Which would also be a good read, but this article also isn't that. It doesn't discuss their experience deploying the protocol, aside from the following statement:

> Meerkat is not deployed to production, but we have run multiple proofs-of-concept with up to 50 replicas distributed around the world, to great success. Leaders in our proof-of-concept clusters constantly fail, and the cluster keeps operating with no increase in error-rate.

I think it would've been more interesting to read why Cloudflare chose the specific algorithm they did, see an example of a pathological but common situation Cloudflare sees at their scale that makes other protocols unsuitable for them, therefore they made X choice and this led to Y gains in production (or on dummy workloads, or whatever). As it stands, there's nothing here actually specific to Cloudflare's workload or deployment. It doesn't even state their use-case beyond "small pieces of control plane state (e.g., leadership for replicated databases)"

Maybe the blog post is just premature. It would be much more valuable if they posted it after actually having run it in production and validated the strengths and weaknesses with real world data.

They could have picked something far more concrete (for Cloudflare's business and the type of services they deploy) than "AI model" there, which is clearly picked just to make it seem 'current' and on-trend.

This is obviously true, and there are surely more web devs than, say, compiler engineers.

But then the logic seems to go as far as to imply nobody does or should be doing these things. Where do they think the “off the shelf” solutions came from?

I worked at <big internet tech company>, and many critical systems written in the 90’s and early 2000s used bespoke compilers, caches, and consensus protocols that were hand rolled by the original developers.

Back then, most of these ideas were already present in academia. But the industry tech wasn’t quite there yet to run these huge services at scale without running into problems (paying a vendor, licensing, the open source solution not quite there or tunable enough to easily integrate it at the needed scale, no company wide consensus on a shared approach yet).

A lot of these handwritten implementations eventually informed the “off the shelf industry solutions” we have today.

I think that’s what gets me down about tech these days. There’s a weird almost anti innovation attitude, which is the opposite of what made me fall in love with this profession. I’m not saying to hand roll a consensus algorithm at your next start up. But there’s definitely a vibe these days that any sort of theoretical, creative, or innovative thinking is suspect. Get back to selling ads!