[srer]

A single server is much faster than most people think, too!

In the microservice or serverless arrangements I've seen, data is scattered across the cloud.

It's common for the dominant factor in performance to be data locality, most times this talk about data locality is about avoiding trips to RAM, or worse disk. But in our "modern" distributed cloud things, finding a bit of data frequently involves a trip over the network. In the monolith world what was once invoking a method on an account object, has become making a HTTP POST to the accounts microservice.

What might have been a microseconds operation in the single server world, might become hundreds of milliseconds in the distributed cloud world. While you can't horizontally scale a single server, your 1000x head start in performance might delay scaling issues for a very long time.

A most excellent paper related to this topic that I think should be mandatory reading before allowing anyone an AWS account is http://www.frankmcsherry.org/assets/COST.pdf :)

[bayindirh]

When you give half the effort to set things up properly, a single server can handle a lot of load and traffic, and get a lot of things done.

If you know some details of the services you're going to host on that hardware, the things you can do while saving a lot of resources is considered as black magic by many people who only deploys microservices to K8S systems.

...and you don't need VMs, containers, K8S and anything.

[GGfpc]

What are those details?

[bayindirh]

It generally boils down to three things: 1) How much resource a service need to run well, 2) How much the service wants to consume if left unchecked, 3) How performant you want your service to be.

After understanding these parameters, you can limit the resources of your application by running it under a cgroup. Doing this won't allow a service to surpass the limits you've put onto it, and cgroup will pressure your service when it nears its resource limits.

Also, sharing resources is good. Instead of having 10 web server containers, you can host all of them under a single one with virtual hosts, most of the time. This allows good resource sharing and doing more with less processes.

On the extreme case, I'm running a home server (DNS server, torrent client, synching client, a small HTTP server and an FTP server with some other services) under a 512MB OrangePi Zero. The guy works well, and never locks up. It has plenty of free RAM, and none of the services are choking.

[codethief]

I agree but at the same time: Inter-process communication is also faster when a process is allowed to write to or read from another process's memory. Doesn't make it a good idea, though.

[bayindirh]

The way I deploy them doesn't mean "compromise one, compromise all". For example, I generally leave SELinux intact. So they're properly isolated.

[moralestapia]

Yeah, nowadays you could just scale-up and still have a lot of leeway. A high-end server (w/ redundancy maybe) is more than enough for 95% of all common startup use cases.

Distributed computing only makes sense when you're starting to deal with millions of daily users.

[efortis]

Yes. HN works well with one dual socket server (2 x 4)

A new server could have 4 × 64.

Also, to distribute the load you can use an ‘A’ DNS record per server:

https://blog.uidrafter.com/freebsd-jails-network-setup

[awoimbee]

To be fair you can run a microservices stack on a single server and it will be very fast, especially if you use gRPC instead of HTTP

[postalrat]

Would grpc make a huge difference if requests took a second each?

[dopp0]

gRPC being an RPC, it avoids the overload of HTTP by miles, achieving low latency as well.