interface atop a RESTful layer has proven itself a sound decision, the one-size-fits-all nature of a Public API is not ideal. When it comes to data transfer and HTTP resource modelling, each client has their own needs, and in the end hacks and workarounds have to be implemented in both clients and servers. Feature development also becomes complicated, with coordination between multiple teams required for every single little feature. SoundCloud is now moving to a different model, where clients have their own façade APIs, modelled after their core characteristics and needs. We are also using the architecture to break away from Conway’s Law and building more cross-functional, end-to-end teams. From: http://gotocon.com/berlin-2013/presentation/APIs:%20The%20Problems%20with%20Eating%20your%20Own%20Dog%20food To implement this, a lot of change in our architecture, tech stack and development processes were required. In this talk we will explore the challenges we had, the options we investigated and how ultimately SoundCloud decided to move forward.

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SoundCloud's microservice architecture is built mostly in Scala, using Finagle as its distributed systems workhorse. Finagle is an RPC system for the JVM, and it is based on a pipes-and-filters architecture that maps very nicely to functional programming concepts of higher-order functions and combinators. Over the past few years we have found that it is extremely useful to go even a step further and think of microservices as functions themselves. In this talk let's explore how SoundCloud uses Scala and Finagle, and how we started thinking of a microservices architecture as a special case of a functional system.

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SoundCloud is the largest repository of audio on the web, used by more than 200 million people every month, who upload more than 11 hours of audio every minute. Like so many others, we have migrated from a typical monolithic architecture to microservices. While the benefits brought by this style of SOA to our productivity and reliability are clear, the architecture required some non-obvious changes in the way we operate systems, and a way to tackle the overhead associated with having hundreds of small moving parts to serve every request. In this talk we’ll share the toolkit and strategy SoundCloud uses to keep its microservices explosion manageable. What do we do about the operations overhead? How to spread devops skills across teams to support the “you build it, you run it” vision? How to deal with breaking changes and asynchronous behaviours? How to deal with chatty interactions? Which protocol? How do I even get a diagram telling me how all this stuff is put together?

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TALK #2: Microservices vs. The First Law of Object Design We've been breaking systems and application into smaller components for a long time now. From Component-Based Design to Distributed Objects to SOA to what is today's preferred golden hammer: microservices. One definition of microservices is that it is a flavor of SOA that emphasizes many specialize services versus a few more generalist ones. Often these microservices are so small that they take care of a single "object". Distributed objects aren't new to this industry, and in 2003, Martin Fowler wrote a classic article where he discusses several problems with this model, and proposes the First Law of Distributed Objects: "Objects have been around for a while, and sometimes it seems that ever since they were created, folks have wanted to distribute them. However, distribution of objects, or indeed of anything else, has a lot more pitfalls than many people realize, especially when they're under the influence of vendors' cozy brochures. This article is about some of these hard lessons-lessons I've seen many of my clients learn the hard way... my First Law of Distributed Object Design: Don’t distribute your objects!" Reinventing the wheel is nothing new in our field, but if microservices are meant to be small, how can we avoid the same problems from the past? What are the technologies, architectures, protocols, and practices we need in place to make sure that our microservices architecture isn't just the largest bowl of spaghetti this organization has ever cooked? SPEAKER: Phil Calçado, Director of Software Engineering at DigitalOcean Phil Calçado works at DigitalOcean, where he helps build the cloud for developers. Before that, he spent four years building the team and architecture behind SoundCloud's move from a monolith to microservices. He tweets at @pcalcado writes at http://philcalcado.com.

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PicPay is the largest digital wallet in Latin America. We offer peer-to-peer payments, BNPL, credit cards, personal loans, insurance, investing, trading, and other financial products to 60 million people and 5 million merchants, processing over $20 billion yearly. But just three years ago, in 2019, PicPay was 30 engineers in a small office working on a single product for a few million users. Growing our product portfolio, team size, and the number of transactions by several orders of magnitude so quickly was as chaotic as you might imagine—but we've done it! Our approach gave teams and engineers radical autonomy to choose the best tool, process, and technology for their area. This strategy was invaluable in handling hypergrowth, but as we stabilize as a business and product, we have realized that what took us here isn't what will keep us moving forward. In this talk, let's explore the consequences of how we dealt with our hypergrowth phase and what are the changes and initiatives we have put in place to make sure that we keep growing and pushing the envelope—but at a manageable pace this time around. Phil Calçado is the Global CTO at PicPay. Before PicPay, Phil was Senior Director of Engineering at SeatGeek, leading the team that built the live events platform used by 44 million people worldwide. He has also led the platform team at Meetup/WeWork, worked on Linkerd - the pioneering Service Mesh, and headed product engineering for DigitalOcean and SoundCloud, both pioneers in adopting Microservices architectures. https://plus.qconferences.com/plus2022/presentation/afterparty-refactoring-after-100x-hypergrowth

don't try this at home: self-improvement as a senior leader

Presented at LeadingEng New York 2022 (https://leaddev.com/leadingeng-new-york/video/dont-try-home-how-practice-self-improvement-senior-leader) -- Most of us have developed our expertise as engineers through a mix of literature and experimentation. The software industry moves at a higher speed than others because we can try and study complex, real-world systems in the comfort of our bedrooms and personal Github accounts. When you become a leader, especially one who leads other leaders, things get a little more complicated. There are books, but they tend to contain generic advice. There are patterns, but the nature of the job makes it harder to identify when and how to apply them. In this session, I want to walk through a few things that have worked for me when you don't have a lab to try things out. Let's explore processes, tools, and resources to continuously improve your skills and expertise when there is no StackOverflow and no coding dojos. Phil Calçado is Global CTO at PicPay, the largest digital wallet in Latin America. He leads a team of more than 1,500 engineers building financial products for 60 million users and processing over four billion dollars yearly. Before PicPay, Phil was Senior Director of Engineering at SeatGeek, where he led the team that built the live events platform used by 44 million people worldwide. He also has led the platform team at Meetup/WeWork, worked on Linkerd - the pioneering Service Mesh, and headed product engineering for DigitalOcean and SoundCloud, both pioneers in the adoption of Microservices architectures.

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For the last ten years or so, many companies have focused on migrating from larger, monolithic systems and applications towards a specific style of Service-Oriented Architecture called Microservices. The promise was that these smaller, loosely-coupled, and independently developed components would increase productivity and safety for organizations, as large and complex business challenges can be broken down into smaller and simpler components. However, even before most organizations were able to fully migrate to this new architecture and enjoy its promised benefits, a new iteration of cloud computing has been made available in the shape of Serverless platforms such as AWS Lambda, and Google Cloud and Microsoft Azure Functions. Now lots of companies found themselves conflicted between abandoning their traditional microservices approach towards Serverless, often even before they have fully migrated to it from the legacy systems. After leading successful Microservices adoption at SoundCloud and DigitalOcean, recently at Meetup I have faced the challenge of pivoting from a traditional monolith-to-microservices migration to a cloud-native platform. In this talk, let's discuss the fundamental concepts, technologies, and practices behind Microservices and Serverless, and how a software architect used to distributed systems based on microservices needs to change their mindset and approach when adopting Serverless.

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