> What I had missed is that we deployed a new internal service last week that sent less than three GetPostRecord requests per second, but it did sometimes send batches of 15-20 thousand URIs at a time. Typically, we'd probably be doing between 1-50 post lookups per request.
The incredible part about this is because their backend is all TCP/IP they were literally exhausting the ports by leaving all 65k of them in TIME_WAIT, and the workaround was to start randomizing the localhost address to give them another trillion ports or so.
The simple answer is that atproto works like the web & search engines, where the apps aggregate from the distributed accounts. So the proper analogy here would be like yahoo going down in 1999.
Google and MSN Search were already available at this time. Also websites used to publish webrings and there was IRC and forums to ask people about things.
It’s more of a concept of a plan for being distributed. I even went through the trouble of hosting my own PDC and still, I was unable to use the service during the outage
> The timing of these log spikes lined up with drops in user-facing traffic, which makes sense. Our data plane heavily uses memcached to keep load off our main Scylla database, and if we're exhausting ports, that's a huge problem.
Golang's use of a potentially unbounded number of threads is just insane. I used to be fairly bullish on golang, but this, combined with the fact that its garbage collected, makes me feel its just unsuitable for production use.
You can have this problem with any kind of thread -- including OS threads -- if you do an unbounded spawn loop. Go is hardly unique in this.
Goroutines are actually better AFAIK because they distribute work on a thread pool that can be much smaller than the number of active goroutines.
If my quick skim created a correct understanding, then the problem here looks more like architecture. Put simply: does the memcached client really require a new TCP connection for every lookup? I would think you would pool those connections just like you would a typical database and keep them around for approximately forever. Then they wouldn't have spammed memcache with so many connections in the first place...
(edit: ah, it looks like they do use a pool, but perhaps the pool does not have a bounded upper size, which is its own kind of fail.)
Why does garbage collection make it unsuitable for production use? A lot of production software is written in garbage collected languages like Java. Pretty much the entire backend for iTunes/Apple Music is written in Java, and it's not doing any kind of fancy bump allocator tricks to avoid garbage. In my mind, kind of hard to argue that Apple Music is not "production use".
There are certainly plenty of projects where garbage collection is too slow, but I don't know that they're the majority, and more people would likely prefer memory safety by default.
Email and the internet don't have "downtime." Certain key infra providers do of course. ISPs can go down. DNS providers can go down. But the internet and email itself can't go down absent a global electricity outage.
You haven't built a decentralized network until you reach that standard imo. Otherwise its just "distributed protocol" cosplay. Nice costume. Kind of like how everybody has been amnesia'd into thinking Obsidian is open source when it really isn't.
The comparison here is to something like TCP/IP. TCP/IP never goes down. TCP/IP is a protocol, the servers may go down and cause disruption, but the protocol doesn't really have the ability to "go down".
Nostr is also a protocol. The communication on top of Nostr is pretty resilient compared to other solutions though, so that's the main highlight here.
If tens of servers go down, then some people may start noticing a bit of inconvenience. If hundreds of servers go down, then some people may need to coordinate out of bound on what relays to use, but it still generally speaking works ok.
That’ll do it.
The simple answer is that atproto works like the web & search engines, where the apps aggregate from the distributed accounts. So the proper analogy here would be like yahoo going down in 1999.
I expect this is common.
Goroutines are actually better AFAIK because they distribute work on a thread pool that can be much smaller than the number of active goroutines.
If my quick skim created a correct understanding, then the problem here looks more like architecture. Put simply: does the memcached client really require a new TCP connection for every lookup? I would think you would pool those connections just like you would a typical database and keep them around for approximately forever. Then they wouldn't have spammed memcache with so many connections in the first place...
(edit: ah, it looks like they do use a pool, but perhaps the pool does not have a bounded upper size, which is its own kind of fail.)
There are certainly plenty of projects where garbage collection is too slow, but I don't know that they're the majority, and more people would likely prefer memory safety by default.
Email and the internet don't have "downtime." Certain key infra providers do of course. ISPs can go down. DNS providers can go down. But the internet and email itself can't go down absent a global electricity outage.
You haven't built a decentralized network until you reach that standard imo. Otherwise its just "distributed protocol" cosplay. Nice costume. Kind of like how everybody has been amnesia'd into thinking Obsidian is open source when it really isn't.
AOL never even got to that level of dominance in the internet 1.0 era.
The point is it's not a distributed network if one node is 99.9% of all traffic.
Okay, nuff trolling for today
If tens of servers go down, then some people may start noticing a bit of inconvenience. If hundreds of servers go down, then some people may need to coordinate out of bound on what relays to use, but it still generally speaking works ok.
The article does work in lynx, at least I can read it.