Allow specifying run tags in pipeline configuration

[schustmi]

Describe changes

This PR adds the ability to specify tags for pipeline runs

• in the config file

# config.yaml
tags:
  - tag_in_config_file

• in code on the pipeline decorator or in pipeline.configure/with_options

@pipeline(tags=["tag_on_decorator"])
def my_pipeline():
  ...

my_pipeline = my_pipeline.with_options(config_file="config.yaml")
run = my_pipeline()
run.tags  # <- will be tag_in_config_file and tag_on_decorator

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Please ensure you have done the following:

• 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.
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Types of changes

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)
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[htahir1]

Good one!

[bcdurak]

This looks great. I have a few follow-up comments though:

• First, since we are using tags more often now, it would be great if we implement a filtering mechanism for these entities based on their tags. (Not just for pipeline runs, but also for artifact versions, model versions, and so on). What do you think?

• We have recently added the ability to add tags to sagemaker pipelines and steps. Structurally, they look a bit different and it might get a bit confusing to define tags separately for ZenML pipelines and orchestrator pipelines.

pipeline_settings = SagemakerOrchestratorSettings(
    pipeline_tags={
        "project": "my-ml-project",
        "environment": "production",
    }
)

step_settings = SagemakerOrchestratorSettings(
    tags={
        "step": "data-preprocessing",
        "owner": "data-team"
    }
)

• Do you think there is also value in using the same tags in the future to tag step runs as well (as we do for Sagemaker pipelines)?

[schustmi]

This looks great. I have a few follow-up comments though:

• First, since we are using tags more often now, it would be great if we implement a filtering mechanism for these entities based on their tags. (Not just for pipeline runs, but also for artifact versions, model versions, and so on). What do you think?
• We have recently added the ability to add tags to sagemaker pipelines and steps. Structurally, they look a bit different and it might get a bit confusing to define tags separately for ZenML pipelines and orchestrator pipelines.

pipeline_settings = SagemakerOrchestratorSettings(
    pipeline_tags={
        "project": "my-ml-project",
        "environment": "production",
    }
)

step_settings = SagemakerOrchestratorSettings(
    tags={
        "step": "data-preprocessing",
        "owner": "data-team"
    }
)

• Do you think there is also value in using the same tags in the future to tag step runs as well (as we do for Sagemaker pipelines)?

• Filtering by tags is implemented in the API and even in the frontend for all these entities? Or am I missing some other place where you'd want to filter by them?
• We currently don't display steps anywhere separately (at least in the dashboard, which IMO is the main usecase for filtering). So I don't see any value in tagging step runs, at least for now. As for the confusion with sagemaker tags: They'll figure it out if they explicitly define tags for their sagemaker orchestrator and they don't show up on their ZenML pipelines, I wouldn't worry about that.

[bcdurak]

• Filtering by tags is implemented in the API and even in the frontend for all these entities? Or am I missing some other place where you'd want to filter by them?
• We currently don't display steps anywhere separately (at least in the dashboard, which IMO is the main usecase for filtering). So I don't see any value in tagging step runs, at least for now. As for the confusion with sagemaker tags: They'll figure it out if they explicitly define tags for their sagemaker orchestrator and they don't show up on their ZenML pipelines, I wouldn't worry about that.

You are absolutely right. I looked over the filter model, could not see anything related to tags amongst the attributes, got confused, and completely overlooked the fact that it inherits from WorkspaceScopedTaggableFilter 🤦

As for Sagemaker (and for any other orchestrator for that matter), I think the UX could be improved a bit but I think we can take another look later. I trust your judgement on this one.