A Data Engineer’s view on his favorite Linux and Open Source conference.
The SCaLE Linux conference has been a regular part of my life for the past 9 years, and it holds a special place in my heart. SCaLE isn’t like most tech conferences; it’s the kind of gathering that encourages you to reach out and meet your fellow Open Source enthusiasts, and they mean it. You won’t find speakers holed up in the speaker lounge; instead you’ll find yourself chatting with them in the halls. As an all-volunteer effort, SCaLE is absolutely best-of-breed. I could not have said it better than Dave Stokes, MySQL Community Manager @ Oracle and long-time SCaLE speaker, who shared: “SCaLE is the show other conferences wish they were.”
This was the first year I attended SCaLE with my Data Engineering hat on, and I was not disappointed. With the wealth of talks on containerization, deployment, and programming languages populating the schedule, my 4-day weekend was packed with sessions that left me inspired and eager to learn more. Here are a few of my highlights!
Community Fundamentals — Aim to be an Open Source Zero
Based on Colonel Chris Hadfield’s book “An Astronaut’s Guide to Life on Earth”, Guy Martin gives a compelling talk that summarizes Colonel Hadfield’s philosophy with an eye towards how to become a trusted member of an Open Source community.
Golang: a humble sales pitch to the holdouts
For a thorough introduction to the Go language pitched at seasoned engineers, see Kelly Heller’s talk on the best features added to Go and the best decisions around features intentionally left out. Full disclosure: Kelly is my wife, but don’t hold that against her, this talk was a crowd favorite!
Doing it live: machine learning at scale… and in an instant
Chris Smith, VP of Engineering and Data Science at Ticketmaster, gave a fun talk on the pipeline that performs streaming fraud detection at massive scale for Ticketmaster’s purchasing process. Interestingly, only the last ~10 minutes of the talk were about their ML engine of choice: Vowpal Wabbit, while the majority of the talk covered the considerations surrounding the design of their distributed pipeline from both engineering and business-need perspectives.
Back in Silicon Valley one week later, thinking about what I can do for the next batch of Insight Data Engineering fellows, I’m still energized by all the stellar people I got to hang out with and the great work they shared at SCaLE. In the next few months, I’ll be digging in to large-scale machine learning, and contributing to our in-house deployment and configuration management tools, continuing our constant effort to integrate the best of industry into our program, and push the envelope of what brilliant people can learn to do in 7 weeks.
I hope to see you at SCaLE next year!
Want to get hands-on experience with Amazon AWS and big data tools in Silicon Valley or New York? The Insight Data Engineering Fellows Program is a free 7-week professional training program where you build cutting edge big data platforms and transition to a career in data engineering at top teams like LinkedIn, Facebook, Slack, and Yelp.
