How to deploy stable diffusion so that its scalable - machine-learning

I would like to use stable diffusion as part of a side project, I have it currently deployed on a vm in google cloud, but its not scalable. How can I deploy it so that its scalable ?

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Example of web development local and production environment sample setup and workflow

I am working on moving our existing websites from a shared hosting to a VPS and then they will be redeveloped and improved using Laravel. My background is not software development, I have however a decent understanding of web development (enough to make a blog, CMS etc) BUT I have never worked in a web dev team so I don't know how things should be done "properly".
Locally I have always used XAMPP and remotely it has always been as basic as publishing files via Filezilla.
Now I have been required to do:
Version control - the changes to the website should be reviewed by a second (non technical person) before going live
Develop a system based on Laravel
What I am struggling to understand is how Ubuntu Server, GIT, Docker, Kubernetes, NGINX etc. all work together. Basically I don't know what "the big picture" looks like, how a decent workflow should look like.
So far I have manually installed all the necessary software to run Laravel on the VPS (the LAMP stack) but soon after I started to run into problems (libraries that are activated locally are not activated remotely). It has also become clear that software updates and differences between my local environment and remote (production environment) will make the issues worst over time.
Can someone explain in VERY general terms, how things should fit together so that my setup is both resilient, robust and scalable? For example:
Install docker on the server and on your computer
Download such and such image
connect GIT in such and such way
Enable unattended-upgrades
The more I read the more I get confused.
What I would like is a simple guide/idea on how things should be done properly.

using AWS EC2 macOS for gitlab CI / CD

since AWS announced that they have now finally MacOS machines in their portfolio, and they are advertise it that was setup for customers to use it for their iOS CI / CD, I want to try that as well. Since I'm very new to the AWS ecosystem, I'm not really aware of what AWS provides overall which I could use for that.
I saw that they provide the macOS in a EC2 and also as a on demand service.
Status Quo:
I host my Repository in GitLab
I have a gitlab CI where I run the iOS pipeline through a curl in azure pipelines. (you pay for a agent per month and my experience with their stability is very bad)
What I want to achieve:
I host my Repository in GitLab
...
...
Run the iOS Pipeline on an AWS EC2 macOS instance on demand.
I already had a look into a lot of how to's but I always end up that I was not able to choose a macOS instance.
You can use AWS EC2 Mac but it is a bad choice. It requires a minimum allocation period of 24 hours at $1.083 per hour. With this price you have plenty of choices.
MacStadium.com - so far most stable cloud mac I have used. You have to setup runner by yourself, price begin from $59/mo.
GitHub Actions Mac runner - Ease to use with all software pre-installed. Work best with GitHub repo, can also work with Gitlab with a little twist. Free for 200 minutes/mo.
macOS Runners on GitLab.com - Work best with Gitlab but still in close beta. Price not decide yet. Use MacStadium under the hook.
bitrise / buildkite / buddybuild etc. all very good if you don't mind they take care of everything for you.

How to run Vagrant with nvidia docker as provider

I'm part of a team developing a machine learning application.
currently we're using Vagrant with a Docker provider as a uniform dev environment.
We want to utilize the GPUs on our computers when we play around during development, and I found that Nvidia released nvidia-docker to enable that for a simple docker container.
How can I use nvidia-docker as a provider for Vagrant?
If it's not possible, is there any equivalent solution?
It is important for us to develop on top of the same docker image that we deploy since we depend on multiple interacting opensource libraries, and we want to manage them in one place
(no dependencies breaking when deploying)

OpenCV deployment on windows azure

Is it possible to deploy an OpenCV application to windows azure?
Open CV is comes into client application category accessible through user interface and also can be used for backend processing. Windows Azure Cloud services is used for web application so Open CV does not fit in the application model. For backend processing you may think to use cloud service as worker but that need lots of work on your part and defeat the purpose.
For the sake of completeness and possibility, you sure can get a Windows Azure Virtual Machine, along with Windows OS and deploy OpenCV application there. Once ready you can Remote Desktop to the VM and use it. You may pay monthly cost to use the VM but you sure can do it. But I am sure that is not your objective either.
Yes, I'll say its possible to install OpenCV applications to Azure.
Check the following Deep Learning VM
It comes with pre-installed software. Most of the machine learning libraries along with the OpenCV project are pre-installed
You can also use APIs to host your models on the Windows Azure

Creating Ruby on Rails cloud hosting

There is a lot of demand in my country for rails and hosting, yet there is not one provider that does this. Are there packaged solutions, or at least guides, out there that can help me get started with providing hosting to people?
You can think of it as a local Heroku.com
I think there is no detailed guides, because every hosting is differs because the demands are different.
For a small sites the Apache/NginX and Phusion Passenger will be very good, because it is easy to use. For large sites, a dedicated VPS is a better solution, because it cannot stale performance (e.g. memory) from other sites.
Some special cases, you can use separated mongrel or webrick instances and proxy them over the webserver.
See the following keywords in google: capistrano, phusion passenger, ruby enterprise, linux rails hosting, xen vps hosting.
Partnering with Jelastic PaaS is a perfect match here. This cloud platform provides out-of-box support for Ruby hosting with automated deployment to containers, automatic scaling and intuitive UI for management https://jelastic.com/blog/ruby-paas-hosting/
And it can be installed on top of any infrastructure (bare metal, IaaS, clouds like Azure or GCP). Currently, it is already available in many countries from local service providers https://jelastic.cloud/
If interested, just drop a message here https://jelastic.com/cloud-platform-for-hosting-providers/

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