odrotbohm

Modulith VS. Microservices

This document contains a tabular comparison of the Modulithic and Microservice Architecture approach under certain aspects. Many of them can be achieved or influenced in both styles, but to different degrees and using different means. No claims of exhaustiveness.

rponte

Pretende usar UUID como PK em vez de Int/BigInt no seu banco de dados? Pense novamente...

TL;TD

Não use UUID como PK nas tabelas do seu banco de dados.

Um pouco mais de detalhes

craigtp

Advanced Distributed System Design Course - Udi Dahan

Notes by Craig Phillips

Fallacies of Distributed Computing

• There are 11 fallacies of Distributed Computing:
  1. The network is reliable
  2. Latency isn’t a problem
  3. Bandwidth isn’t a problem
  4. The network is secure

5. The topology won’t change

bgadrian

type Set struct {
	list map[int]struct{} //empty structs occupy 0 memory
}

func (s *Set) Has(v int) bool {
	_, ok := s.list[v]
	return ok
}

timvisee

Falsehoods programmers believe about time

This is a compiled list of falsehoods programmers tend to believe about working with time.

Don't re-invent a date time library yourself. If you think you understand everything about time, you're probably doing it wrong.

Falsehoods

• There are always 24 hours in a day.
• February is always 28 days long.
• Any 24-hour period will always begin and end in the same day (or week, or month).

soulmachine

First of all, please note that token expiration and revoking are two different things.

1. Expiration only happens for web apps, not for native mobile apps, because native apps never expire.
2. Revoking only happens when (1) uses click the logout button on the website or native Apps;(2) users reset their passwords; (3) users revoke their tokens explicitly in the administration panel.

1. How to hadle JWT expiration

A JWT token that never expires is dangerous if the token is stolen then someone can always access the user's data.

Quoted from JWT RFC:

ptarjan

Scaling your API with rate limiters

The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.

In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.

Request rate limiter

This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.

pmunin

using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.ComponentModel;
using System.Timers;

namespace DebounceUtils
{
    /// <summary>
    /// Event debouncer helps to prevent calling the same event handler too often (like mark Dirty or Invalidate)

vasanthk

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

1. Clarify and agree on the scope of the system

• User cases (description of sequences of events that, taken together, lead to a system doing something useful)
  • Who is going to use it?
  • How are they going to use it?

richardkundl

namespace BloomFilter
{
	using System;
	using System.Collections;

	/// <summary>
	/// Bloom filter.
	/// </summary>
	/// <typeparam name="T">Item type </typeparam>
	public class Filter<T>