Evolutionary Architecture is rapidly becoming seen as the responsible approach to technology rather than some crazy idea that leads to chaos and despair. This talk follows the evolutionary path of Evolutionary Architecture first. We’ll then try to see where such ideas might lead us in the future.

We are the modern day scribes. Nothing happens in our society without us. But so far, we are unorganized, undisciplined, and we have no unifying ethics or standards. Society is becoming aware of us. Software developers have become both villains and heroes in our culture. More importantly, our society depends critically upon us. What oath, if any, should we swear? How would we enforce it?

Mob Programming is a development practice where the whole team works on the same thing, at the same time, in the same space, and on the same computer. It is a whole-team approach to doing all the work the team does including designing, coding, testing, and working with the customers, users and other stakeholders.

This is an evolutionary step beyond pair programming, and accentuates face-to-face communication, team alignment, collaboration, and self-organizing team concepts of the Agile approach to software development. Mob Programming can be a highly effective approach to software development.

Please join me as I share how the concept got started, the benefits, techniques we use, and some of the problems we’ve faced.

In this session, you’ll learn about game design: the art and science of constructing enjoyable, engaging games. We aren’t doing any coding, and we’re not talking game engine development – instead, we’ll be taking a deep dive into game design theory, using it to understand how people interact with rules, and how to use it to improve your community, your company, your project, and your software.

Video games are the most glamorous of the electronic arts, but splashy graphics and amazing sound aren’t the defining feature of games. Games are the world’s only interactive artistic medium, and good interaction needs to be designed. Today’s master crafters of interaction design are game designers.

In this session, you’ll get a fresh perspective on user experience design and community engagement by understanding how people are interacting with the fastest-growing form of entertainment in the world.

Topics covered in this session include:

• Why games work, and how to analyse and build engaging experiences
• The Mechanics-Dynamics-Aesthetics framework: what it’s good for, and how to use it
• How to understand what a game’s doing, and how to build for fun

We’ll take this knowledge and apply it to real world examples in the realms of UX and UI design, community management, project management, and company building, as well as a few examples from the actual game development industry.

KEYWORDS

Design, Games, Rules, Interaction, UX

While many of the distributed systems we operate today are built with language like Java and Go, distributed programming has a long history of innovation and adoption of its ideas. This include innovations seen all throughout the various fields of computing: novel type systems for dynamic languages; the concept of the promise, now a standard programming technique in web development; and unified models of programming when data lives across nodes. Some of these ideas had major impact, while some fell incredibly short. Many technically superior ideas were not adopted simply because they were too “research” focused.

During this talk, we will present the history of RPC and current uses in industry like Finagle and gRPC, and why RPC may not be the best abstraction for building your next distributed application.

Artificial Intelligence (AI) in general, and Machine Learning (ML) specifically are indisputably the hottest fields in the industry at the moment and have demonstrably advanced many areas of technology and science alike: web page classification, spelling correction, search ranking, graph building, large-molecule database screening for receptor-protein binding, predictive analytics, etc. etc. However, despite all the aforementioned advances, there are classes of problems (e.g. where “baselining” is required, such as network security) where ML is not a suitable technology to apply to. In fact, there are facets of ML that we simply don’t yet understand. In this session we describe the basics of AI and ML, discuss examples in network security and why ML is not a suitable solution, and finally discuss general shortcomings ML, namely reasoning and debugging.

KEYWORDS

Machine Learning, Deep Learning, Artificial Intelligence, General Intelligence, Machine Cognition, Data Science, Analytics, Security

Business applications are demanding ever-greater flexibility, yet responding to evolving requirements is still a challenge for software developers. Programming languages and frameworks are often brittle and inflexible, prone to unpredictable second-order effects which make change not merely difficult but often risky. Can we do better? This talk will explore techniques for designing software systems to be both robust and adaptable.

For examples of patterns which enable flexibility, this talk will focus on Clojure, a dynamically-typed functional language; Datomic, a transactional, distributed database; and clojure.spec, a dynamic testing and validation library.

