Reactive architecture patterns allow you to build self-monitoring and self-healing systems that can react to both internal and external conditions without human intervention. How would you like to design systems that can automatically grow as the business grows, automatically handle varying load (cyber Monday?), and automatically handle (and repair) internal and external errors, all without human interaction? I'll show you how to do this with your current technology stack (no special languages, tools, frameworks, or products). In this two-part session I will leverage both slides and live coding using Java and RabbitMQ to describe and demonstrate how to build reactive systems. Get ready for the future of software architecture - that you can start implementing on Monday.

Part 1 Agenda:

• Reactive systems introduction
• Channel Monitor Pattern (self-awareness)
• Consumer Supervisor Pattern (scalability and elasticity)
• Workflow Event Pattern (error handling)

Reactive architecture patterns allow you to build self-monitoring and self-healing systems that can react to both internal and external conditions without human intervention. How would you like to design systems that can automatically grow as the business grows, automatically handle varying load (cyber Monday?), and automatically handle (and repair) internal and external errors, all without human interaction? I'll show you how to do this with your current technology stack (no special languages, tools, frameworks, or products). In this two-part session I will leverage both slides and live coding using Java and RabbitMQ to describe and demonstrate how to build reactive systems. Get ready for the future of software architecture - that you can start implementing on Monday.

Part 2 Agenda

• Thread Delegate Pattern (scalability)
• Threshold Adjust Pattern (automatic configuration and self-learning)
• Producer Control Flow Pattern (self-healing)

There are many different uses for Apache Kafka. It can be used as a streaming broker, event broker for transactional data, and even a database. This session is about understanding streaming architecture and how to implement it using Apache Kafka. I start this session by talking about some of the streaming architecture patterns, then dive into how Apache Kafka works using the Core API. Using live coding examples in Apache Kafka, I also talk about the differences between Kafka and regular messaging (RabbitMQ, ActiveMQ, etc.) and when you should use each. I end this session by putting everything together, showing an actual streaming architecture using Kafka within a Microservice ecosystem for gathering various metrics for business and operational monitoring and reporting.

Agenda:

• Streaming architecture patterns
• Kafka overview
• Kafka producers and consumers
• Kafka vs. standard messaging
• Streaming examples in a microservices ecosystem

Even though teams are gaining more experience in designing and developing microservices, nevertheless there is still a lot to learn about this highly distributed and somewhat complicated architecture style. Unfortunately, lots of microservices anti-patterns and pitfalls emerge during this learning curve. Learning about these anti-patterns and pitfalls early on can help you avoid costly mistakes during your development process. While anti-patterns are things that seem like a good idea at the time and turn out bad (see martinfowler.com/bliki/AntiPattern.html), pitfalls are those practices that are never a good idea at the time - ever. In this session I will cover some of the more common anti-patterns you will likely encounter while creating microservices, and most importantly describe some of the techniques for avoiding these anti-patterns.

Agenda

• Function-Driven Identification AntiPattern
• I Was Taught to Share AntiPattern
• The Timeout AntiPattern
• Hop on the Bus AntiPattern
• Data-Driven Migration AntiPattern

Even though teams are gaining more experience in designing and developing microservices, nevertheless there is still a lot to learn about this highly distributed and somewhat complicated architecture style. Unfortunately, lots of microservices anti-patterns and pitfalls emerge during this learning curve. Learning about these anti-patterns and pitfalls early on can help you avoid costly mistakes during your development process. While anti-patterns are things that seem like a good idea at the time and turn out bad (see martinfowler.com/bliki/AntiPattern.html), pitfalls are those practices that are never a good idea at the time - ever. In this session I will cover some of the more common pitfalls you will likely encounter while creating microservices, and most importantly describe some of the techniques for avoiding these pitfalls.

Agenda

• Grains of Sand Pitfall
• Where's the Acid Pitfall
• Logging Can Wait Pitfall
• Jump on the Bandwagon Pitfall
• Give it a Rest Pitfall

It seems like all we talk about these days is making our architectures more modular. Buy why? In this session I will discuss the drivers and reasons why it is essential to move towards a level of modularity in our architectures. I will discuss and show real-world use cases of distributed modular architectures (specifically microservices and service-based architecture), and then discuss in detail the core differences between microservices and service-based architecture and when you should consider each. I'll end the talk by discussing the most effective way of migrating to modular distributed architectures.

Agenda:

• Drivers for modularity
• Modular distributed architectures
• Microservices vs. service-based architecture
• The move towards modularity

One of the expectations of any software architect is to analyze the current technology environment and recommend solutions for improvement. This is otherwise known as continually assessing architecture vitality. Too many times software architects fail to regularly perform this task, leading to emergency refactoring efforts to save a troubled system from failure. The question is, what does it mean to assess an application architecture? In this session we will explore static analysis metrics and tools and techniques for leveraging those metrics for determining structural decay. Using a real-world large-scale application, I'll show you how to leverage code metrics to find (and fix) structural decay before it gets you into trouble.

Agenda

• Architecture and structural decay
• Architecturally significant code metrics and what they mean
• Interpreting results and tracking metrics
• Code analysis tools and how to use them
• Real-world hands-on architecture analysis using tools and metrics

Traditional approaches to software architecture do not address the core tenet of all agile practices - feedback! We make many of the most important architectural decisions early in the development lifecycle and fail to get accurate feedback on those decisions throughout implementation. Compounding the problem? Agile methods offer no architectural advice. This session explores several architectural practices that help increase architectural agility.

What’s the goal of architecture? To serve as a blueprint of the system that everyone understands? Possess the flexibility to evolve as new requirements emerge? To satisfy the architectural qualities, including performance, security, availability, reliability, and scalability? Yes. Yes. Yes. At the heart of these three questions are the three pillars of architecture - social, process, and structure. But how do we create software architectures that achieves all of these goals? And how do we ensure no disconnect occurs between developers responsible for implementation and architects responsible for the vision? In this session, we’ll explore several principles to increase architectural agility and provide some actionable advice that will help you get started immediately.

Recently, microservices have take the development community by storm. Though a modern architectural paradigm, the underlying principles of microservices are embedded across many proven traditional architectural approaches, especially modularity. At the end of the day, microservices are just one way to the increase modularity of our software system. But there are others.

In this session we will examine several different ways to modularize large software systems. We'll start with the “modular monolith” and demonstrate how this modular monolith gives us a significant degree of architectural agility to evolve the architecture to microservices by incrementally breaking pieces of the application off and deploying them as microservices.

The way we build and deliver software is changing. We must deliver software more quickly than ever before and traditional approaches to software architecture, infrastructure and methodology do not allow us to meet demand. We’ve reached the limits of agility through process improvement alone, and further increases demand we focus on improving architecture, infrastructure, and methodology simultaneously. 12 Factor is an app development methodology for building modern apps in the modern era.

Building modern apps requires modern methods and 12 Factor is an app development methodology that helps development teams build software by emphasizing development practices that meld together modern architectural paradigms with agile practices like continuous delivery for deployment to cloud platforms. In this session, we’ll examine the 12 Factors and explore how to apply them to apps built using Java.

With Java 9, modularity will be built in to the Java platform…Finally! In this session, we explore the default Jigsaw module system and compare it to the alternative module system, OSGi, on the Java platform.

We will demonstrate the impact that Jigsaw will have on our existing applications and identify what we must do to get ready for Jigsaw. You will also see firsthand how to use the Jigsaw module system and the benefits that support for modularity on the Java platform will have on your applications.

Cloud continues to grow in importance in even the most conservative companies’ IT strategies. Because of this, even experienced software architects must confront a new world in which many of our normal architectural assumptions no longer hold. Before we create architectures that leverage cloud infrastructure, we need to rebuild our mental model of infrastructure around the appropriate concepts and principles. The purpose of this session is to do just that.

In this session we’ll:

• tour the current cloud infrastructure landscape
• explore the key business and technology motivators for adopting cloud
• explore the unique aspects of cloud infrastructure that violate our traditional assumptions
• examine the risks associated with adopting cloud infrastructure
• navigate some of the key tradeoffs involved with cloud architecture choices
• overlay traditional architecture patterns and examine their suitability to cloud
• define a cloud native architecture that is optimized to exploit the uniqueness of the cloud environment

The learner should leave this session prepared for deeper dives into cloud native architecture patterns and migration strategies.

NOTE: We'll cover roughly 50% of the material in Part 1.

