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Support display in progress traces#19265

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B-Step62 merged 20 commits intomlflow:masterfrom
B-Step62:support-display-in-progress-traces
Dec 12, 2025
Merged

Support display in progress traces#19265
B-Step62 merged 20 commits intomlflow:masterfrom
B-Step62:support-display-in-progress-traces

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@B-Step62 B-Step62 commented Dec 8, 2025

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Install mlflow from this PR

# mlflow
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/19265/merge
# mlflow-skinny
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/19265/merge#subdirectory=libs/skinny

For Databricks, use the following command:

%sh curl -LsSf https://raw.githubusercontent.com/mlflow/mlflow/HEAD/dev/install-skinny.sh | sh -s pull/19265/merge

Related Issues

#16244

What changes are proposed in this pull request?

Current trace detail UI can only render a completed trace. However, now MLflow (SQL backend) support ingesting spans incrementally and the new GetTrace API can return spans from in-progress traces. This PR adds support to show in-progress trace.

The change can be broke down into three:

  1. Call the new GetTrace endpoint when the server is OSS SQL backend (by checking the span location tag) to fetch spans from a in-progress trace.
  2. Update trace renderer to handle multiple top-level spans. The root span is exported at the end, so the trace will have multiple roots until then.
  3. Add auto-polling (only when the backend is OSS SQL) to fetch new spans automatically.

How is this PR tested?

  • Existing unit/integration tests
  • New unit/integration tests
  • Manual tests
In-progress.trace.mp4

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.

Support displaying spans in a in-progress trace incrementally.

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

Components

  • area/tracking: Tracking Service, tracking client APIs, autologging
  • area/models: MLmodel format, model serialization/deserialization, flavors
  • area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
  • area/scoring: MLflow Model server, model deployment tools, Spark UDFs
  • area/evaluation: MLflow model evaluation features, evaluation metrics, and evaluation workflows
  • area/gateway: MLflow AI Gateway client APIs, server, and third-party integrations
  • area/prompts: MLflow prompt engineering features, prompt templates, and prompt management
  • area/tracing: MLflow Tracing features, tracing APIs, and LLM tracing functionality
  • area/projects: MLproject format, project running backends
  • area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
  • area/build: Build and test infrastructure for MLflow
  • area/docs: MLflow documentation pages

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)

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
@github-actions github-actions bot added area/tracing MLflow Tracing and its integrations rn/feature Mention under Features in Changelogs. labels Dec 8, 2025
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
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github-actions bot commented Dec 8, 2025

Documentation preview for e2cfa2e is available at:

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Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Comment on lines +37 to +39
// Stop polling if trace is completed
const traceState = data && isV3ModelTraceInfo(data.info) ? data.info.state : undefined;
return traceState === 'IN_PROGRESS' ? 1000 : false;
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I wonder if this works well, if root_span is logged before child spans (e.g. concurrent span logging) then trace info status will be updated as OK and we stop polling.
Similar for databricks, if the trace info status is also generated from root span status then it's possible child spans are not logged?

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Hmm that's true. If the root span is there, we can actually compare the span count and keep polling.

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We still say status "OK", in that case, but I think it is valid since the traced operation itself is indeed completed, just trace logging is not complete.

Also there can be a case where a child span completely gets lost due to network issue, then this keep polling. But I think it is fine - we only poll while the trace modal is open and users will likely close it after waiting for a while.

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Yeah the thing I want to avoid is that we stop polling and some spans are not logged, the user closes this page and then clicks into it again finding the structure changed. I previously discussed this with Daniel a bit, and feel like adding a refresh button may work better.

Comment on lines +37 to +39
// Stop polling if trace is completed
const traceState = data && isV3ModelTraceInfo(data.info) ? data.info.state : undefined;
return traceState === 'IN_PROGRESS' ? 1000 : false;
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I wonder if this works well, if root_span is logged before child spans (e.g. concurrent span logging) then trace info status will be updated as OK and we stop polling.
Similar for databricks, if the trace info status is also generated from root span status then it's possible child spans are not logged?

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Hmm that's true. If the root span is there, we can actually compare the span count and keep polling.

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We still say status "OK", in that case, but I think it is valid since the traced operation itself is indeed completed, just trace logging is not complete.

Also there can be a case where a child span completely gets lost due to network issue, then this keep polling. But I think it is fine - we only poll while the trace modal is open and users will likely close it after waiting for a while.

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Yeah the thing I want to avoid is that we stop polling and some spans are not logged, the user closes this page and then clicks into it again finding the structure changed. I previously discussed this with Daniel a bit, and feel like adding a refresh button may work better.

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
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looks good!

@B-Step62 B-Step62 enabled auto-merge December 12, 2025 07:22
@B-Step62 B-Step62 added this pull request to the merge queue Dec 12, 2025
Merged via the queue into mlflow:master with commit 11ed451 Dec 12, 2025
52 of 54 checks passed
@B-Step62 B-Step62 deleted the support-display-in-progress-traces branch December 12, 2025 07:48
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4 participants