swalkinshaw

Moved to Shopify/graphql-design-tutorial

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.

markrendle

Update, September 2016

OK, you can pretty much ignore what I wrote below this update, because it doesn't really apply anymore.

I wrote this over a year ago, and at the time I had spent a couple of weeks trying to get Kafka 0.8 working with .NET and then Node.js with much frustration and very little success. I was rather angry. It keeps getting linked, though, and just popped up on Hacker News, so here's sort of an update, although I haven't used Kafka at all this year so I don't really have any new information.

In the end, we managed to get things working with a Node.js client, although we continued to have problems, both with our code and with managing a Kafka/Zookeeper cluster generally. What made it worse was that I did not then, and do not now, believe that Kafka was the correct solution for that particular problem at that particular company. What they were trying to achieve could have been done more simply with any number of other messaging systems, with a subscriber reading messages off and writing

kachayev

Channels Are Not Enough

... or Why Pipelining Is Not That Easy

Golang Concurrency Patterns for brave and smart.

By @kachayev

Intro

tsiege

ANNOUNCEMENT

I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!






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Chaser324

Whether you're trying to give back to the open source community or collaborating on your own projects, knowing how to properly fork and generate pull requests is essential. Unfortunately, it's quite easy to make mistakes or not know what you should do when you're initially learning the process. I know that I certainly had considerable initial trouble with it, and I found a lot of the information on GitHub and around the internet to be rather piecemeal and incomplete - part of the process described here, another there, common hangups in a different place, and so on.

In an attempt to coallate this information for myself and others, this short tutorial is what I've found to be fairly standard procedure for creating a fork, doing your work, issuing a pull request, and merging that pull request back into the original project.

Creating a Fork

Just head over to the GitHub page and click the "Fork" button. It's just that simple. Once you've done that, you can use your favorite git client to clone your repo or j

macintux

• https://ferd.ca/a-distributed-systems-reading-list.html
• http://the-paper-trail.org/blog/distributed-systems-theory-for-the-distributed-systems-engineer/
• https://github.com/palvaro/CMPS290S-Winter16/blob/master/readings.md
• http://muratbuffalo.blogspot.com/2015/12/my-distributed-systems-seminars-reading.html
• http://christophermeiklejohn.com/distributed/systems/2013/07/12/readings-in-distributed-systems.html
• http://michaelrbernste.in/2013/11/06/distributed-systems-archaeology-works-cited.html
• http://rxin.github.io/db-readings/
• http://research.microsoft.com/en-us/um/people/lamport/pubs/pubs.html
• http://pdos.csail.mit.edu/dsrg/papers/
• http://scalingsystems.com/2011/09/07/reading-list-for-distributed-systems/

gschema

Basic JavaScript MVC Implementation

Despite being derived from classical MVC pattern JavaScript and the environment it runs in makes Javascript MVC implementation have its own twists. Lets see how typical web MVC functions and then dive into simple, concrete JavaScript MVC implementation.

How Web MVC typically works

Typical server-side MVC implementation has one MVC stack layered behind the singe point of entry. This single point of entry means that all HTTP requests, e.g. http://www.example.com or http://www.example.com/whichever-page/ etc., are routed, by a server configuration, through one point or, to be bold, one file, e.g. index.php.

At that point, there would be an implementation of Front Controller pattern which analyzes HTTP request (URI at first place) and based on it decides which class (Controller) and its method (Action) are to be invoked as a response to the request (method is name for function and member is name for a variable when part of the class/object).

drewjoh

<?php

	require("postmark.php");
	
	$postmark = new Postmark("your-api-key","from-email","optional-reply-to-address");
	
	$result = $postmark->to("reciver@example.com")
		->subject("Email Subject")
		->plain_message("This is a plain text message.")
		->attachment('File.pdf', base64_encode(file_get_contents('sample.pdf')), 'application/pdf')