Now that we’ve been equipped with an understanding of how software architectures can exploit the unique aspects of cloud infrastructure environments, it’s time to construct a pattern catalog that can guide our decision making as we journey from concepts and principles to concrete implementations. The software industry has long been motivated by the promise of a “component marketplace” from which we can draw commodity components which can be composed via standardized mechanisms to create powerful systems. These systems are often compared to the myriad of possible creations that can be produced using Lego pieces. The power in the Lego “architecture” is found in the amazing diversity of individual pieces that are composed via a universal system of compatibility. Cloud native architectures approximate the same power via Lego-like patterns.

In this two-part series, we’ll divide the cloud native patterns into two categories:

1. Bricks - how we design cloud native services
2. Mortar - how we compose cloud native systems

In part one we’ll study “Brick Patterns” from the following categories:

• Externalized Configuration
• Externalized State
• Externalized Channels
• Runtime Reconfiguration
• Continuous Delivery via Multi-Version Concurrent Execution
• Brick Telemetry

The learner should leave this session prepared to design and implement cloud native “bricks” that can be composed via any “master builder” of cloud native solutions.

Now that we’ve been equipped with an understanding of how software architectures can exploit the unique aspects of cloud infrastructure environments, it’s time to construct a pattern catalog that can guide our decision making as we journey from concepts and principles to concrete implementations. The software industry has long been motivated by the promise of a “component marketplace” from which we can draw commodity components which can be composed via standardized mechanisms to create powerful systems. These systems are often compared to the myriad of possible creations that can be produced using Lego pieces. The power in the Lego “architecture” is found in the amazing diversity of individual pieces that are composed via a universal system of compatibility. Cloud native architectures approximate the same power via Lego-like patterns.

In this two-part series, we’ll divide the cloud native patterns into two categories:

1. Bricks - how we design cloud native services
2. Mortar - how we compose cloud native systems

In part one we’ll study “Mortar Patterns” from the following categories:

• Service Discovery
• Edge Gateways
• Fault Tolerance
• Event-Driven Systems
• Contract Management
• Integration Telemetry

The learner should leave this session prepared to compose cloud native solutions from any available collection of cloud native “bricks.”

If you’ve been following along, you’ve realized by now that cloud native architectures are fundamentally different than most traditional architectures. Most of the cloud native architectures that we can see in the wild have been built by relatively young companies that began from a zero-legacy state. Architects in more mature organizations are faced with the daunting challenge of building modern systems that exploit the unique characteristics of cloud infrastructure while simultaneously attempting to migrate legacy systems into those same environments, all the while “keeping the lights on.”

Much of the last two years of my career have been spent helping Fortune 500 companies devise cloud native migration strategies, and I’ve built a increasingly large catalog of patterns that have proven useful across multiple systems and industry verticals. In this session we’ll dive into those patterns and more, including:

• the utility of cloud native maturity models
• the cloud continuum: cloud ready, cloud friendly, cloud resilient, cloud native
• the app continuum: evolving toward distributed systems
• criteria for selecting applications to migrate
• the occasionally palatable perils of “lift and shift”
• applying the Strangler Pattern
• leveraging strategic domain-driven design: bounded contexts, context maps, and anti-corruption layers
• insulating from “irreplaceable” legacy systems of record with hexagonal architecture

The learner should leave this session with a tool belt suitable for attacking an upcoming cloud native architecture migration effort.

In this presentation, we'll build, test, and deploy an image-processing pipeline using Amazon Web Services such as Lambda, API Gateway, Step Functions, DynamoDB, and Rekognition.

We'll take a look at some of the following topics:

• Describing serverless deployments with SAM
• Testing lambda functions with SAM Local
• Interacting with AWS API's from lambda functions
• Configuring IAM policies for lambda functions
• Describing workflows of functions with Step Functions
• Deploying with Cloud Formation

The verdict is in: Cloud is NOT a fad. If you haven't already, as a software architect you will be called upon to evaluate various cloud services and determine their suitability for your company's use. In this session, we'll examine ten key criteria that you can use to evaluate any cloud service.

During our time together we'll examine the following criteria:

1. Economics: Price/Cost/Unit of Billing
2. Applicability to Business Case
3. Resiliency Requirements
4. Scalability Requirements
5. Security Requirements
6. Regulatory Requirements
7. Degree of Provider “Lock-In”
8. Required “Undifferentiated Heavy Lifting”
9. Differentiating Features
10. Available Tooling

On the 2017 tour, I introduced the notion of “serverless” and Functions as a Service (FaaS) platforms. We understood the motivation for serverless computing, compared serverless to other cloud-native infrastructure approaches, navigated some architectural tradeoffs, and took a whirlwind tour of the Big 3 FaaS providers.

