Nick Payne makeusabrew

Abstraction Suggestions

Summary: use good/established messaging patterns like Enterprise Integration Patterns. Don't make up your own. Don't expose transport implementation details to your application.

Broker

As much as possible, I prefer to hide Rabbit's implementation details from my application. In .Net we have a Broker abstraction that can communicate through a lot of different transports (rabbit just happens to be our preferred one). The broker allows us to expose a very simple API which is basically:

publish
request
start/stop subscription

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns                     on recent CPU
L2 cache reference ........................... 7 ns                     14x L1 cache
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns                     20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs 4X memory

Backend Architectures

Twitter

ror, scala, jetty, erlang, thrift, mongrel, comet server, my-sql, memchached, varnish, kestrel(mq), starling, gizzard, cassandra, hadoop, vertica, munin, nagios, awstats

Introduce Gizzard of Twitter - 트위터의 새로운 분산 관리 라이브러리 Gizzard를 소개합니다.
The Architecture Twitter Uses to Deal with 150M Active Users, 300K QPS, a 22 MB/S Firehose, and Send Tweets in Under 5 Seconds
Scaling Twitter: Making Twitter 10000 Percent Faster

Make it real

Ideas are cheap. Make a prototype, sketch a CLI session, draw a wireframe. Discuss around concrete examples, not hand-waving abstractions. Don't say you did something, provide a URL that proves it.

Ship it

Nothing is real until it's being used by a real user. This doesn't mean you make a prototype in the morning and blog about it in the evening. It means you find one person you believe your product will help and try to get them to use it.

	'use strict';

	const parseExpression = require("./parse-expression");

	function findAll(regex, target) {
	let results = [], match;

	while (match = regex.exec(target)) {
	results.push(match);
	}

	function MyObject() {}

	MyObject.prototype.doSomething = function() {
	console.log('MyObject.doSomething()');
	}

	// -----

	var parent = MyObject;

	<?php
	// An experiment: using traits for dependency injection

	// A trait provides a way to inject a Logger and a way to use it
	trait aLogger {
	protected $logger = null;
	public function setLogger(Logger $logger){
	$this->logger = $logger;
	}
	public function log($msg){

	/**
	* Returns a function which won't be invoked until delay has elapsed, without further calls being made during that interval.
	* If further calls are made, the delay is reset and the cycle repeats.
	* @param {Function} fn Behaviour to be wrapped in this delay
	* @param {Number} delay Duration in milliseconds
	* @return {Function}
	*/
	function until(fn, delay) {
	var timeoutId;
	var scheduledCall = setTimeout.bind(window, fn, delay);

	(based on http://www.whatsmypass.com/the-top-500-worst-passwords-of-all-time)

	123456
	porsche
	firebird
	prince
	rosebud
	password
	guitar
	butter

	Latency Comparison Numbers (~2012)
	----------------------------------
	L1 cache reference 0.5 ns
	Branch mispredict 5 ns
	L2 cache reference 7 ns 14x L1 cache
	Mutex lock/unlock 25 ns
	Main memory reference 100 ns 20x L2 cache, 200x L1 cache
	Compress 1K bytes with Zippy 3,000 ns 3 us
	Send 1K bytes over 1 Gbps network 10,000 ns 10 us
	Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD