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.

Microservice architecture is a modern architectural approach that focuses on breaking apart the monolith and building modular services. But the framework we use has a tremendous impact on how we build and deploy services. A new type of framework has emerged that provides a lightweight stack for building microservices.

In this session, we will explore some modern Java micro frameworks for building microservices. Example frameworks you may see include Dropwizard, Spark, Ninja, RestExpress, Play, Restlet, and RestX.

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.

I.flow() AI is an emotional intelligence AI that learns to respond in real-time to the pain of humans, for example, developers that are having a hard time. The I.flow() AI Platform is still in the early stages of mapping theory to concrete implementation, so in this talk we'll breakdown architecture strategy, pain metrics, pair programming buddy, supply chain flows, and the underpinning of Flow theory.

Flow is an old concept, adopted into the software world by mapping Flow from Lean manufacturing. When we map a metaphor between two different domains, our brain locks onto the isomorphisms between contexts, and “Flow” becomes stickies flowing on a whiteboard, or features flowing out to customers. It becomes difficult to see Flow any other way.

What if our object-oriented blinders led to an object-oriented notion of Flow, and there's a totally different way to look at the system? Flow, at it's core, is a paradigm shift, a metaphorical lens, that helps us see, understand, and predict the behavior of any Flow System. Better predictive models, enables AI automation like we've never had before. It's about time we started applying AI to our own problems.

This is my story of lessons learned on how to stop the crushing effects of business pressure… I was team lead with full control of our green-field project. After a year, we had continuous delivery, a beautiful clean code base, and worked directly with our customers to design the features. Then our company split in two, we were moved under different management, and I watched my project get crushed.

As a consultant, I saw the same pattern of relentless business pressure everywhere, driving one project after another into the ground. I made it my mission to help the development teams solve this problem. This is my story of lessons learned on how to transform an organization from the bottom up. I'll show you how to lead the way.

The crushing business pressure is caused by a broken feedback loop that's baked into the organization's design. In this presentation, I'll show you how to fix the broken feedback loop. Learn how to:

• Gather evidence of developer productivity loss
• Identify the key organizational changes required for success
• Make the case to management for improvement
• Partner with your manager for long-term success

If the system is broken, we need to fix the system. You can change the system by making the decision to lead.

In this session, we'll use I.flow() AI as a metaphorical lens to explore the world of philosophy.
Each one of us is on a journey to discover who we are, why we're here, and what it all means. I.flow() Emotional Intelligence AI evolved as a result of deep self-reflection, in the search for an authentic self, and the courage to live an authentic life.

“I.choose() therefore I.am()”

This session is a collection of life reflections and lessons learned, codified into diagrams and code abstractions using I.flow() AI. We'll start with the assumption that life is a video game, and humans are the AI. We'll break down models for human relationships, different ways of being in the world, and discuss the meaning of the game of life.

If you are someone that delights in a great philosophical discussion over dinner, you won't want to miss this talk.

This is my story of lessons learned on why improvement efforts fail… I had a great team. We were disciplined about best practices and spent tons of time on improvements. Then I watched my team slam into a brick wall. We brought down production three times in a row, then couldn’t ship again for a year.

Despite our best efforts with CI, unit testing, design reviews, and code reviews, we lost our ability to understand the system. We thought our problems were caused by technical debt building up in the code base, but we were wrong. We failed to improve, because we didn’t solve the right problems. Eventually, we turned our project around, but with a lot of tough lessons along the way.

In this talk, we'll go through a deep-dive case study that starts with project failure, then revisit all the mistakes we made over a 3 year journey to turn the project around. We'll discuss bad assumptions, strategies that failed, ideas that changed, techniques and tools that changed, and how we eventually learned our way to victory.

After reviewing each mistake, we'll have a group discussion about the underlying reasons, so you can avoid these mistakes on your own project.

Since the dawn of software development, we've struggled with a huge disconnect between the management world and the engineering world – the clash of top-down control, money, and economics, versus art, freedom, working with our friends, and bringing awesome creations to life.

Overcoming these challenges in our industry requires a huge paradigm shift – rather than building organizations as money-making machines with top-down control, our organizations need to become thinking, feeling, interconnected social organisms, where our humanity isn't boiled down to a few numbers.

