swarmsible VS deploy-cloudrun

We use Docker Swarm for our deployments, so I will answer the questions based on that.

We have built some tooling around setting up and maintaining the swarm using ansible [0]. We also added some Hetzner flavour to that [1] which allows us to automatically spin up completely new clusters in a really short amount of time.

deploy from source repo:

- We use Azure DevOps pipelines that automate deployments based on environment configs living in an encrypted state in Git repos. We use [2] and [3] to make it easier to organize the deployments using `docker stack deploy` under the hood.

keep software up to date:

- We are currently looking into CVE scanners that export into prometheus to give us an idea of what we should update

load balancing:

- depending on the project, Hetzner LB or Cloudflare

handle scaling:

- manually, but i would love to build some autoscaler for swarm that interacts with our tooling [0] and [1]

automate backups:

- docker swarm cronjobs either via jobs with restart condition and a delay or [4]

maintain security:

- Hetzner LB is front facing. Communication is done via encrypted networks inside Hetzner private cloud networks

- [0] https://github.com/neuroforgede/swarmsible

Pretty much the same as our goto for projects at work: Hetzner + Docker (Swarm) with some Ansible to orchestrate things

We have built some automation around cluster management over at https://github.com/neuroforgede/swarmsible.

I used to do everything in ansible, but Docker Stacks are just so much nicer to use.

In any case automation is king. I don't have to remember stuff if I can just look at some IaC Code :).

Our tooling can be found here https://github.com/neuroforgede/swarmsible . It is not yet documented tbh, but most things are pretty straight forward to use if you have used ansible, docker etc already.

Story of one of the projects I am involved in:

We came from Ansible managed deployments of vanilla docker with nginx as single node ingress with another load balancer on top of that.

Worked fine, but HA for containers that are only allowed to exist once in the stack was one thing that caused us headaches.

Then, we had a workshop for Rancher RKE. Looked promising at the start, but operating it became a headache as we didn't have enough people in the project team to maintain it. Certificates expiring was an issue and the fact that you actually kinda had to baby-sit the cluster was a turn off.

We killed the switch to kubernetes.

In the meantime we were toying around with Docker Swarm for smaller scale deployments and inhouse infrastructure. We didn't find anything to not like and are currently moving into that direction.

How we do things in Swarm:

1. Monitoring using an updated Swarmprom stack (https://github.com/neuroforgede/swarmsible/tree/master/envir...)

For anyone interested in this, check out: https://github.com/neuroforgede/swarmsible/blob/master/environments/test/test-swarm/stacks/02_monitoring/README.md

Examples for products in this category are: Google Cloud Run, AWS App Runner, Azure Container Apps. Each has different scalability, cost, and integration trade-offs.

Cloud Run is a managed platform that enables you to run container based workloads on top of Google infrastructure. Cloud Run automates many of the above steps and allows you to focus on developing and deploying updates to your application.

Serverless computing was also introduced, where the developers focus on their code instead of server configuration.Google offers serverless technologies that include Cloud Functions and Cloud Run.Cloud Functions manages event-driven code and offers a pay-as-you-go service, while Cloud Run allows clients to deploy their containerized microservice applications in a managed environment.

The quickest way is to deploy to Cloud Run. The service will use Dockerfile to build the production image. You can even omit the GOOGLE_APPLICATION_CREDENTIALS env var as these are in GCP’s projects by default.

In our company we use Google Cloud Run to deploy web applications, and every app is built into a docker image. For now we use the default memory limit by Cloud Run which is 256 MB per container. Recently we started to notice that the part of applications go beyond this limit, causing a container to restart and in some cases even resulting to downtime of a service.

It's perhaps a little fiddlier than other options, but you can probably host it on Google Cloud Run and it would fall within the free tier.

You can see more here on how to use the google cloud run github actions.

I wonder what the aversion is to using a plain old server / vps. It's really not that difficult to deploy nowadays [0][1][2][3] and I'd rather get an $8 bill every month as insurance than ever worry about shit like OP just went through. It'll probably be more performant anyway due to cold starts and "edge" still having to hit us-east-1 for data.. cache your static files with Cloud Flare/Front. People are always surprised by how much traffic a single VPS can take[4] and believe it all has to be serverless to be web scale. I believe HN still runs on a single core or something.

There's a ton of places to get cloud credits as well, too many to link, so just Bing™ it

[0] https://docs.aws.amazon.com/cdk/api/v2/docs/aws-cdk-lib.aws_...

[1] https://aws.amazon.com/apprunner/

[2] https://cloud.google.com/run

[3] https://render.com/

[4] https://news.ycombinator.com/item?id=34676186

Google Cloud Run