This won't work :) echo will run as root but the redirection is still running as the unprivileged user. Needs to be run from a privileged shell or by doing something like sudo sh -c "echo $NUM_PAGES > /proc/sys/vm/nr_hugepages"

The point gets across, though, technicality notwithstanding.

> The real bottleneck is the single-threaded main loop in the postmaster.

A single-threaded event loop can do a lot of stuff. Certainly handle 4000 tasks of some sort in under 10s. Just offhand it seems like it would be eminently possible to handle incoming connections on the scale they describe in a single-threaded event loop.

Clearly the existing postgres postmaster thread is a bottleneck as it is implemented today. But I'd be interested to go deeper into what it's doing that causes it to be unable to keep up with a fairly low workload vs. what is possible to do on a single thread/core.

This sounds exactly like the problem tools like pgbouncer were designed to solve. If you're on AWS one could look at RDS Proxy.

We have a habbit of never scheduling long running processes at round hours. Usually because they tend to be busier.

https://hakibenita.com/sql-tricks-application-dba#dont-sched...

They probably don't even need a database anyway for data that is likely write once, read many. You could store the JSON of the meeting in S3. It's not like people are going back in time and updating meeting records. It's more like a log file and logging systems and data structures should be enough here. You can then take that data and ingest it into a database later, or some kind of search system, vector database etc.

Database connections are designed this way on purpose, it's why connection pools exist. This design is suboptimal.

> Most meetings start on the hour, some on the half, but most on the full. It sounds obvious to say it aloud, but the implication of this has rippled through our entire media processing infrastructure.

When you can control when it happens, you can often jitter things. For instance the naive approach of rate limiting users down to quantized times (eg: the minute, the hour, etc.) leads to every client coming back at the same time. The solution there is to apply a stable jitter so different clients get different resets.

That pattern does not go all that well with meetings as they need to happen when they happen, which is going to be mostly the hour and 30 minutes etc. However often the lead up time to those meetings is quite long, so you can do the work needed that should happen on the hour, quite a bit ahead of time and then apply the changes in one large batch on the minute.

You have similar problems quite often with things like weekly update emails. At scale it can take you a lot of time to prepare all the updates, often more than 12 hours. But you don't want the mails to come in at different times of the day so you really need to get the reports prepared and then send them out when ready.

My first thought was "why even use big databases, you have perfect workload to shard it between a bunch of instances and as a bonus any downtime would only affect smaller part of customers"

I'm actually surprised that it handled that many connections. The data implies that they have 4000 new connections/sec...but is it 4000 connections handled/sec?

ya, right. just make up some reason not following the best practices

you can keep things synced across databases easily and keep it super duper simple.