Books mentioned at devopsdays Oslo 2017

There was a lot of books mentioned during the talks at Devopsdays Oslo 2017. I compiled a list of all the books mentioned. If you want to see the talks, you can find links to the recordings on the Devopsdays website (the books are listed by the speaker)

Mike Long

• The Structure of Scientific Revolutions by Thomas S. Kuhn
• The Phoenix Project By Gene kim

Stein Inge Morisbak

• Driving Technical Change by Terrence Ryan

Trond Arve Wasskog

• Test Driven Development: By Example by Kent Beck
• Continuous Integration: Improving Software Quality and Reducing Risk by Paul M. Duvall
• Release It!: Design and Deploy Production-Ready Software by Michael T. Nygard
• Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation by Jez Humble
• The Phoenix Project
• Lean Enterprise: How High Performance Organizations Innovate at Scale by Jez Humble,Joanne Molesky and Barry O’Reilly
• Site Reliability Engineering: How Google Runs Production Systems by Niall Richard Murphy, Betsy Beyer, Chris Jones and Jennifer Petoff

Mark Burgess

• In Search of Certainty: The Science of Our Information Infrastructure by Mark Burgess

At Devopsdays Oslo 2017, there was a discussion about machine learning at one of the one of the openspace sessions. I made some notes from the session, and put it into a gist that I shared on twitter. This is essentially that gist, so not much editing here.

machine learning resources, from Devopsdays Oslo open spaces session

Thanks to @HannahFoxwell for the following links:

• A book: Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies
• A free course at Udacity
• Machine learning toolkit in python
• A free ebook for programmers
• https://hortonworks.com/products/data-platforms/hdp/
• More free lessons on ML

some more resources

Using tensorflow with WebRTC: https://webrtchacks.com/webrtc-cv-tensorflow/

Two interesting podcasts episodes about the ethics of AI:

• You are not so smart
• TED radio hour

(By the way, I recommend both those podcasts)

Who will be the first to loose their jobs to robots? Dilbert

Kubernetes, jupyter notebooks + tensorflow: Kubeflow