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Enrich documentations for docker deployment
🛠 DevTools 🛠
Install mlflow from this PR
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/10983/merge
Checkout with GitHub CLI
gh pr checkout 10983
Related Issues/PRs
Follow-up for #10954
What changes are proposed in this pull request?
Add documentation for the new --install-java
flag and warning box for the default behavior change.
How is this PR tested?
- [x] Existing unit/integration tests
- [ ] New unit/integration tests
- [x] Manual tests
Does this PR require documentation update?
- [x] 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?
- [x] 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.
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 - [x]
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:
- [x]
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
Documentation preview for 3e7d5446905e55e44fa629e77a938126b61b6a95 will be available here when this CircleCI job completes successfully.
More info
- Ignore this comment if this PR does not change the documentation.
- It takes a few minutes for the preview to be available.
- The preview is updated when a new commit is pushed to this PR.
- This comment was created by https://github.com/mlflow/mlflow/actions/runs/7792387067.