Skip to content

Replace Databricks Community Edition with Lighthouse [1] #14642

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 8 commits into from
Feb 19, 2025

Conversation

TomeHirata
Copy link
Collaborator

Related Issues/PRs

N/A

What changes are proposed in this pull request?

We stop supporting MLflow remote access to Databricks Community Edition (CE). Instead, we recommend that users use Databricks for a free trial. This PR replaces the existing CE page with new content for Databricks free trial. Changes for tutorials will be addressed in follow-up PRs.

How is this PR tested?

  • Existing unit/integration tests
  • New unit/integration tests
  • Manual tests

Does this PR require documentation update?

  • No. You can skip the rest of this section.
  • Yes. I've updated:
    • Examples
    • API references
    • Instructions

Release Notes

Is this a user-facing change?

  • No. You can skip the rest of this section.
  • Yes. Give a description of this change to be included in the release notes for MLflow users.

Document update to replace Community Edition with Databricks free trial.

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

Components

  • area/artifacts: Artifact stores and artifact logging
  • area/build: Build and test infrastructure for MLflow
  • area/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations
  • 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/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
  • 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

Interface

  • 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

Language

  • 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

How should the PR be classified in the release notes? Choose one:

  • rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
  • rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
  • rn/feature - A new user-facing feature worth mentioning in the release notes
  • rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
  • rn/documentation - A user-facing documentation change worth mentioning in the release notes

Should this PR be included in the next patch release?

Yes should be selected for bug fixes, documentation updates, and other small changes. No should be selected for new features and larger changes. If you're unsure about the release classification of this PR, leave this unchecked to let the maintainers decide.

What is a minor/patch release?
  • Minor release: a release that increments the second part of the version number (e.g., 1.2.0 -> 1.3.0).
    Bug fixes, doc updates and new features usually go into minor releases.
  • Patch release: a release that increments the third part of the version number (e.g., 1.2.0 -> 1.2.1).
    Bug fixes and doc updates usually go into patch releases.
  • Yes (this PR will be cherry-picked and included in the next patch release)
  • No (this PR will be included in the next minor release)

Copy link

github-actions bot commented Feb 18, 2025

Documentation preview for c99c3d6 will be available when this CircleCI job
completes successfully. You may encounter a {"message":"not found"} error when reloading
a page. If so, add /index.html to the URL.

More info

Signed-off-by: Tomu Hirata <[email protected]>
@TomeHirata TomeHirata marked this pull request as ready for review February 18, 2025 11:22
Signed-off-by: Tomu Hirata <[email protected]>
@TomeHirata TomeHirata added the rn/documentation Mention under Documentation Changes in Changelogs. label Feb 19, 2025
@@ -140,44 +140,62 @@ of this method below:
- Requires extra port forwarding if you deploy your server on cloud VM.
- No serving support.

## Method 2: Use Free Hosted Tracking Server (Databricks Community Edition)
## Method 2: Use Free Hosted Tracking Server (Databricks Free Trial)

**Notice**: This part of guide can be directly executed in cloud-based notebook, e.g., Google Colab or
Copy link
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Can we move these instruction to getting-started/databricks-trial/index.html? Ideally the guide should be accessible from every tutorial not only from this one.

Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Moved most parts to getting-started/databricks-trial/index.html and changed the content in the tracking server overview to point to the page.

Signed-off-by: Tomu Hirata <[email protected]>
Signed-off-by: Tomu Hirata <[email protected]>
Signed-off-by: Tomu Hirata <[email protected]>
Copy link
Collaborator

@B-Step62 B-Step62 left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM!

nearly full functionlities of the Databricks platform including managed MLflow.
You can use a Databricks Workspace to store and view your MLflow experiments without being charged within the free trial period.
Refer to the instructions in <Link to="/getting-started/databricks-trial/" target="_blank">Try Managed MLflow</Link>
for how to use the Databricks Free Trial to store and view your MLflow experiments.

### Conclusion
Copy link
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

(not a blocker) What about making these pros/cons as a single table and put at the top of this doc, so users can compare side-by-side? Having three Conclusion paragraphs feel a bit strange when reading.

Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Good call, let me do it as a follow up.

@TomeHirata TomeHirata enabled auto-merge February 19, 2025 13:53
@TomeHirata TomeHirata added this pull request to the merge queue Feb 19, 2025
Merged via the queue into mlflow:master with commit c6383fc Feb 19, 2025
41 checks passed
@TomeHirata TomeHirata deleted the docs/lighthouse/1 branch February 19, 2025 15:27
@B-Step62 B-Step62 removed the v2.20.3 label Feb 26, 2025
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
rn/documentation Mention under Documentation Changes in Changelogs.
Projects
None yet
Development

Successfully merging this pull request may close these issues.

3 participants