Add a deployment mode to skip non-essential validation checks during kedro run

[DimedS]

Description

Introduce a dedicated deployment mode for kedro run command, which could be enabled via a flag (e.g., --deployment) or through project settings. This mode would skip non-essential validation checks that are only useful during pipeline development.

This ticket is a follow-up to the discussion in #4603 (comment)

Currently, there are more than five checks prefixed with _validate_ that verify the validity of the pipeline structure. However, once a pipeline has been developed and tested locally, these checks are less meaningful when running the pipeline repeatedly in a deployment environment without any changes to the pipeline code.

Benefits

• Reduced runtime overhead in production
• More control for advanced users deploying stable pipelines
• Aligns with patterns seen in other tools that offer dev vs. prod execution modes

[datajoely]

How are we ensuring dependencies are valid. We have a wider uv ticket, it would be great to look into compiling just the necessary requirements.

[datajoely]

I'd also like to see how we handle the following requirement:

• as a user I'm deploying my Kedro pipeline to a k8s based orchestrator
• part of my Kedro pipeline is data engineering focused and needs Spark, JDK etc.
• part of my Kedro pipeline is ML focused and needs Tensorflow/Pytorch

I want to only want to deploy the relevant dependencies to the target containers. Note it's not an issue / very cheap to deploy the same code twice even if only part of it will be executed in different locations.