←back to thread

DigitalOcean App Platform

(pages.news.digitalocean.com)
646 points digianarchist | 2 comments | | HN request time: 0s | source
Show context
user5994461 ◴[] No.24700185[source]
I am so glad to see this. I was looking to deploy an app and the choice is either Heroku or manage your own server which I don't want to do.

Heroku gives instant deployment for the most common types of apps (python/java/ruby). It's PaaS done right, it's fantastic. You should really have a look if you're not aware of it, it's only $7 for a starter app.

Problem is, scaling up is about $50 per gigabyte of memory which makes it a dead end for anything non trivial. You're forced to go to digital ocean / Linode / OVH instead to have something affordable.

That leaves Digital Ocean as the only alternative (don't trust Linode) and it sucks because it only gives me a server to manage. I don't want to manage a server I want to run a (python) application. It's 2020 this sort of things should auto deploy from GitHub without bothering me to manage an operating system.

replies(19): >>24700693 #>>24700794 #>>24701039 #>>24702228 #>>24702633 #>>24702880 #>>24703398 #>>24703543 #>>24703620 #>>24704410 #>>24704873 #>>24705031 #>>24705668 #>>24706188 #>>24706382 #>>24707003 #>>24709134 #>>24716137 #>>24727185 #
dvcrn ◴[] No.24705668[source]
Why not take the initial complexity cost and learn k8s and containerization? That's what I've been doing as a step-up from Heroku and have been very happy with it.

My project currently runs on Digitalocean managed k8s and setting it up really wasn't hard. I had everything already in containers for dev/prod anyway, and having those run on k8s just meant I had to write the deployment manifests that pull the containers and setup the pods.

What I love about managed k8s (and also shared a couple times in comments on HN) is that it's separated from the servers below. I can have 20 containers (that can be separate things all-together) running on the cheapest Droplet and would only pay whatever that droplet costs, so under $20. Then when I need more power, I just scale the Droplets used for the k8s cluster and my pods/containers get shoveled around the available resources automatically.

I liked this approach so much that I now have a private 'personal projects cluster' that runs on digitalocean with the cheapest/weakest droplet avvailable, and whenver I have a small hobby project that needs to be hosted somewhere, I just add that container to the k8s cluster and be done with it.

replies(4): >>24705748 #>>24705749 #>>24706558 #>>24706813 #
prakis ◴[] No.24706558[source]
> Why not take the initial complexity cost and learn k8s and containerization?

Security, OS patches, maintaince and more than anything DDOS attacks. I don't want to handle all that, I just want to concentrate on development not maintaince.

replies(1): >>24706591 #
1. dividedbyzero ◴[] No.24706591[source]
Managed k8s offerings usually take care of everything below the k8s API. Our GKEs auto-upgrade their control plane and the worker nodes, both OS and k8s versions. I could force my way onto the workers via SSH if I really wanted to, but by default I can't even get on those machines. All you ever do yourself is kubectl this, kubectl that. I believe DO's k8s offering is like that as well.
replies(1): >>24706689 #
2. ForHackernews ◴[] No.24706689[source]
You're still self-hosting, just on top of k8s rather than on top of VMs. All the ingress is your problem, logging, monitoring...

It's only managed in the same way that AWS Elastic Beanstalk is managed.