In this 2018 edition of the talk, we’ll still cover a few of the same themes to bring new folks up to speed, but we’ll also look at what’s changed in this ecosystem over the past year, take a look at new or enhanced features, offerings, runtimes, and programming models, and examine what use cases are becoming popular for serverless computing. We’ll also look at how tradeoffs have evolved, and definitely throw in a few demos.

By the end of this conference you will have learned many new tools and technologies. The easy part is done, now for the hard part: getting the rest of the teamand managementon board with the new ideas. Easier said than done.

Whether you want to effect culture change in your organization, lead the transition toward a new technology, or are simply asking for better tools; you must first understand that having a “good idea” is just the beginning. How can you dramatically increase your odds of success?

You will learn 12 concrete strategies to build consensus within your team as well as 6 technique to dramatically increase the odds that the other person will say “Yes” to your requests.

As a professional mentalist, Michael has been a student of psychology, human behavior and the principles of influence for nearly two decades. There are universal principles of influence that neccessary to both understand and leverage if you want to be more effective leader of change in your organization.

In this session we discuss strategies for getting your team on board as well as when/how to approach management within the department and also higherup in the organization.

It happens to us all; there are simply days where it seems impossible to get anything done. This session focuses on techniques and tips to get into the zone, stay in the zone and to protect your productivity, even in disruptive environments.

Rather than focusing on any one productivity methodology (e.g. GTD) This talk analyzes the internal and external factors that affect our productivity and offers broader strategies to get back on track.

In Part 1, you learned the core principles of influence and persuasion. How to we take this back to the office and apply what we've learned?

We dive deep in to specific strategies to get both the team and the business on board with your ideas and solutions. We cover several realworld patterns you can follow to be more effective and more persuasive. Part 1 was conceptual, part 2 is practical.

In this example-driven presentation, you'll learn how to leverage Spring Boot to accelerate application development, enabling you to focus coding on logic that drives application requirements with little concern for code that satisfies Spring's needs.

For over a decade, Spring has sought to make enterprise Java development easier. It began by offering a lighter alternative to EJBs, but continued to to address things such as security, working with various sorts of databases, cloud-native applications, and reactive programming. And, along the way, Spring even took steps to make itself easier to use, offering Java-based and automatic component configuration. Even so, there's still a lot of near-boilerplate code required to develop Spring applications.

Enter Spring Boot. Spring Boot's primary purpose is to make Spring easier to work with. It achieves this in three ways:

• Automatic configuration : Considering what's on the runtime classpath as well as other factors, Spring Boot can automatically configure components in a Spring application context.
• Simplified dependency management : Taking advantage of transitive dependency resolution at build-time, Spring Boot offers several “starter” dependencies, focused on specific characteristics of an application, that transitively bring in libraries to enable development of those characteristics.
• Runtime insight : Spring Boot offers insight into the inner workings of a running application via REST endpoints and/or JMX MBeans to better understand what makes a running application tick.

All together, Spring Boot lets you focus on fulfilling your application's requirements without worrying about writing code that satisfies the needs of a framework.

In this session, you'll learn how to take your Spring Boot skills to the next level, applying the latest features of Spring Boot. Topics may include Spring Boot DevTools, configuration properties and profiles, customizing the Actuator, and crafting your own starters and auto-configuration.

TBD

In this session, you'll learn how to use Spring Data to rapidly develop repositories for a variety of database types, including relational (JPA and JDBC), document (Mongo), graph (Neo4j), and others (Redis, Cassandra, CouchBase, etc).

For decades, relational databases and SQL have enjoyed their position as the leading choice for data persistence. Even though many alternative database types have emerged in recent years, the relational database is still a top choice for a general purposes data store and will not likely be usurped from its position any time soon. When it comes to working with relational data, Java developers have several options.

But relational databases are not a one-size-fits-all solution. Thankfully, there are many options for data persistence, including relational, document, graph, key-value, and column-store databases, each presenting their unique way of handling data suitable for different problems.

Spring Data makes it easy to work with various databases by offering a programming model that is consistent, regardless of which type of database you're working with. And regardless of the database you're dealing with, you will find that Spring Data eliminates a lot of boilerplate code.

