In-browser assisted full cloud stack deployments

Describe changes

Implements a new automated experience of deploying cloud infrastructure and registering full cloud ZenML stacks two-in-one with minimal user input. This experience is meant to reduce the friction and technical difficulties usually encountered when a user has to create a cloud ZenML stack from scratch.

The zenml stack deploy CLI command has been repurposed to support this new experience as showcased here:

$ zenml stack deploy -p aws --set

AWS ZenML Cloud Stack Deployment                                                                                                                                                                                   
================================

Provision and register a basic AWS ZenML stack authenticated and connected to all the necessary cloud infrastructure resources required to run pipelines in AWS.                                                   

**Instructions**                                                                                                                                                                                                       

You will be redirected to the AWS console in your browser where you'll be asked to log into your AWS account and create a CloudFormation ZenML stack. The stack parameters will be pre-filled with the necessary   
information to connect ZenML to your AWS account, so you should only need to review and confirm the stack.                                                                                                         

After the CloudFormation stack is deployed, you can return to the CLI to view details about the associated ZenML stack automatically registered with ZenML.                                                        

NOTE: The CloudFormation stack will create the following new resources in your AWS account. Please ensure you have the necessary permissions and are aware of any potential costs:                                 

 • An S3 bucket registered as a ZenML artifact store.                                                                                                                                                              
 • An ECR repository registered as a ZenML container registry.                                                                                                                                                     
 • Sagemaker registered as a ZenML orchestrator.                                                                                                                                                                   
 • An IAM user and IAM role with the minimum necessary permissions to access the above resources.                                                                                                                  
 • An AWS access key used to give access to ZenML to connect to the above resources through a ZenML service connector.                                                                                             

The CloudFormation stack will automatically create an AWS secret key and will share it with ZenML to give it permissions to access the resources created by the stack. You can revoke these permissions at any time
by deleting the CloudFormation stack.                                                                                                                                                                              

Proceed to continue with the deployment. You will be automatically redirected to AWS in your browser. [y/n]: y
If your browser did not open automatically, please open the following URL into your browser to deploy the stack to AWS: AWS CloudFormation Console.                                                                

**Stack successfully registered! 🚀**                                                                                                                                                                                  

Stack stack:                                                                                                                                                                                                       

 • sagemaker orchestrator: aws-cf-eu-central-1-wpyh                                                                                                                                                                
 • s3 artifact_store: aws-cf-eu-central-1-iaiy                                                                                                                                                                     
 • aws container_registry: aws-cf-eu-central-1-smep                                                                                                                                                                
 • Service Connector: aws-cf-eu-central-1-pabl                                                                                                                                                                     

**Follow-up**                                                                                                                                                                                                          

The ZenML stack has been successfully deployed and registered. You can delete the CloudFormation at any time to revoke ZenML's access to your AWS account and to clean up the resources created by the stack by    
using the AWS CloudFormation console.

AWS is currently the only supported provider with Google and Azure to follow shortly.

Side changes

Make the `zenml` repository name configurable in the container registry stack component

Currently, ZenML uses the .../zenml docker repository by default for all pipeline images it builds/pushes. This can be overridden, but it's a docker settings that must be configured in code. At the same time, we want these full stack deployment templates to create unique cloud resources, which includes container registries. Therefore, we need the ability to configure the container registry stack components to use a "default repository name" that is different than zenml. This PR also adds that capability by modeling a new (optional) default_repository configuration attribute to all container registry stack components.

Use the region from the AWS service connector in the S3 artifact store

The S3 artifact store doesn't explicitly configure the AWS region in the s3fs client. This can lead to errors in environments such as Sagemaker, because the region might default to something else. This PR now uses the AWS region in the service connector to explicitly configure the s3fs client.

Deprecations

The zenml stack deploy CLI command has been renamed to zenml stack deploy-mlstack and marked as deprecated. Users should use the new zenml stack deploy CLI command to benefit from the new experience or use the mlstacks project stacks separately.

Pre-requisites

Please ensure you have done the following:

[x] I have read the CONTRIBUTING.md document.
[ ] If my change requires a change to docs, I have updated the documentation accordingly.
[ ] I have added tests to cover my changes.
[x] I have based my new branch on develop and the open PR is targeting develop. If your branch wasn't based on develop read Contribution guide on rebasing branch to develop.
[ ] If my changes require changes to the dashboard, these changes are communicated/requested.

Types of changes

[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)
[ ] Other (add details above)

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@schustmi I might need you to take a quick look at the side-change documented in the PR description. It affects the way we build docker container images to run pipelines.

LLM Finetuning template updates in examples/llm_finetuning have been pushed.

zenml-io / zenml