With the rate at which tooling evolving at an accelerating rate, how does your organization keep up? What does a winning migration strategy from static iron to a modern infrastructure built on immutable microservices look like? Nuke and pave the world, and embrace a forklift upgrade to a new technology stack? Dynamic secrets, infrastructure as code, immutable servers, service discovery, and cluster schedulers are becoming the norm, learn how to integrate these puzzle pieces successfully into your organization and applications.

KEYWORDS

Operations, Organisation, Change, Cluster Scheduler, Service Discovery, Consul, Nomad, Terraform, Vault, Fabio, Dynamic Secrets

Personal career management is much like project management, and the same things that trip us up in the technical realm – formulation, resource allocation, estimation, risk assessment – are also too often absent from our thinking about our own career development. How might we benefit from applying our technical thinking to what we normally think of as a soft topic? What lightweight approaches may help us better achieve personal goals?

KEYWORDS

Professional Development, Personal Career Management, Estimation, Decision Analysis, Planning, Formulation

The frontend ecosystem is a rich and complex environment. Developing high quality web applications means understanding browser quirks, web performance, testing strategies, and API design. Consistently getting all of this right is difficult in an organization where hundreds of engineers are collaborating on the same codebase.

In this talk we look at the solutions Facebook has developed for data fetching, code delivery, performance profiling, and testing React applications. And we review the methodologies Facebook uses when designing new infrastructure like Relay and GraphQL.

KEYWORDS

React, GraphQL, Redux, Flux, Relay, JS, Frontend, Performance

As programmers, we tend to treat data as generic stuff to feed into the algorithms and architectures we love. We don’t really pay attention to the data itself, especially when we have terabytes or petabytes of it.

Huge mistake. And we are trained to make it! It is why it takes a year for a new programmer to be productive at working on the Google ranking algorithm. It held back progress on genome sequencing algorithms. It has cost me more time than I’d care to imagine.

The good news is that you don’t have to look at all of your petabytes of data. Just eyeball a ten record sample when you start, and repeat as you work the data. Even then, eyeballing can be hard work, and done wrong can be worse than doing nothing. But done right, it can be fun, and the data will almost always surprise you. Better yet, you can use your favorite algorithms and architectures to build tools to make eyeballing your data easier and much more effective.

The bitcoin network is the largest distributed computer in existence. It is a solution – suggested in 2008 by Satoshi Nakamoto – to the problem of distributed consensus that many scientists thought impossible.

This talk will be fast-paced and highly technical, and will explain how Bitcoin actually works. The first three times you think you understand Bitcoin you are probably wrong. After this talk you can bump your wrongness down by one.

KEYWORDS

Bitcoin, Distributed Consensus, Blockchain, Cryptocurrency

Modern systems can fail in spectacular ways. Failure isn’t a question of if, but when. Resilient systems can endure and gracefully recover from failures, but ensuring your system has these properties requires thought and some deliberate architectural decisions. Join me in this talk as I attempt to find answers in academic research and industry to build a more robust system. I will also share the lessons learned while applying these patterns at Fastly and key takeaways that you can carry to your own systems.

KEYWORDS

Architecture, Patterns, Resilience, Distributed Systems, Robustness

We built a reference application for microservices (https://microservices-demo.github.io/) and along the way we heavily (ab)used container technologies. From the services, to databases, to builds, tests, through continuous integration and deployment pipeline. In this talk I’ll look at how we leveraged containers throughout, where this approach was really beneficial and where it turned out to be more hindrance than stimulus.

KEYWORDS
Docker, Containers, Cloud, Microservices, Deployment, Continuous Integration

Connecting with other people, finding a sense of belonging and the need for support are natural human desires. Employees who don’t feel supported at work don’t stay around for long — or if they do, they quickly become unmotivated and unhappy. At a time when organizational structures are flattening and workforces are increasingly fluid, supporting and connecting people is more important than ever. This is where organizational communities of practice come in.

Modern organizations with cross functional teams, have the ability to silo organizations into teams, programmes and functions. They can take people further away from other people that they can learn with. We need a way to bring people with the same concerns back together and this is what communities of practice do.

Communities of practice have many valuable benefits for both individuals and organizations. They include accelerating professional development; breaking down organizational silos; enabling knowledge sharing and management; building better practice; helping to hire and retain staff; and making people happier.

