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Mark Chadwick markchadwick

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@philippta
philippta / microservices.md
Last active February 23, 2025 06:27

This Microservice Should Have Been a Library

About 6 years ago when I was a PHP ecommerce dev, I've always wanted to work with distributed systems and microservices. They seemed so cool and the new way of architecting software systems because all of big tech did it. But now working with them day to day for about 3 years I came to realize that my initial anticipation was stupid. Well, not stupid in the traditional sense, because how could I have known what I'd get myself into.

Microservices and distributed systems have been preached to solve two major problems: Scale and scale.

So let's talk about them.

@kyleburton
kyleburton / bot-verbs.txt
Last active August 19, 2024 23:02
The list of 'bot-verbs' that we give to new team members.
Philosophical:
* writing lines of code is one of the least valuable things I can do
* cultivate your impatience
* reject the status quo, unless we can re-derive it from first-principles
* engineers imprint on the first languages (techniuqes, frameworks or technology) that we find success with (unconsciously seen as caregivers, which we defend w/o always knowing why)
* we tend to overvalue the familiar/known; we tend to undervalue the unfamiliar/unknown, this interferes with our receptiveness to new ideas and personal growth
* we're 90% composed of bad habits; many of our best habits become bad as time passes; this allows us to filter for the fundamental; the great
* make doing the right thing easier than any other thing, or we will fail to achieve greatness, or break bad habits
* be conscious, be intentional
* "is this the highest we can aim?" (I prefer this over "is this the best we can do", the former is aspirational, the latter is judgemental)
@debasishg
debasishg / gist:8172796
Last active June 23, 2025 05:56
A collection of links for streaming algorithms and data structures

General Background and Overview

  1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
  2. Models and Issues in Data Stream Systems
  3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
  4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
  5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t