MLflow Roadmap Item

This is an MLflow Roadmap item that has been prioritized by the MLflow maintainers. We’ve identified this feature as a highly requested addition to the MLflow package based on community feedback.
We're seeking a community contribution for the implementation of this feature and will enthusiastically support the development and review of a submitted PR for this.

Contribution Note

As with other roadmap items, there may be a desire for multiple contributors to work on an issue. While we don’t discourage collaboration, we strongly encourage that a primary contributor is assigned to roadmap issues to simplify the merging process.
The items on the roadmap are of a high priority. Due to the wide-spread demand of roadmap features, we encourage potential contributors to only agree to take on the work of creating a PR, making changes, and ensuring that test coverage is adequately created for the feature if they are willing and able to see the implementation through to a merged state.

Feature scope

This roadmap feature’s complexity is classified as:

• good-first-issue: This feature is limited in complexity and effort required to implement.
• simple: This feature does not require a large amount of effort to implement and / or is clear enough to not need a design discussion with maintainers.
• involved: This feature will require a substantial amount of development effort but does not require an agreed-upon design from the maintainers. The feedback given during the PR phase may be involved and necessitate multiple iterations before approval. (Please bear with us as we collaborate with you to make a great contribution)
• design-recommended: This is a substantial feature that should have a design document approved prior to working on an implementation (to save your time, not ours). After agreeing to work on this feature, a maintainer will be assigned to support you throughout the development process.

Proposal Summary

This FR intends to bring support for model version searching in search_registered_models() by tags. This is a re-visitation of #3296 and should involve a detailed refactoring and merging of the general implementation in that PR.
This search should also implement or logic similar to #6075

Motivation

What is the use case for this feature?

Simplify the process of finding registered models by supporting user-configured tags within the model registry.

Why is this use case valuable to support for MLflow users in general?

It's challenging to search for registered models at organizations that have a large ML 'footprint' of deployed models.

What component(s), interfaces, languages, and integrations does this feature affect?

Components

• area/artifacts: Artifact stores and artifact logging
• area/build: Build and test infrastructure for MLflow
• area/docs: MLflow documentation pages
• area/examples: Example code
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/projects: MLproject format, project running backends
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/server-infra: MLflow Tracking server backend
• area/tracking: Tracking Service, tracking client APIs, autologging

Interfaces

• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
• area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
• area/windows: Windows support

Languages

• language/r: R APIs and clients
• language/java: Java APIs and clients
• language/new: Proposals for new client languages

Integrations

• integrations/azure: Azure and Azure ML integrations
• integrations/sagemaker: SageMaker integrations
• integrations/databricks: Databricks integrations