In this session, Emily will pull from experiences of building and growing communities of practice at the Government Digital Service, other government departments and organizations as well as case studies from her ongoing research into this area. You will gain an understanding of why community of practice are so important in modern organizations and practical advice to those who are thinking about setting one up or looking to reinvigorate one that already exists.

KEYWORDS

Continuous Delivery, DevOps, Software Engineering, Quality

Why did the normally shy and reticent member of my team do what he did last Thursday? Why did my short-tempered, brutish CEO rise to that occasion with such warmth and largesse? For the last ten months, people have been asking me if I am myself. Who else could I possibly be? Such questions are intriguing and consequential for understanding ourselves and our organizations.

This presentation provides guidance for answering them based on Dr. Little’s work on free traits, personal projects and wellbeing. A central tenet of this perspective is that people often act out of character in order to advance their personal projects. Such behaviour may puzzle us, and we wonder what is going on. What is going on is both complex and deeply human. Audiences come away with some very practical examples of how they drive each other to distraction and with a clearer understanding of why it is essential to their organizations that they continue to do so.

The presentation merges psychological insights with an exceptionally motivating message about respect for differences between individuals. Dr. Little’s presentations have been described by highly diverse groups as ‘utterly hilarious’ and ‘profoundly moving,’ suggesting he is a ‘cross between Robin Williams and Einstein.’

How fast can we possibly make microservices?

You can have sub-microsecond wire-to-wire response times using off-the-shelf hardware and familiar languages. I’ll show you how to put the technology in place, but that’s the easy part. Why on earth would you want to do this, and how could you possibly stay agile?

An FPGA-powered network adapter can have a response packet on the wire before the server operating system has dispatched the incoming packet, and well before a high-level web stack has even heard about it.

To do this, you need to use hardware design for part of your microservice; you’ll use a programming language that allows intricately parallel expressions. I’ll show you how to do this using Haskell to compile to VHDL, then we’ll tackle the scary parts:

• How do I test and deploy this?
• Can I keep my continuous refactoring and continuous delivery?

We’ll walk through building a toy microservice, and see how to test and update it. We’ll talk about how this fits into the broader architecture of your service, and (crucially) how to convince the people around you to enjoy the challenge.

FGPA, Microservices, Haskell, Hardware Design, Test, Deploy. Continuous Integration

Distributed Systems are difficult to build and test for two main reasons: partial failure & asynchrony. These two realities of distributed systems must be addressed to create a correct system, and often times the resulting systems have a high degree of complexity. Because of this complexity, testing and verifying these systems is critically important. In this talk we will discuss strategies for proving a system is correct, like formal methods, and less strenuous methods of testing which can help increase our confidence that our systems are doing the right thing

Change in an organization is really hard. This is especially true when a company that was once on the forefront of innovation finds itself having lost that luster through its own growth & success. The past few years there has been a transformation happening at PayPal that is touching every part of the organization to make it innovative again. At the heart of this change is engineering innovation coupled with a new, close partnership between product, design and engineering.

Can your organization be changed? From Bill’s experience at Yahoo!, Netflix, PayPal and consulting with numerous companies he believes there are some core principles you can employ to drive transformation that are all centered around the customer. The question Bill will explore is “How can engineering and design be the catalyst for that change?” While this talk will be inspirational, it will take an honest (and humorous) look at what has worked and what hasn’t worked so well in trying to scale change.

Governments collect a lot of data. Data on air quality, toxic chemicals, laws and regulations, public health, and the census are intended to be widely distributed. Some data is not for public consumption.

This talk focuses on open government data — the information that is meant to be made available for benefit of policy makers, researchers, scientists, industry, community organisers, journalists and members of civil society.

We’ll cover the evolution of Linked Data, which is now being used by Google, Apple, IBM Watson, governments, non-profits, and thousands of others worldwide.

Next we’ll delve into the evolution of the U.S. Environmental Protection Agency’s Open Data service that we implemented using Linked Data and an Open Source Data Platform. Highlights include how we connected to hundreds of billions of open data facts in the world’s largest, open chemical molecules database PubChem and DBpedia.