Create a kustomize tekton resolver

A Tekton bundle resolver can quickly and concisely reference a pipeline bundle but this precludes the pipeline definition from being modified. In order to support modification of a pipeline definition, a kustomize-like resolver should be created.

Goals

In order to enable shorter referencing customization of Tekton pipelines, it would be beneficial if there was a kustomize-like resolver which can inject custom tasks into a Pipeline reference.

Requirements

• • (Optional) Use Cases

< What are we making, for who, and why/what problem are we solving?>

Out of scope

<Defines what is not included in this story>

Dependencies

< Link or at least explain any known dependencies. >

Background, and strategic fit

< What does the person writing code, testing, documenting need to know? >

Assumptions

< Are there assumptions being made regarding prerequisites and dependencies?>

< Are there assumptions about hardware, software or people resources?>

Customer Considerations

< Are there specific customer environments that need to be considered (such as working with existing h/w and software)?>

Documentation Considerations

< What educational or reference material (docs) is required to support this product feature? For users/admins? Other functions (security officers, etc)? >

What does success look like?

< Does this feature have doc impact? Possible values are: New Content, Updates to existing content, Release Note, or No Doc Impact?>

QE Contact

< Are there assumptions being made regarding prerequisites and dependencies?>

< Are there assumptions about hardware, software or people resources?>

Impact

< If the feature is ordered with other work, state the impact of this feature on the other work>

Related Architecture/Technical Documents

<links>

Done Checklist

• Acceptance criteria are met
• Non-functional properties of the Feature have been validated (such as performance, resource, UX, security or privacy aspects)
• User Journey automation is delivered
• Support and SRE teams are provided with enough skills to support the feature in production environment