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jgc AT cloudflare DOT com

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"Oh I get that this is the key fact, I put a smiley in there because I was fishing for a more exact number that is unlikely to be given"

The honest truth is that I actually don't know how many servers we have because it's not a number that I have to worry about.

I do know that floor(log_10(#servers)) = 2.

Hundreds of servers in 23 locations worldwide, each server running multiple instances of Nginx: http://blog.cloudflare.com/a-tour-inside-cloudflares-latest-... The key fact is that this type of scale is possible with Nginx + Lua + hundreds (not thousands) of servers.

If that were to happen (and I think it's a big "if" because of the complexity of predicting what will throw it off given that the attacker doesn't know the code we are running) then we'd see the WAF latency increase and alarms would be generated immediately. That, in turn, would cause a bunch of other mechanisms to come into play.

We are entirely Linux not NetBSD and are not currently using Lua in the kernel at all. We did, however, sponsor some of Mike Pall's work on LuaJIT based on our particular workload: http://luajit.org/sponsors.html#sponsorship_perf

We use Lua for the WAF (as Mike says), but also for all request processing. This is in part because we use Nginx and in part because employ agentzh (http://agentzh.org/) and he works on OpenResty. Fairly recently we moved all processing of requests through CloudFlare to a Lua-based system inside Nginx.

That's >5B pages views per 24 hours going through LuaJIT-ed code.

From the post:

    A recent example illustrates the power of this approach:

    Cloudflare's WAF (web application firewall) basically generates
    Lua code for the (highly non-linear) maze of firewall rules. An
    incoming attack triggers certain rules and the corresponding paths
    are turned into linearized traces. These can be heavily optimized
    by LuaJIT, much more so than you could ever hope to do with a
    static compiler.

    When a different attack wave is started, it'll spawn different
    traces -- i.e. the generated code dynamically adapts to the
    specific attacks.

    The result is a much higher firewall throughput than you might be
    able to achieve with a data-driven or a static compilation
    approach. This directly equates into money saved on machines
    needed to handle the load.
Added to that is the fact that the WAF configuration (which is automatically generated Lua code) is different for each customer and so we rely heavily on caching and JITing to get the performance.

The bottom line is that LuaJIT is very fast and very flexible.

I'll poke around and have a look to see why. The Ray ID will be different each time; it's a debugging feature that identifies the request when something goes wrong.

If this persists please contact support AT cloudflare DOT com so we can track it.