HackerNews Readings
40,000 HackerNews book recommendations identified using NLP and deep learning

Scroll down for comments...

Active Measures: The Secret History of Disinformation and Political Warfare

Thomas Rid, Derek Perkins, et al.

4.5 on Amazon

3 HN comments

The Kubernetes Book: Updated April 2021

Nigel Poulton

4.4 on Amazon

2 HN comments

Machine Learning with R: Expert techniques for predictive modeling, 3rd Edition

Brett Lantz

4.6 on Amazon

2 HN comments

Enchanted: A History of Fantasy Illustration

Jesse Kowalski, Rusty Burke, et al.

4.6 on Amazon

2 HN comments

Head First JavaScript Programming: A Brain-Friendly Guide

Eric Freeman and Elisabeth Robson

4.6 on Amazon

2 HN comments

Python Programming Language

Berajah Jayne

4.6 on Amazon

2 HN comments

The Site Reliability Workbook: Practical Ways to Implement SRE

Betsy Beyer , Niall Richard Murphy , et al.

4.7 on Amazon

2 HN comments

Python Programming: An Introduction to Computer Science, 3rd Ed.

John Zelle

4.6 on Amazon

2 HN comments

Unit Testing Principles, Practices, and Patterns: Effective testing styles, patterns, and reliable automation for unit testing, mocking, and integration testing with examples in C#

Vladimir Khorikov

4.8 on Amazon

2 HN comments

Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python, 2nd Edition

Stefan Jansen

4.5 on Amazon

2 HN comments

Decode and Conquer: Answers to Product Management Interviews

Lewis C. Lin

4.5 on Amazon

2 HN comments

Hands-On Programming with R: Write Your Own Functions and Simulations

Garrett Grolemund and Hadley Wickham

4.5 on Amazon

2 HN comments

The Alignment Problem: Machine Learning and Human Values

Brian Christian and Brilliance Audio

4.6 on Amazon

2 HN comments

Building Mobile Apps at Scale: 39 Engineering Challenges

Gergely Orosz

5 on Amazon

2 HN comments

Learning Web Design: A Beginner's Guide to HTML, CSS, JavaScript, and Web Graphics

Jennifer Robbins

4.6 on Amazon

2 HN comments

Prev Page 11/16 Next
Sorted by relevance

gregdoesitonJune 8, 2021

This is a really cool project. When I worked at Uber, the team built a custom release train called Metro, automating as much as possible, integrating with various internal tools and touchpoints. It worked really well: except if you want this, you need to build it yourself.

When I researched my book Building Mobile Apps at Scale [1], the best advice I could give for large teams and release trains is… maybe build one yourself? Given I didn’t know of any products that would work from medium to large teams.

It’s great to see someone tackling this problem space. You should talk with Uber’s mobile platform for some hard-learned lessons when building Metro.

[1] https://www.mobileatscale.com/

gregdoesitonMay 5, 2021

I'm excited to share that Building Mobile Apps at Scale: 39 Engineering Challenges is out. It's my first-ever paperback book and one that is free as a PDF for the rest of the month[1].

I had worked for years at Uber, first as a mobile engineer, then an engineering manager. Despite being a mobile-first company, I could not shake the feeling that non-mobile engineers and managers consistently underestimated the complexity of large-scale mobile development. I've been in so many meetings where an engineer, a PM, or a director would say, "oh, compared to the backend, the mobile part should be simple enough... it's just another frontend, right?".

I found myself explaining again and again to PMs, engineers, and stakeholders all the hoops the mobile team needs to jump to ship things in production. How mistakes are very expensive - and thus, we need to ship almost all changes behind feature flags. How the build train means that the changes we make today will take at least 2 weeks to get to prod. How devices being offline is something we need to actively support, and anticipate... and so on. I noticed similar "aha moments" each time. Talking with other mobile engineers in similar environments, they were having similar conversations, and battling similar assumptions on mobile being relatively simple.

I had been collecting the numerous challenging areas that I planned to publish as a blog post. After I shared the draft on Twitter[2], I got an unexpected amount of interest in people offering to contribute. The contents became too long for a post, and so this book was born. Several people asked for a paperback version[3], and I decided to create the book in print as well, as I felt the contents warranted it.

I hope you find this book useful - both if you're a mobile engineer or if you work with mobile teams. And I'd love to hear any feedback!

[1] https://www.mobileatscale.com/#pricing

[2] https://twitter.com/GergelyOrosz/status/1335305213394251780

[3] https://twitter.com/elevenetc/status/1335595203411972097

Built withby tracyhenry

.

Follow me on