Learnings

<p>Recommended Books 2021 for platform engineer and SRE </p>

<p>When dealing with extensive Figma files with dozens of different Pages, you can create an empty page between other pages and call it ” ” to create breathing rooms between contexts and make the file more amicable to navigate.</p>

<p>Does the join order matter in SQL? </p>

<p>A capability-safe language would have minimized the impact of, or even prevented, the log4j vulnerability: </p>

<p>Software architecture patterns: Take a deep dive into several common software architecture patterns </p>

<p>The Key to Understanding Why Things Happen: </p>

<p>An ad plugin was stealing 30% of the revenue for a year and I didn't even notice: </p>

<p>How To Stay Curious as a Coder </p>

<p>I’m harvesting credit card numbers and passwords from your site. Here’s how: </p>

<p>Thread about what platform engineering is, where the trends are going, and why you should care: </p>

<p>Designing accessible services: best design practices for users from these areas: low vision, D/deaf and hard of hearing, dyslexia, motor disabilities, users on the autistic spectrum and users of screen readers </p>

<p>Continuous Integration and Feature Branching </p>

<p>How to use regex and be able to understand one day later what I did the day before. </p>

<p>Services Don’t Have to Be Eight-9s Reliable </p>

<p>Never, Ever, Ever Use Pixelation for Redacting Text </p>

<p>10 Usability Heuristics Applied to Complex Applications. </p>

<p>How to build software that’s ready for the handoff: </p>

<p>Django’s Field Choices Don’t Constrain Your Data </p>

<p>The Factorio Mindset: </p>

<p>Heuristics That Almost Always Work: </p>

<p>Organizational culture that is high-trust and emphasizes information flow is predictive of software delivery performance and organizational performance in technology: </p>

<p>Alexandrian Patterns - A solution to a problem in a context:</p>

<p>Improve Serialization Performance in Django Rest Framework </p>

<p>Simplistic protocols and models and language features can end up becoming <em>complexity multipliers</em> because the complexity is duplicated by each and every <em>user</em> of the model or protocol. They are also effort multipliers. Fortunately, one can sometimes solve this problem by wrapping or refactoring the protocol or model or language feature within a library to utilize it, thus capturing the Essential Complexity into the library and thus creating the feature/language/model that should have existed in the first place. </p>