Serverless Golang API with AWS Lambda
read.acloud.guru
read.acloud.guru
I'm hoping someone will correct me if I'm missing something. Otherwise it seems like Lambda isn't really suited to use-cases where random latency spikes would degrade user experience.
The Lambda runtime is exceedingly slow at that on the 128MB tier. This is in fact the case for Django apps, even in their default state.
Now here's where the fun fact starts: If a function times out during cold start, it hasn't successfully been warmed. That means upon its next trigger, it will coldstart again.
Now lets say you deploy a tiny little function over wsgi. You see in your metrics that it takes an avg of 200ms... now, you're a smart dev, you set its global timeout to 3 seconds down from the default of 30 seconds because you don't want to get billed more than necessary. But as it turns out, the cold start takes on average 10 seconds. Your function now never successfully completes.
It was not meant to run an entire framework in. If you’re reaching for an entire framework to run a simple function in a lambda, I’d bail on one or the other. Don’t use a framework, or don’t use lambda.
Example: I have an API in Django which uses DRF, served on a classic web server instance behind load balancers etc. Parts of that API, which have the same authentication/business logic/etc, are much more suited to lambda, I'm sure it's not hard to imagine :)
That is, the cost of idle time is shifted from your account to their account. This sets up a bit of a race: Amazon's goal is to have as few hidden warm instances for as little time as possible. The user's goal is to have as many hidden warm instances as possible for as long as possible.
This is where you start to see pinging to provoke AWS into keeping a warm copy. As time goes on they will have a growing incentive to prevent tricks like these from working.
At the moment, on the economics, hosted FaaSes will always have this tension. Self-hosted FaaSes open up the possibility of setting your own policy for trading latency against idle cost.
Disclosure: I am part of a team working on Project Riff, a FaaS.
if you already have a K8s cluster it's probably cheaper to just create your application regulary and use it like that. No need to use a FaaS which complicates your whole setup for no additional benefit.
As it happens Riff and most other FaaS projects are built on kubernetes.
I still have these resources idle, when I use Riff.
Most folk want cold starts for economic reasons and warm starts for performance reasons. In a hosted setting you can't truly set your policy, you can only try to encourage by external stimuli.
A good example would be using something like apex/gateway which simply proxies lambda requests to golang standard http handlers. Virtually elminating vendor lock-in.
I think serverless has a place (yes even for business logic) but like anything you have to pick the right took for the job.
Apex/gateway: https://github.com/apex/gateway
I won’t argue that its cheaper because it’s not. Once you get to a certain point you should probably migrate onto real instances which is why I think that the abstraction I talked about is important.
You can easily get this with CoreOS + docker images on GCE
> manage load balancing
Load balancers are one click since what, 2005?
> or scaling (yes I’m aware of the cold start latency cost).
Except you do. You run a 4 CPU database on the backend. How many lambdas can hit it at once before it dies? You need to manage this still.
Lambda is not the worst thing ever, but many many things using it would be far better off on something like kubernetes or a docker image behind a load balancer.
People talk about vendor lock-in and all that. If you don't write things from scratch there is a vendor lock-in everywhere. Open source is also vendor lock-in. For example, we used to use xulrunner from Mozilla for some time and look where it is right now - nowhere.
I was also concerned initially with being locked in into a particular platform but then again, what I realised is that if your project is extremely successful you can always spend big to migrate when you have the funds to do it. As a startup, that is not the case. You start with nothing. So platforms like AWS are absolutely amazing because not too long ago you still had to buy your own datacenters.
But just in terms of dollars, how much does it cost to own hardware? I have never worked in an "infrastructure" team so I'm am outsider looking at it with no experience but I hope someone will correct me.
Imagine a startup needs a 42U cabinet in four co locations. Each one costs a thousand to fifteen hundred dollars a month? Let's say that puts the colocation bill at $5k a month. Next, we need the actual computers and it seems this is the expensive part? I simply searched for servers. Just for kicks, I selected a 2U supermicro 2023US-TR4. With 2x epyc 7301 16 core processors, 16 x 4GB RAM, 2TB Intel P4600 SSD, 4TB Hitachi 7K6000 HDD, and a five year next business day on site service quotes about $10k.
I imagine you can fit up to 20 such computers in a full 42U cabinet. This means just buying the computers will set us back 4 * 20 * $10k? Spending almost $1M on admittedly low end server hardware sounds expensive.
Colocation cost over let's say five years will be about 5 * 12 * $5k or about $300k.
I guess just because you have space for 20 computers doesn't mean you have to fill them all up. Also, I guess you don't need to be in four locations.
If we scale down our ambitions to 10 computers each in two locations, initial cost is 2 * 10 * $10k or about $200k and colocation costs are 5 * 12 * < $2k? or about $100k? because we no longer need a full cabinet...
I know I'm making a lot of assumptions and I'm hand washing a lot of important details but this seems like the smallest possible cost of self hosting, no? About $300k over five years is about $5k per month. It won't make sense for everyone but I guess if we have a thousand people paying us ten dollars a month, that pays for the hardware?
I welcome all corrections and insights. Like I said, I have no experience in these things.
I used to work for a company that leased dedicated servers, and I talked to A LOT of customers that lost their business or lost a significant amount of their runway/savings/whatever due to mistakes caused by not having a real sysadmin around to handle their infrastructure. Long running issues they didn't have the experience to troubleshot, bad (or nonexistent!) backups or restoration procedures, extended outages due to server related issues, bad update/firewall/other security practices, etc.
There's pitfalls with every option, but running your own infrastructure is a completely different skillset from developing an application, and is a professional trade in and of itself - you can try to force this on a developer and hope they have the time and expertise to handle all of these different things and run the risk that they don't, or you can tack on another ~100k/yr for a professional. And as you grow, so does the complexity, and maybe now your infrastructure spans a lot of racks, and you need network engineers, you need multiple sysadmins, etc, etc, etc.
You can't DevOps your way out of managing physical infrastructure
"Yep, that's cgi"
For the not-yet-old farts: https://en.wikipedia.org/wiki/Common_Gateway_Interface
(Note CGI capable accounts are still available for WAY cheaper than on Amazon at a great many hosters)
(And no, the program is not restarted every request: https://en.wikipedia.org/wiki/FastCGI )
(You can even get ones that "autoscale" because the load is sharded on the hosters side, meaning the CGI will start up on a number of different servers - can be pretty high - when required, and only when required)
Implementations for pretty much every language are available.
Serverless does, of course, mean WAY less efficient (but you're charged for that by Amazon, so that's a plus, not a minus for cloud providers), far less language implementations than cgi, less support, closed source, much bigger memory usage, ...