DesWurstes

How to setup a practically free CDN using Backblaze B2 and Cloudflare

⚠️ Note 2023-01-21
Some things have changed since I originally wrote this in 2016. I have updated a few minor details, and the advice is still broadly the same, but there are some new Cloudflare features you can (and should) take advantage of. In particular, pay attention to Trevor Stevens' comment here from 22 January 2022, and Matt Stenson's useful caching advice. In addition, Backblaze, with whom Cloudflare are a Bandwidth Alliance partner, have published their own guide detailing how to use Cloudflare's Web Workers to cache content from B2 private buckets. That is worth reading,

Why you need a prefix for ESNI

Background

Some CDNs allow their customers to bring in their own DNS. Some do not provide DNS service at all, requiring every customer to bring in their own DNS.

The customer's DNS will have a zone definition like the following:

The algorithm that used to be described here is broken.

A better alternative is described here: https://github.com/sipa/writeups/tree/main/elligator-square-for-bn

I recently happened upon a very interesting implementation of popen() (different API, same idea) called popen-noshell using clone(2), and so I opened an issue requesting use of vfork(2) or posix_spawn() for portability. It turns out that on Linux there's an important advantage to using clone(2). I think I should capture the things I wrote there in a better place. A gist, a blog, whatever.

This is not a paper. I assume reader familiarity with fork() in particular and Unix in general, though, of course, I link to relevant wiki pages, so if the unfamiliar reader is willing to go down the rabbit hole, they should be able to come ou

Don't use VPN services.

No, seriously, don't. You're probably reading this because you've asked what VPN service to use, and this is the answer.

Note: The content in this post does not apply to using VPN for their intended purpose; that is, as a virtual private (internal) network. It only applies to using it as a glorified proxy, which is what every third-party "VPN provider" does.

A Russian translation of this article can be found here, contributed by Timur Demin.
A Turkish translation can be found here, contributed by agyild.
There's also this article about VPN services, which is honestly better written (and has more cat pictures!) than my article.

Ok, I geeked out, and this is probably more information than you need. But it completely answers the question. Sorry. ☺

Locally, I'm at this commit:

$ git show
commit d6cd1e2bd19e03a81132a23b2025920577f84e37
Author: jnthn <[email protected]>
Date:   Sun Apr 15 16:35:03 2012 +0200

When I added FIRST/NEXT/LAST, it was idiomatic but not quite so fast. This makes it faster. Another little bit of masak++'s program.

	#!/usr/bin/python3


	#################################################################################
	# #
	#.______ _______. ______ ___ .__ __. #
	#\| _ \ / \| / \| / \ \| \ \| \| #
	#\| \|_) \| ______ \| (----`\| ,----' / ^ \ \| \\| \| #
	#\| / \|______\| \ \ \| \| / /_\ \ \| . ` \| #
	#\| \|\ \----. .----) \| \| `----./ _____ \ \| \|\ \| #

	// Tracking cursor position in real-time without JavaScript
	// Demo: https://twitter.com/davywtf/status/1124146339259002881

	package main

	import (
	"fmt"
	"net/http"
	"strings"
	)

	#!/usr/bin/env bash

	# script that fixes weird macOS 10.14 SDK issues
	# SO: https://stackoverflow.com/questions/51314888/ld-warning-text-based-stub-file-are-out-of-sync-falling-back-to-library-file#comment93288538_53111739
	# script source: https://gist.github.com/wawiesel/eba461de5f5e38f7f0ac93ae3676b484
	# slightly modified to include PrivateFrameworks too

	F=/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/System/Library/Frameworks
	G=/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/System/Library/PrivateFrameworks

	# Mostly copied from https://keras.io/applications/#usage-examples-for-image-classification-models
	# Changing it to use InceptionV3 instead of ResNet50
	from keras.applications.inception_v3 import InceptionV3, preprocess_input, decode_predictions
	from keras.preprocessing import image
	import numpy as np

	model = InceptionV3()
	img_path = 'elephant.jpg'