workflows-samples VS Dokku

Have you seen this? https://cloud.google.com/workflows

Cloud Workflows: A serverless workflow orchestration service

Workflows can trigger actions, like Cloud Run Jobs, in a sequence of steps. The Workflows product waits for the job to complete, fail, or time out before it moves on to the next step. It uses polling to check on the job, so there may be a delay between the job finishing and the next step.

Has anyone integrated firestore/realtime database together with GCP workflows? What was your use case? How was your experience with it? Why have you decided to go that way?

In the past few years, YAML (http://yaml.org) has become an essential part of software, particularly for infrastructure-as-code tools. Yaml at the heart of kubernetes configuration, kubernetes-inspired APIs like Google's config connector, and a number of workflow systems like Google Cloud Workflows and Github Actions.

If your routine is just a bunch of API calls, you can also replace steps 1-2 with Workflows.

I have come at this problem from a bit of a different angle by asking what is the closest I can possibly get to the hypothetical dream state of everything is automated, autoscaling blah blah blah as possible with the absolute smallest budget in terms of not only actual costs but time budget as well.

I only know the GCP ecosystem kind of well so I don't fully know to what extent these things exist in AWS and Azure but there I think there is a really nice path you can get on with the serverless route that skips K8s entirely but keeps you very well aligned in case you ever need to "upgrade" or get out of the GCP ecosystem.

I write very stock standard gRPC services and then put them onto Cloud Run (which has a very Heroku like workflow) and stick https://cloud.google.com/api-gateway in front of things and now my API is running on the exact same setup as any other service Google is running in production. Huge amounts of logic get moved out of my code base as a result.

If you are also willing to write your APIs a fairly particular way https://google.aip.dev/ it starts to become trivial to integrate other things like https://cloud.google.com/workflows, https://cloud.google.com/pubsub and https://cloud.google.com/tasks which is traditionally where a lot of the "state" and weirdly complicated logic previously lived in my code. I'm now not really writing any of that.

Now it's all declarative where I just say what I want to happen and I don't have to think about much else beyond that because it too is using that same internal GCP infrastructure to handle all the complicated parts around what to do when things go wrong.

But to me they are all extremely heavily aligned with the K8s path so the lock in certainly doesn't feel as scary.

Google Workflows combines Google’s cloud services and APIs to help developers build reliable large-scale applications, process automation, and deploy machine learning and data pipelines.

Lately, I build a system using Cloud Workflows which can combine Google Cloud Services such as Cloud Functions and Cloud Run. Sometimes, I was in a situation where I want to examine more efficiently using logs on Cloud Logging when debugging or daily monitoring.

Look at Cloud Workflows for simple workflows

Would be great to see a comparison to some better known alternatives like

- Dokku [0]

- CapRover [1]

[0] https://dokku.com/

[1] https://caprover.com/

If you want to dig into it anyways, Dokku is an interesting mention. They provide an Open Source PaaS that you can install on your server to simplify self hosting containers.

When I came across Coolify, I thought of giving it a try. I am aware of Dokku, but I never really tried it because it doesn't have a UI. I work primarily as a UI developer, so having a nice UI to work with is a plus for me.

I run all my projects on Dokku. It’s a sweet spot for me between a barebones VPS with Docker Compose and something a lot more complicated like k8s. Dokku comes with a bunch of solid plugins for databases that handle backups and such. Zero downtime deploys, TLS cert management, reverse proxies, all out of the box. It’s simple enough to understand in a weekend and has been quietly maintained for many years. The only downside is it’s meant mostly for single server deployments, but I’ve never needed another server so far.

https://dokku.com/

Yeah there are a bunch of selfhostable things:

Caprover (https://caprover.com/)

Dokku (https://github.com/dokku/dokku)

But people still choose Netlify and Vercel for ease of use I think.

Maybe we need something that's just Netlify. The closest I've seen to the "right" UX is Ness:

https://ness.sh

The modern iteration of these tools has taken the developer experience learnings from the Platform as a Service (PaaS) category, and will bring them to your own VM, giving you your own personal PaaS. Example of this include Dokku, Coolify, Caprover, Cloud66 and many more!

Based on the fact that your ideal is to have a similar experience to heroku than managing your own server setting up reverse proxies take a look at these options:

1) https://dokku.com - lets you turn your light sail instance basically into heroku

2) https://render.com

3) https://fly.io

4) If you have aws credits this is their heroku equivalent: https://aws.amazon.com/elasticbeanstalk

above is not what I do but would be the options I would pursue if I understand your preference and requirement correctly.

All in all, I really recommend trying out Dokku if you are a developer interested in hosting your own projects. It makes it super easy to get everything you need to get up and running without having to worry about the specifics. And the price is impossible to beat!

The installation instructions are on the frontpage of our site. Thats basically all you need to do to install Dokku. As far as using it, we have a simplified tutorial here.