This. AWS architect here. There are a lot of ways to reduce pricing in AWS like horizontal scaling, serverless functions, reserved instances. Most people aren’t aware of it and if you’re going to dive in head first into something like cloud, you’ll need to bear the consequences and then learn eventually.
Interesting, I’ll check out droplets, but in my experience with Azure Functions there’s not much vendor lock in. My API was just a normal Node.js / express server, the only part that was locked in to Azure Functions was the format for the endpoint definitions, but those can be adjusted in like an hour’s worth of time to anything else
Yep. And if you want to really save some cash and don’t mind getting a little crazy, use an EKS node orchestrator that supports spot instances. I’m starting to do a serious dive into Harness at the moment actually.
Google recently released a white paper on cost saving in kubernetes as well.
If you’ve got a kubernetes cluster running on 10 different spot instances, isn’t there a risk that all ten could be revoked at the same time? Even if they are built out across regions and availability zones?
Counterargument: I don’t need Lemmy to have 100% uptime. It’s not a corporate service and while – obviously – if it’s down all the time I would eventually move on, I’m not going to fault a not-for-profit entity for periodic failures.
I’m in a similar boat. I’m a sysadmin supporting a legacy application running on AWS EC2 instances and a new ‘serverless’ microservice based platform as well. It’s really really hard to scale and optimize anything running on EC2s unless you really know what you’re doing or the application is designed with clustering in mind.
You tend to end up sizing instances based on peak load and then wasting capacity 90% of the time (and burning through cash like crazy). I can imagine a lot of Lemmy admins are overspending so fast they give up before they figure it out.
This. AWS architect here. There are a lot of ways to reduce pricing in AWS like horizontal scaling, serverless functions, reserved instances. Most people aren’t aware of it and if you’re going to dive in head first into something like cloud, you’ll need to bear the consequences and then learn eventually.
Even with ASGs, ec2 costs a bomb for performance.
And “serverless” functions are a trap.
If you’re gonna commit to reserved instances, just buy hardware for goodness sake, its a 3 year commitment with a huge upfront spend.
How are serverless functions a trap? They seem like a great cheap option for simple CRUD / client > server > db apps (what most apps end up being).
Anything that is “cheap” to do on serverless is cheaper to do on a $5 droplet, especially once it starts to grow.
Serverless gets you to buy in to a vendors lock-in.
Interesting, I’ll check out droplets, but in my experience with Azure Functions there’s not much vendor lock in. My API was just a normal Node.js / express server, the only part that was locked in to Azure Functions was the format for the endpoint definitions, but those can be adjusted in like an hour’s worth of time to anything else
Yep. And if you want to really save some cash and don’t mind getting a little crazy, use an EKS node orchestrator that supports spot instances. I’m starting to do a serious dive into Harness at the moment actually.
Google recently released a white paper on cost saving in kubernetes as well.
If you’ve got a kubernetes cluster running on 10 different spot instances, isn’t there a risk that all ten could be revoked at the same time? Even if they are built out across regions and availability zones?
Counterargument: I don’t need Lemmy to have 100% uptime. It’s not a corporate service and while – obviously – if it’s down all the time I would eventually move on, I’m not going to fault a not-for-profit entity for periodic failures.
I’m in a similar boat. I’m a sysadmin supporting a legacy application running on AWS EC2 instances and a new ‘serverless’ microservice based platform as well. It’s really really hard to scale and optimize anything running on EC2s unless you really know what you’re doing or the application is designed with clustering in mind.
You tend to end up sizing instances based on peak load and then wasting capacity 90% of the time (and burning through cash like crazy). I can imagine a lot of Lemmy admins are overspending so fast they give up before they figure it out.