Tim Berglund

Decision Making in Software Teams

1:30 PM MDT

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 decisionmaking 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.

Stream Processing Your Way with Apache Flink?

5:00 PM MDT

Apache Flink has become the standard piece of stream processing infrastructure for applications with difficulttosatisfy demands for scalability, high performance, and fault tolerance, all while managing large amounts of application state.

The key to demystifying Apache Flink is to understand how the combination of stream processing plus application state has influenced its design and APIs. A framework that cares only about batch processing, or one that performed only stateless stream processing, would be much simpler.

We'll explore how Flink's managed state is organized, and how this relates to the programming model exposed by its APIs. We'll look at checkpointing: how it works, the correctness guarantees that Flink offers, how state snapshots are organized on disk, and what happens during recovery and rescaling.

We'll also look at watermarking, which is a major source of complexity and confusion for new Flink developers. Watermarking epitomizes the requirement Flink has to manage application state in a way that doesn't explode as those applications run continuously on unbounded streams.

You'll leave with a good mental model of Apache Flink, ready to use it in your own stateful stream processing applications.