In this session, you'll see how to take Spring Data's automatic repository generation to a whole new level. We'll look at ways to model data and manipulate Spring Data to produce repositories and APIs that are more than just CRUD layers on top of a database.

TBD

In this sessions we'll see how to use components of Spring Cloud to configure and discover microservices in a cloud native microservice-architected application. Specifically, we'll look at Spring Cloud Netflix and Netflix' Eureka and Ribbon projects for service discovery as well as the Spring Cloud Config project's configuration server to provide a central point of external configuration.

Microservice-architecture presents many benefits, not the least of which include opportunities to develop, evolve, scale, test, and deploy individual modules of an application independently from the rest of the application. But once an application is broken apart, a new set of challenges arises.

If the individual microservices are to work together in service of the greater application, then they must know about each other. Rather than hardcode the specifics of each microservice within every other microservice, it's better to provide a registry with which a service can register and other services may use to lookup those service details.

Microservices, like any application, will also likely depend on application-level configuration. It's generally a good idea to keep that configuration separate from the application itself, and this is even more true with microservices. Using a centralized configuration service, microservices can obtain their configuration details, some of which may be shared across many microservices. Because it is separate from the application/microservice code, that configuration itself can be versioned and evolve at a pace independent of the microservices it serves.

Starting with JDK 5, we have had Futures, and they mostly went ignored. Now with concurrency and reactive technology in demand, it is essential that we understand what futures are, and how to handle them and make use of their power in asynchronous systems.

This presentation is a basic ground up introduction to Futures. We start with Futures and how they came packaged with JDK 5. We take a look at Executors, how to create a thread pool, which pool you should choose. How to model Futures in the JDK and show the difference for awaiting the answer and taking on the answer asynchronously. We also take a look at what a Promise is and when to use one. We then invest time taking a look at Guava's callback solution. Then we finally look at the handling of futures in both Scala and Clojure.

Reactive is a the latest buzzword to consume our industry. This presentation distills and defines reactive systems, describe the difference between reactive architecture vs. reactive programming, describe common patterns, and demos the popular reactive JVM technologies like RXJava, and Akka.

Introduction to reactive gets in deep on a discussion of patterns: Source, Sink, Back Pressure, Reactive Pull/Push including a Light introduction to actors using Akka, ReactiveX using RXJava and Reactive Streams in RXJava and Akka. We also will showcase the differences between ReactiveX and Akka.

ReactiveX is a set of Reactive Extensions developed by Netflix, and is developed for various programming languages, like Java, Scala, and Clojure. ReactiveX overhauls the observable design pattern to achieve reactive goals. This presentation will solely focus on the Java version of ReactiveX, RXJava.

RXJava is combining the Observer Pattern with Functional Programming to compose complex asynchronous reactive systems. This presentation will also give an overview on RXJava concepts like Source, Sink, BackPressure and Reactive Pull and Push.

Our jobs usually deal with something other than new code. It is usually old spaghetti and difficult-to-read code. How do we test such code? How do we get through it? How can we surgically remove and make some of this harmful code testable?

This session looks at lousy code, and we talk about some strategies we can do to diagnose, test, apply, and finally refactor to produce something that would promote some sanity in your development process. We can do much with our code to make it better and testable while avoiding extensive mocking. The content of this course is all in Java and JUnit.

Workshop Requirements

• JDK 11+
• Maven 3.8.x
• IDE (I will be using IntelliJ)

Angular 2 is a total rewrite when compared to Angular 1.x. If you are new to Angular 2 and interested in learning to develop applications using ES6 (JavaScript), then this presentation is for you.

We will take an example oriented approach to create a fully functional front end that fetches data from the backend, displays it, allows users to edit the data, and sends back to the backend. Along the way we will learn about the different parts that make up Angular 2 applications.

JavaScript is one of the most powerful and yet perilous languages. It is arguably the most ubiquitous language, the king of the client side programming the web. The dynamic nature of the language offers many benefits, but the weak typing and lack of tooling can make changes unpredictable, that is, if we're not careful. Automated testing can greatly alleviate the pains and lead to more fruitful development.

In this presentation we will take look at the tools, but also the approach to automate the tests for JavaScript code. We will start with simple cases at first, but quickly dive into dealing with dependencies, and measuring code coverage.