How do we shift the paradigm of the organization, to bridge these two worlds together? The short answer – with the help of software.

By measuring the friction in a developer's Flow, we have a data-driven feedback loop for personal improvement. What if we measure Flow across the team? Across team dependencies? Across the organization?

What would it take to build an organizational operating system, that uses our past experience and lessons learned as the foundation for an intelligent hive mind, that helps everyone in the organization make better decisions? What if we codified our organizational ideals into the business accounting rules of the software, then sold it as the “the next big thing” in the industry?

At the end of the day, business is a game. If we take responsibility for making up the rules, we can redefine the game we wish to play. In this session, we'll discuss a potential future for our industry, where we design the organizational operating system that runs the world.

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

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.

In this session we will take a look at building applications with Angular. We will build a very simple application from the ground up, and attempt to understand the approach of Angular, as well as understand some of the terminology that Angular introduces.

This session will focus on the Angular 10

TypeScript, Components, Annotations/Directives, Observables, Reactive Stores, Model-Driven forms … Oh my! Angular, much like AngularJs (1.x.x), despite being a powerful platform for building rich client side applications, comes laden with both new terminology, and a “newer” approach to writing client side code.

In this session, as we build a simple application, we will attempt to tease apart these concepts, slowly building our understanding towards how these pieces come together, and how we can leverage them to build rich client side application.

Details

• Quick overview of what Angular has to offer, how it is different from Angular 1.x
• A glance at the project we are going to build, and all the important files that angular-cli generates
• Create our first component
• Proceed with creating a component hierarchy to display all hard coded data

Along the way we will see how to use the Angular style guide to follow conventions adopted by the Angular community at large, and some ways to use the angular-cli tool.

In this session we will take a look at building applications with Angular. We will build a very simple application from the ground up, and attempt to understand the approach of Angular, as well as understand some of the terminology that Angular introduces.

This session will focus on the Angular 10

TypeScript, Components, Annotations/Directives, Observables, Reactive Stores, Model-Driven forms … Oh my! Angular, much like AngularJs (1.x.x), despite being a powerful platform for building rich client side applications, comes laden with both new terminology, and a “newer” approach to writing client side code.

In this session, as we build a simple application, we will attempt to tease apart these concepts, slowly building our understanding towards how these pieces come together, and how we can leverage them to build rich client side application.

Details

• Using in-build pipes in Angular
• Create our own pipe
• Create the necessary infrastructure to allow for HTTP Calls to the backend
• Load all the containers using Ajax
• Introduces routing, and update the homepage to navigate to these routes

Along the way we will see how to use the Angular style guide to follow conventions adopted by the Angular community at large, and some ways to use the angular-cli tool

In today's world, our applications need to be both responsive, fast and scalable. Our applications need to respond to user interactions such as mouse movements, clicks and inputs as well as asynchronous inputs like XHR calls, server sent events, setInterval, even web socket events! Unfortunately as things stand today, there is no consistent way to deal with the myriad of different “changes” that could happen in an application.

But what if there is? This is what Reactive Extensions (specifially RxJs in this session) allow us to do. It offers us an abstraction that allows us to treat everything from DOM events (infinite streams) to our domain (maps, sets and arrays) as streams. This consistent interface now permits us to create and manipulate any source identically. Futhermore, it allows us to react to different sources as if they are one!

Reactive Extensions are fast becoming the de-facto approach of managing asynchronicity in JS land. From Netflix's UI to Angular 2 $http to ES7 - reactive programming is everywhere!

This session is RxJs 101, covering

• A brief introduction to reactive programming
• How reactive programming is analogous to dataflow programming
• The architectural patterns underlying reactive extensions
• How we can create and manipulate “observable” streams within our applications
• Error handling
• Hot and Cold observables
• The reactive landscape, and a couple of gotcha

If we have time we will look at a simple demo, and reactive progamming's role in Angular 2

In this session we will get acquainted with Docker. We will discuss what docker is, how to install it, and how to start using Docker. We will also explore some of the benefits of containerizing your applications.

Containers are taking over the world. Containers provide a means to have hermatic builds of your software, allowing for truly immutable testing, and delivery of your software. Docker is one of many containerization technologies, and in this session we will take a brief look at Docker and what it has to offer.

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.

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.”

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.

