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WhatsApp can't tell me how many users were talking about Peanut Butter Sandwiches 30 seconds ago. WhatsApp can't alert me when people suddenly start talking abo

WhatsApp can't tell me how many users were talking about Peanut Butter Sandwiches 30 seconds ago. WhatsApp can't alert me when people suddenly start talking about earthquakes, super bowls, or Elon Musk. WhatsApp doesn't need to fanout a message to millions of consumers, millions of times a day (and with multi-second latency to boot!). WhatsApp also doesn't provide a CDN, mobile analytics/monetization/debugging platform. WhatsApp also doesn't contribute to open source like Twitter does (Storm, Bootstrap, Aurora). Describing twitter as a "140-char" mailing list is very reductionist. OTOH WhatsApp problem is very well served by Erlang/Mnesia an open source distributed messaging library developed by telecommunications company who were likely doing WhatApp-scale 10 yeas before WhatsApp came around. While WhatsApp engineers are great, there is very much a "standing on the shoulders of giants" - giants who have well researched the problem of building a system that lets two or three individuals communicate. There wasn't anyone doing Twitter 10 years ago (well, maybe Google). I don't mean to imply that Twitter is an efficient well oiled machine, but the comparison to WhatsApp is daft.

oinksoft 11y ago
You're underestimating the difficulty of scaling Mnesia the way WhatsApp did (one source says "In-memory Mnesia database using about 2TB of RAM sharded across 16 partitions to store about 18 billion records." [1]). The prevailing wisdom in the Erlang community was that Mnesia could not be made to do such things. The only well-known user of Mnesia at anywhere near this scale prior to WhatsApp was Klarna. To achieve this, Klarna employed at least one of the original Mnesia developers who wrote proprietary patches for their system [2]. So while you accuse parent of being reductionist, your views of WhatsApp's engineering challenges also seem reductionist. Erlang/OTP software doesn't write and scale itself ... large-scale distributed systems are decidedly non-trivial no matter what tools you've chosen. [1] http://highscalability.com/blog/2014/3/31/how-whatsapp-grew-to-nearly-500-million-users-11000-cores-an.html http://highscalability.com/blog/2014/3/31/how-whatsapp-grew-... [2] https://www.erlang-factory.com/upload/presentations/601/EUC2012-009.pdf https://www.erlang-factory.com/upload/presentations/601/EUC2...
- nemothekid 11y ago
  When I checked this post, you were below zero - I'm not sure why you are downvoted. In any case, my main point isn't that that WhatsApp is simple. When I said the parent posted was being reductionist, I was referring to Twitter's product offering. AFAIK (I could be wrong) WhatsApp is a messaging backend and multiple client frontends. The "50" engineers is deceiving becaus, despite the fact that Mnesia could or couldn't have scaled, there is a very non-trivial amount of engineers who worked on it and Mnesia is a good & proven system. In a similar light, Instagram was 13 engineers (or was it employees) and hundreds of django instances - and that maybe all you need for a photo feed, however Instagram didn't have a trending feature until earlier this year and how knows how many engineers that took. If WhatApp hired another 200 engineers, likely 195 would either be twiddling their thumbs or working on new features outside what was needed in that acquisition to Facebook. Now we can make the argument that Twitter is bloated because they have too many products (Fabric, Vine, Crashlytics, and their numerous other acquisitions) - and the scaling back of those engineers may mean sunsetting those products - and thats fair. To imply they have 4000 engineers building a glorified 140-char mailing list is not.

oinksoft 11y ago

You're underestimating the difficulty of scaling Mnesia the way WhatsApp did (one source says "In-memory Mnesia database using about 2TB of RAM sharded across 16 partitions to store about 18 billion records." [1]). The prevailing wisdom in the Erlang community was that Mnesia could not be made to do such things. The only well-known user of Mnesia at anywhere near this scale prior to WhatsApp was Klarna. To achieve this, Klarna employed at least one of the original Mnesia developers who wrote proprietary patches for their system [2]. So while you accuse parent of being reductionist, your views of WhatsApp's engineering challenges also seem reductionist. Erlang/OTP software doesn't write and scale itself ... large-scale distributed systems are decidedly non-trivial no matter what tools you've chosen. [1] http://highscalability.com/blog/2014/3/31/how-whatsapp-grew-to-nearly-500-million-users-11000-cores-an.html http://highscalability.com/blog/2014/3/31/how-whatsapp-grew-... [2] https://www.erlang-factory.com/upload/presentations/601/EUC2012-009.pdf https://www.erlang-factory.com/upload/presentations/601/EUC2...

nemothekid 11y ago
When I checked this post, you were below zero - I'm not sure why you are downvoted. In any case, my main point isn't that that WhatsApp is simple. When I said the parent posted was being reductionist, I was referring to Twitter's product offering. AFAIK (I could be wrong) WhatsApp is a messaging backend and multiple client frontends. The "50" engineers is deceiving becaus, despite the fact that Mnesia could or couldn't have scaled, there is a very non-trivial amount of engineers who worked on it and Mnesia is a good & proven system. In a similar light, Instagram was 13 engineers (or was it employees) and hundreds of django instances - and that maybe all you need for a photo feed, however Instagram didn't have a trending feature until earlier this year and how knows how many engineers that took. If WhatApp hired another 200 engineers, likely 195 would either be twiddling their thumbs or working on new features outside what was needed in that acquisition to Facebook. Now we can make the argument that Twitter is bloated because they have too many products (Fabric, Vine, Crashlytics, and their numerous other acquisitions) - and the scaling back of those engineers may mean sunsetting those products - and thats fair. To imply they have 4000 engineers building a glorified 140-char mailing list is not.