Distributed and parallel computing have been around for a while. The problem is not new, but solutions have generally been complex. Over the years several solutions have come along to ease the pain. Spark is a wonderful programming API and a tool that can ease the pain of creating distributed, high concurrent, performing code.

In this presentation we will take an example oriented approach to creating applications that make use of Spark. We will learn how to create the code to use Spark, how to configure and manage the number of threads, and how to distribute the computations.

Reactive Programming is at the top of new excitements in our field. There is a lot of discussion and theory around this concept, but what does it feel to create applications using these ideas? That's the focus on this talk, and we'll use Vert.x as a vehicle.

Learn about reactive programming, how to create applications, and how Vert.x can make that an enjoyable task.

Understand Java from a functional programming point of view. This part covers the basics of lambdas and streams, emphasizing functional programming by transforming collections using the stream approach.

Also includes method references and static and default methods in interfaces.

Functional features in Java, including parallel streams, the java.util.function package, the Optional data type, and reduction operations.

The talk also covers the new date and time package based on Joda time, as well as collectors and implementing the Collector interface.

Java SE 8 introduces many new features that can simplify your code. Using streams, lambdas, and the new Optional type all change the way we write Java. In this presentation, we'll work through a series of examples that show how to rewrite existing code from Java 7 or earlier using the new Java 8 approach.

Examples will include replacing anonymous inner classes with lambdas, switching from iterating over collections into transforming streams, using immutables wherever possible, lazy evaluation, and more.

This talk will focus on interesting features of Java 8 that go beyond the basics. Topics will include:

• the map, filter, and flatMap methods
• simple reductions
• extracting and combining streams
• using Optional as intended
• grouping and partitioning
• downstream collectors
• the java.time package
• generics in detail

Sample code will be provided to illustrate all the techniques, along with tests and a build file.

Everyone worries about performance but few of us have the time to truly understand it. Fortunately, our modern JVMs and CPUs are capable of some amazing performance tricks, but those same tricks only make reasoning about performance that much harder.

In this talk, we'll take a look at some surprising and often unintuitive performance problems and solutions. Not simply with the goal of memorizing solutions but also to better understand the complexity that lies inside both JVMs and CPUs.

Everyone worries about performance but few of us have the time to truly understand it. Fortunately, our modern JVMs and CPUs are capable of some amazing performance tricks, but those same tricks only make reasoning about performance that much harder.

In this talk, we'll take a look at some surprising and often unintuitive performance problems and solutions. But not simply with the goal of memorizing solutions, but to better understand the complexity that lies inside both JVMs and CPUs.

Today, we all benefit from the sophistication of modern compilers and hardware, but that extra complexity can also make it difficult to reason about performance.

In this talk, we'll examine some surprising performance cases and learn how to
use profiling and benchmarking tools to better understand our modern execution environments.

Unlike earlier languages, Java had a well-defined threading and memory model from the beginning. And over the years, Java gained new packages to help solve concurrency problems.

Despite this, Java concurrency is sometimes subtle and fraught with peril.

In this talk, you'll learn these subtleties. And finally, you'll learn how to handle concurrency by exploring the concepts behind java.util.concurrent and other concurrency libraries.

We all have an innate sense of what's possible. Not only is this how magicians fool you, but it might also be what's holding you back.

In this session Michael Carducci shares how he applied lessons learned in his career as a professional magician to his “day-job” as a software engineer.

Magicians have a simple process for creating new material; think of the most impossible thing you can imagine, the engineer a way to make it possible. Michael has been engineering solutions to “impossible” problems for nearly 20 years and this has given him a unique perspective on dealing with challenges in all aspects of his life.

This talk combines illusion, anecdotes and real-world examples to help identify and overcome your mental obstacles.

Hypothesis and data driven development ties together current thinking about requirements, Continuous Delivery, DevOps, modern architecture, and engineering techniques to help rethink building software.

Agile development claims to abhor “Big Design Up Front”…yet what is that giant backlog building session but BDUF in other clothing? Back in the olden days of software development, we were forced to speculate on what users want, then build it. We were basically running a buffet. But what if we could switch to à la carte? With modern engineering practices like Continuous Delivery, we can shift our perspective and start building by hypothesis rather than speculation. This talk shows the full spectrum of software development, from ideation through execution and deployment, through the lens of modern software engineering practices. I discuss building a platform using feature toggles, canary releases, A/B testing, and other modern DevOps tools to allow you to run experiments to see what your users really want. By building a platform for experimentation, product development shifts from up-front guessing to market driven. This talk unifies the practices of modern architecture, DevOps, and Continuous Delivery to provide a new approach to feature development. This talk also demonstrates how to undertake major architectural restructuring with zero regression failures by relying on data and the scientific method.

