Personal Reading List: 2Q2021
My personal reading list for April, May, and June 2021.
Color Key: Special Notes, Completed Reading. Updated throughout the Quarter.
At Bat (Schnell)
The First 90 Days: Proven Strategies for Getting Up to Speed Faster and Smarter, by Michael D. Watkins, Harvard Business Review Press, 2013. Copy provided by Deloitte.
The Kubernetes Workshop: Learn How to Build and Run Highly Scalable Workloads on Kubernetes, by Zachary Arnold, Sahil Dua, Wei Huang, Faisal Masood, Melony Qin, and Mohammed Abu Taleb, Packt Publishing, 2020.
Production Kubernetes: Building Successful Application Platforms, by Josh Rosso, Rich Lander, Alex Brand, and John Harris, O'Reilly, 2021.
At Bat (Langsam)
Fluent Python: Clear, Concise, and Effective Programming, by Luciano Ramalho, O'Reilly, 2015.
The Model Thinker: What You Need to Know to Make Data Work for You, by Scott E. Page, Basic Books, 2018.
Practical Statistics for Data Scientists: 50 Essential Concepts, by Peter Bruce and Andrew Bruce, O'Reilly, 2017. Copy provided by MarkLogic.
On Deck
Kubernetes in Production Best Practices: Build and Manage Highly-Available Production-Ready Kubernetes Clusters, by Aly Saleh and Murat Karslioglu, Packt Publishing, 2021.
Python Programming for Beginners: A Kid's Guide to Coding Fundamentals, by Patricia Foster, Rockridge Press, 2020. Copy provided by Amazon.
In the Hole
Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith, by Sam Newman, O'Reilly, 2020. Copy provided by Nginx.
Presto: The Definitive Guide, by Matt Fuller, Manfred Moser, and Martin Traverso, O'Reilly, 2020. Copy provided by Starburst.