This talk will begin by briefly examining what it means for infrastructure to be represented as code. We’ll examine some fundamental software components required for automating infrastructure using code such as GPG, package managers, SSL, and more. We’ll examine some interesting failure cases for these tools and how these shortcomings might make it impossible to truly represent infrastructure as code, for now.
Doc walks us through the Hawthorne Effect and Goodhart’s Law to explain why setting goals for velocity can actually hurt a project’s chances. Take a look at what can negatively impact velocity, ways to stabilize fluctuating velocity, and methods to improve velocity without the risks. Leave with a toolkit of additional metrics that, coupled with velocity, give a better view of the project’s overall health.
Rust is a systems programming language from Mozilla that focuses on safety, speed, and concurrency. Rust reached 1.0 a year ago, and so there’s a question everyone is asking: how has 1.0 tested in production? Is the language “ready” yet? In this talk, Steve will give an overview of Rust’s value proposition, focusing on examples and anecdotes from companies using Rust in production today.
When Apple open sourced Swift late last year, they invited the community into the discussion of where Swift should go and why. Instead of us having to imagine what the Swift language and library stewards and architects are thinking, we can read their words on the Swift evolution mailing list. In this talk we’ll look at what idiomatic Swift will look like soon when Swift 3 is soon released and talk about the reasoning behind some of the choices.
Kafka Streams represents a new design point in the stream processing space. Where most frameworks provide a service for running stream processing applications, Kafka Streams emphasizes low-overhead development that feels more like developing any other application.
Elm is a purely functional language for the browser. It compiles to JavaScript — after enforcing immutability, types, semantic versioning, and tight boundaries for user and server interactions. This session gives an overview of Elm, then focuses on the Elm Architecture: how it overturns what is essential in object-oriented and even backend functional programming.
Good engineers write good code, but the best engineers raise the skills of their junior colleagues, too. If you’re a senior engineer, you must learn to mentor new hires. Especially if you’re committed to diversity: mentorship is critical to the careers of women and minorities in tech. I have failed at mentoring, then succeeded. I distinguished five warning signs that a mentorship will fail, and five prerequisites that make a mentorship very likely to succeed. Learn from me, and march to mentorship triumph.
Spark is becoming a data processing giant, but it leaves much as an exercise for the user. Developers need to write specialized logic to move between batch and streaming modes, manually deal with late or out-of-order data, and explicitly wire complex flows together. This talk looks at how we tackled these problems over a multi-petabyte dataset at Cerner.
In today’s world of exploding big and fast data, developers who want both streaming analytics and ad hoc, OLAP-like analysis have often had to develop complex architectures such as Lambda—a path for fast streaming analytics using NoSQL stores such as Cassandra and HBase with a separate batch path involving HDFS and Parquet. While this approach works, it involves too many moving parts, too many technologies for ops, and too many engineering hours. Helena Edelson and Evan Chan highlight a much simpler approach to combine streaming and ad hoc/batch analysis using what they call the NoLambda stack (Apache Spark/Scala, Mesos, Akka, Cassandra, Kafka), plus FiloDB, a new entrant to the distributed-database world that combines streaming and ad hoc analytics.
Agile HR represents a new, emerging way for HR to partner with their leaders and people. The paradigm is shifting from one of controls and standards to a new level of engagement – one that focuses on the facilitation and improvement of organizational agility. This means helping to build and drive programs that create adaptability, foster innovation, provide transparency, and inspire collaboration. Building on these principles, Comcast’s Technology + Product team is reimagining Performance Management. We are an innovative and agile organization and we are transforming our Performance Management approach to reflect our culture, provide real-time feedback, and develop our most important resources – our talent.