This session covers two critical soft skills for architects:

• creating clear, concise documentation of software architecture, both structure and decisions
• presenting architectural ideas as clearly as possible

New architects find soft skills like creating lucid documentation and building compelling presentations challenging. This presentation covers a variety of ways to document ideas in software architecture, ranging from diagramming techniques (that aren't UML) to Architecture Decisions Records and ultimately to presentations. The second part of the talk leverages patterns and anti-patterns from the Presentation Patterns book to help architects build clear and concise representations of their ideas.

Stories and lessons from architecture, design, process, and other sources, each illustrating important principles and pitfalls for modern architects.

Those who cannot remember the past are condemned to repeat it.  –George Santayana

The past is never dead. It's not even past. –William Faulkner

Most developers pursue the Latest and Greatest with intense fervor, yet the history of engineering, including software projects, contains rich lessons that we risk repeating ad nauseam. This session recounts a variety of stories of projects that failed architecturally…and why. Ranging from the Vasa in 1628 to Knight Capital in 2012, each story tells of a mistaken interpretation of some architectural fundamental principle and the consequences–some good, some less so. I I also look at the common threads for these stories, which resonates with problems many companies have but don't realize.

• Pets. Com
• San Francisco project
• The Vasa
• F16
• Sagrada Familia
• Tacoma Narrows Bridge
• null
• Ada
• Serialization
• Knight Capital
• Ariane 5
• Webvan
• Chandler project

This session compares Service-oriented, Service-based, and Micro-service architectures, describing the problem each is designed to solve, differences and similarities, variants and hybrids, and engineering practices.

Microservice architectures are quite popular, described as “SOA done correctly”. But what are the real differences between SOA, Microservice, and service-based architectures? What about middle ground between the shared everything of SOA versus shared nothing of microservices? This talk explores the similarities and differences between various service-oriented architectural styles. I describe the characteristics of SOA, microservices, and hybrid service-based architectures, along with the considerations and constraints for each. I also discuss specific engineering practices, orchestration styles, reuse strategies, and migrating from monolithic applications to service-based or microservice architectures. No one architecture can solve every problem, and many projects take on more complexity than necessary by choosing the wrong paradigm.

The technology space is a lot like the ocean - miss one wave and another will come along shortly; most shiny new things begin with a sizable amount of hype as everyone rushes to play with the new toy. This cycle is often met with a level of disappointment as we quickly discover our new bauble isn't all that and a bag of chips so we rush off to the next best thing ever.

A few short years ago, HTML5 was the new hotness but at the time browser support was spotty at best. Despite the spotlight moving on to something else, browser support has improved markedly and we even have new toys to play with! In this talk, I will walk you through what is possible in today's browser as well as what other new features you might not be aware of. HTML5 may no longer qualify as bleeding edge, but it is still deserving of our attention.

JavaScript UI frameworks continue to evolve but centers of gravity have clearly formed around Angular and React. With both libraries boasting of big company backing and passionate communities, which one is right for your next project? While we cannot crown the one true framework, we will dive into the differences and the similarities with an aim to help you make an informed decision on your next web project.

Picking a framework is often fraught with clashing opinions, in this talk I'll try to help you make a good choice for your team.

For the last several years, the JavaScript world has been awash in various Model-View-Whatever frameworks and libraries with new implementations popping up like bunnies. With the popular React library, Facebook took a different approach to developing JavaScript user interfaces by focusing on the View in MV*. This talk will get you up and running on React, a library that gives us a declarative approach to designing highly performant interactive user interfaces. We'll dive into the basics of components, JSX, the virtual DOM and more. By the end of this session you'll have a solid foundation in what React brings to the table and how it might help you on your next project.

For the last several years, the JavaScript world has been awash in various Model-View-Whatever frameworks and libraries with new implementations popping up like bunnies. With the popular React library, Facebook took a different approach to developing JavaScript user interfaces by focusing on the View in MV*. This talk will get you up and running on React, a library that gives us a declarative approach to designing highly performant interactive user interfaces. We'll dive into the basics of components, JSX, the virtual DOM and more. By the end of this session you'll have a solid foundation in what React brings to the table and how it might help you on your next project.