Reactive Programming in gaining a lot of excitement. Many libraries, tools, and frameworks are beginning to make use of reactive libraries. Besides, applications dealing with big data or high frequency data can benefit from this programming paradigm. Come to this presentation to learn about what reactive programming is, what kind of problems it solves, how it solves them. We will take an example oriented approach to learning the programming model and the abstraction.

Reactive Programming
Nature of Problems
Programming API
The Reactive Programming Abstraction
Examples

Java 8 is the most significant change to the language since it's introduction, surpassing changes seen in any of the previous versions. It is not merely syntactical change or addition of a few extra features, it's a paradigm shift. Come to this presentation to learn about the power and capabilities of functional programming using Java 8 and how to benefit from those when building Java applications.

Lambda Expressions
A Look under the hood
Stream
Functional Programming Principles Applied
Function Pipeline
Lazy Evaluations
Parallel Streams

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.

JShell, introduced in Java 9, is a great experimentation tool, useful for micro-prototyping, and trying out code snippets. In this presentation we will learn the benefits of the tool, when to use it, and how to put that to real good use during development.

In this example driven presentation we will look at writing snippets, creating functions, defining and redefining variable and methods, creating classes, and configuring the tool to meet your desired level of feedback.

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.

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.

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.

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.

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.

On the NFJS tour, there are questions that seem to come up again and again. One common example is “How do we determine which new tools and technologies we should focus our energy on learning?” another is “How do we stop management from forcing us to cut corners on every release so we can create better and more maintainable code?” which, after awhile becomes “How can we best convince management we need to rewrite the business application?”

There is a single metaanswer to all these questions and many others.

It begins with the understanding that what we as engineers value, and what the business values are often very different (even if the ultimate goals are the same) By being able to understand these different perspectives it's possible to begin to frame our arguments around the needs and the wants of the business. This alone will make any engineer significantly more effective.

This session picks up from where “Stop writing code and start solving problems” stops discussing what is value, how do we align the values of the business with the needs and values of the engineer.

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 this session we will dive deeper into Dockerfiles. We will explore the DSL that Dockerfiles provide to allow for the automation of image creation.

Dockerfiles provide a means to automate the creation of images, and consequently the containers within which our applications run. The Dockerfile, though minimal, provides us with everything we need to package our software, and enable it to run. In this session we will dive deep into the Docker DSL, and explore the many commands that it provides, and along the way explore some differences between similar commands, and some gotchas.

Kafka has captured mindshare in the data records streaming market, and in this presentation, we knock on its door and see what lies behind. What is the draw? What makes it an attractive addition? How does it compare to Message Queues and other message streaming services?

We will do a thorough introduction into what is Kafka. We will also discuss Consumers, Producers, Streams. Integration with ZooKeeper, and discuss the performance aspect of using Kafka.

Life is full of choices and the choices are full of tradeoffs. One such choice is which client side technology to use: React or Angular 2? This presentation will not decide that for you, but it will provide you with enough details so you can make that decision for your applications.

This presentation has three parts. A short introduction to React along with key capabilities and limitations. A short introduction to Angular 2 along with key key capabilities and limitations. Finally, a comparison and a list of things to consider in choosing one over the other.

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.

At some point, graphics cards became serious business computationally. We'll explore why and how this switch has happened.

The most basic introduction to computers spells it out: software runs on the CPU. At some point, this became not entirely true. Graphics cards now support general purpose computing via apis such as CUDA and OpenCL. This talk will introduce you to how and why you can take advantage of these capabilities for a wide variety of applications. Moore's Law may have petered out, but we have plenty of other ways to make our applications run faster.

Java 8 is pretty great, but mix in JavaSlang (now called Vavr) and get ready for some functional programming excitement.

JavaSlang is a project that decorates Java with immutable data structures, better Optionals, tuples, and more. Now with JavaSlang (Vavr) we can really bring in some more power to functional programming and Java. We will even discuss some new concepts like for comprehensions, Try, and Either!

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)

If Java 8 was all about how we code, Java 9 is all about how we will build. Modularization will have the biggest impact of any change that happened in Java since its inception. In this presentation we will learn about the need for modularization, how it impacts development, the rules to follow when creating modules, and the effect it has on legacy code.

We will explore creating module, using modules, readability, exports, automatic modules, and unnamed modules.

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.