Tim Berglund

Presentations

Then Our Buildings Shape Us

Winston Churchill famously said, "First we shape our buildings, and afterwards, our buildings shape us." He was talking about the reconstruction of the House of Parliament, which was damaged in a bombing raid in World War II. There was a debate about how to shape the chamber to best accommodate the deliberative activity of the body that met in it. Churchill was talking about buildings, but it turns out his insight is a very general one indeed.

Developers are constantly debating their choices of language, platform, editor, methodology, and even where to put the curly braces. The robust internal dialog in community is a healthy thing, but our debates are often focused on the wrong topics. Have you ever compared languages by performance benchmarks? Platforms by alleged claims of developer productivity? Methodologies by feature velocity? There is a very good chance you're doing it wrong.

Rather than focus on the material content of our debates—language performance, editor productivity, methodological velocity—we should take Churchill's advice and think about the form of our choices. How will our choice of language influence the way we solve future problems? What assumptions does our methodology make about the nature of work? How will our choice of database affect the kinds of problems we think of as solvable?

Drawing on lessons from building architecture, literature, music, the visual arts, and even software itself, we'll learn the priority of interpreting the form of things before attempting to understand their content. You may never look at software architecture the same way again.

NoSQL Smackdown 2012

Alternative databases continue to establish their role in the technology stack of the future—and for many, the technology stack of the present. Making mature engineering decisions about when to adopt new products is not easy, and requires that we learn about them both from an abstract perspective and from a very concrete one as well. If you are going to recommend a NoSQL database for a new project, you're going to have to look at code.

In this talk, we'll examine three important contenders in the NoSQL space: Cassandra, MongoDB, and Neo4J. We'll review their data models, scaling paradigms, and query idioms. Most importantly, we'll work through the exercise of modeling a real-world problem with each database, and look at the code and queries we'd use to implement real product features. Come to this session for a thorough and thoroughly practical smackdown between three important NoSQL products.

Connected Data with Neo4j

Neo4j is an open-source, enterprise-class database with a conventional feature set and a very unconventional data model. Like the databases we're already used to, it offers support for Java, ACID transactions, and a feature-rich query language. But before you get too comfortable, you have to wrap your mind around its most important feature: Neo4j is a graph database, built precisely to store graphs efficiently and traverse them more performantly than relational, document, or key/value databases ever could.

Neo4j is an obvious fit to anyone who thinks they have a graph problem to solve, but this is not many people. It turns out that the most interesting property of Neo4j is its architectural agenda. It wants you to think of the entire world as a graph—as a set of connected information resources. Steeped in the thinking of resource oriented architecture, this NoSQL database wants to change the way you look at your world, and unlock new value in your data as a result.

Neo4J Workshop

TBA

TBA

Gradle Workshop (Bring a Laptop)

Gradle. Another build tool? Come on! But before you say that, take a look at the one you are already using.

Whether your current tool is Make, Rake, Ant, or Maven, Gradle has a lot to offer. It leverages a strong object model like Maven, but a mutable, not predetermined one. Gradle relies on a directed acyclic graph (DAG) lifecycle like Maven, but one that can be customized. Gradle offers imperative build scripting when you need it (like Ant), but declarative build approaches by default (like Maven). In short, Gradle believes that conventions are great -- as long as they are headed in the same direction you need to go. When you need to customize something in your build, your build tool should facilitate that with a smile, not a slap in the face. And customizations should be in a low-ceremony language like Groovy. Is all this too much to ask?

Gradle has received the attention of major open source efforts and has chalked up significant conversions by the Spring Integration, Hibernate, and Grails projects. What do these technology leaders see in this bold new build tool? They see not only a better way to build Java applications, but an extensive ecosystem of connecting to existing Ant and Maven build files while expanding the horizon of test, CI, and deployment automation in an easy manner. Join us for 90 minutes and let us take you on this same walk of discovery of the most innovative build tool you've ever seen.

Hadoop

When you want to measure fractions of a millimeter, you get a micrometer. When you want to measure centimeters, you get a ruler. When you want to measure kilometers, you might use a laser beam. The abstract task is the same in all cases, but the tools differ significantly based on the size of the measurement.

Likewise, there are some computations that can be done quickly on data structures that fit into memory. Some can't fit into memory, but will fit on the direct-attached disk of a single computer. But when you've got many terabytes or even petabytes of data, you need tooling adapted to the scale of the task. Enter Hadoop.

Hadoop is a widely-used open source framework for storing massive data sets in distributed clusters of computers and efficiently distributing computational tasks around the cluster. Come learn about the Hadoop File System (HDFS), the MapReduce pattern and its implementation, and the broad ecosystem of tools, products, and companies that have grown up around this ground-breaking project.

ClojureScript

Clojure has recently been gaining attention as one of the most innovative languages of the JVM in current use, and it has mostly found a home on the server. In parallel, JavaScript has ascended to the position of the most important language of the web, and until recently it has lived only on the client. Few observers looked at the world of web development and predicted that these two would get together. Happily for us, they have!

ClojureScript is a dialect of Clojure that compiles to JavaScript, and targets the JavaScript runtimes of the web as a deployment environment. It offers the unparalleled expressiveness of Lisp, the performance and space efficiency of the Google Closure Compiler, interoperability with the in-browser object model, natural integration with server-side Clojure applications, and an insanely productive in-browser REPL. In a time of proliferating JavaScript extensions and client-side development frameworks, you owe it to yourself to take a look at this compelling vision of how client-side web development should be done.

Decision Making in Software Teams

Alistair Cockburn has described software development as a game in which we choose among three moves: invent, decide, and communicate. Most of our time at No Fluff is spent learning how to be better at inventing. Beyond that, we understand the importance of good communication, and take steps to improve in that capacity. Rarely, however, do we acknowledge the role of decision making in the life of software teams, what can cause it to go wrong, and how to improve it.

In this talk, we will explore decision making pathologies and their remedies in individual, team, and organizational dimensions. We'll consider how our own cognitive limitations can lead us to to make bad decisions as individuals, and what we might do to compensate for those personal weaknesses. We'll learn how a team can fall into decision-making dysfunction, and what techniques a leader might employ to healthy functioning to an afflicted group. We'll also look at how organizational structure and culture can discourage quality decision making, and what leaders to swim against the tide.

Software teams spend a great deal of time making decisions that place enormous amounts of capital on the line. Team members and leaders owe it to themselves to learn how to make them well.