Today you can't swing a dry erase marker without hitting someone talking about “the cloud”. From the CIO to the project room, the cloud is bound to be a topic of conversation. While there is no denying the buzz worthiness of the term, you probably should take a deep breathe before declaring your entire portfolio will be cloud native by the end of the year. In this talk, I will discuss a practical way of assessing your applications and how to create a thoughtful plan to move applications to the cloud - when it makes sense.

We'll talk about what factors to consider when surveying an application, why some systems shouldn't go to the cloud and what else you need to consider beyond the basics of picking a cloud vendor. Cloud based deployments have tremendous benefits to today's organizations - but as with any new technology, it must be introduced with care.

Machine Learning is a huge, deep field. Come get a head start on how you can learn about how machines learn.

This talk will be an overview of the Machine Learning field. We’ll cover the various tools and techniques that are available to you to solve complex, data-driven problems. We’ll walk through the algorithms and apply them to some real but accessible problems so you can see them at work.

Documents contain a lot of information. We'll introduce you to a variety of techniques to extract them.

Machine Learning techniques are useful for analyzing numeric data, but they can also be useful for classifying text, extracting content and more. We will discuss a variety of open source tools for extracting the content, identifying elements and structure and analyzing the text can be used in distributed, microservice-friendly ways.

This open source machine learning framework from Google has taken off. Come learn what you can do with it in your own organization.

TensorFlow is a powerful data flow-oriented machine learning framework developed by Google's Brain Team. It was designed to be easy to use and widely applicable on both numeric, neural network-oriented problems as well as other domains. We'll cover the over view as well as apply it to several fun, realistic problems.

What happens if web applications got really fast?

We are increasingly able to do more in the browser because of faster networks, optimized JavaScript engines, new standard APIs and more. There is a new initiative to allow a binary format called WebAssembly that will provide a compiled, cross-platform representation that will take us to the next level. Complex business applications and 3D video games will alike will benefit from this new standard. Come hear about what it can do for you.

We all have seen our share of bad code and some really good code as well. What are some of the common anti patterns that seem to be recurring over and over in code that sucks? By learning about these code smells and avoiding them, we can greatly help make our code better.

Come to this talk to learn about some common code smell and to share your experiences as well.

Cloud continues to grow in importance in even the most conservative companies’ IT strategies. Because of this, even experienced software architects must confront a new world in which many of our normal architectural assumptions no longer hold. Before we create architectures that leverage cloud infrastructure, we need to rebuild our mental model of infrastructure around the appropriate concepts and principles. The purpose of this session is to do just that.

In this session we’ll:

• tour the current cloud infrastructure landscape
• explore the key business and technology motivators for adopting cloud
• explore the unique aspects of cloud infrastructure that violate our traditional assumptions
• examine the risks associated with adopting cloud infrastructure
• navigate some of the key tradeoffs involved with cloud architecture choices
• overlay traditional architecture patterns and examine their suitability to cloud
• define a cloud native architecture that is optimized to exploit the uniqueness of the cloud environment

The learner should leave this session prepared for deeper dives into cloud native architecture patterns and migration strategies.

NOTE: We'll cover roughly 50% of the material in Part 1.

Cloud continues to grow in importance in even the most conservative companies’ IT strategies. Because of this, even experienced software architects must confront a new world in which many of our normal architectural assumptions no longer hold. Before we create architectures that leverage cloud infrastructure, we need to rebuild our mental model of infrastructure around the appropriate concepts and principles. The purpose of this session is to do just that.

In this session we’ll:

• tour the current cloud infrastructure landscape
• explore the key business and technology motivators for adopting cloud
• explore the unique aspects of cloud infrastructure that violate our traditional assumptions
• examine the risks associated with adopting cloud infrastructure
• navigate some of the key tradeoffs involved with cloud architecture choices
• overlay traditional architecture patterns and examine their suitability to cloud
• define a cloud native architecture that is optimized to exploit the uniqueness of the cloud environment

The learner should leave this session prepared for deeper dives into cloud native architecture patterns and migration strategies.

NOTE: We'll cover roughly 50% of the material in Part 1. If you come to only Part 2, we'll be starting in the middle.