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fix(operator): decouple LWS availability from Volcano - #17070
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WalkthroughThe operator now detects LWS independently of Volcano. It no longer watches or cleans up legacy Volcano PodGroups. The upgrade notes and installation guides describe separate scheduling configuration and Volcano or native Kubernetes gang-scheduling options. ChangesLWS and Volcano decoupling
Priority: ⚪ Pending latest changes Estimated code review effort: 3 (Moderate) | ~20 minutes Severity of issue fixed: Medium Merge Risk: 🟡 Moderate · up to
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| Check name | Status | Explanation | Resolution |
|---|---|---|---|
| Docstring Coverage |  |
Docstring coverage is 20.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 5 functions across 3 files. (5 skipped: 5… | Write docstrings for the functions missing them to satisfy the coverage threshold. |
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Check name Status Explanation Title check The title clearly and concisely describes the main change: decoupling LWS availability from Volcano. Linked Issues check Issue #15776requires LWS use without Volcano and allows users to select the scheduling integration.features.Newdetects LWS fromleaderworkerset.x-k8s.ioonly. Unset LWS configuration follows LW…Out of Scope Changes check The changes remain within Issue #15776and the stated implementation. They remove legacy Volcano PodGroup scheme registration, watches, cleanup, and RBAC; preserve explicit Grove Volcano integration; …Description check The description clearly explains the change, implementation details, validation, and linked issue. It includes the required issue reference with Closes #15776. It does not use the template headings …Full details: Linked Issues check
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Explanation
Issue
#15776requires LWS use without Volcano and allows users to select the scheduling integration.features.Newdetects LWS fromleaderworkerset.x-k8s.ioonly. Unset LWS configuration follows LWS API availability, and explicit LWS enablement checks only that API. Volcano discovery runs only for explicitVolcanoSchedulerenablement. The operator still selects the LWS reconciliation path from the LWS gate. Updated tests remove the Volcano migration dependency, and the PR summary reports feature-gate and LWS controller tests passed.
Full details: Out of Scope Changes check
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Explanation
The changes remain within Issue
#15776and the stated implementation. They remove legacy Volcano PodGroup scheme registration, watches, cleanup, and RBAC; preserve explicit Grove Volcano integration; and document separate Volcano and native Kubernetes LWS scheduling options. The migration notes, regenerated manifests, tests, and documentation support the decoupling behavior. No unrelated change is established by the whole-PR summary.
Full details: Description check
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Explanation
The description clearly explains the change, implementation details, validation, and linked issue. It includes the required issue reference with
Closes #15776. It does not use the template headings exactly and does not identify specific files for reviewer focus, but the content is otherwise complete.
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Full details: Docstring Coverage
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Explanation
Docstring coverage is 20.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 5 functions across 3 files. (5 skipped: 5 unsupported.)
Resolution
Write docstrings for the functions missing them to satisfy the coverage threshold.
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Actionable comments posted: 1
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Inline comments:
Review comments at
@docs/fern/pages/kubernetes/installation/multinode-orchestration.md:
- Line 99: Update the native gang-scheduling guidance to state that it is
unsupported for Dynamo-managed LWS workloads: Dynamo creates the LeaderWorkerSet
without spec.scheduling, and that field cannot be added afterward because it is
immutable. Do not present this option as supported unless a creation-time
configuration path is added.
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📒 Files selected for processing: 10
deploy/helm/charts/platform/README.mddeploy/helm/charts/platform/README.md.gotmpldeploy/helm/charts/platform/components/operator/files/role.yamldeploy/operator/cmd/main.godeploy/operator/internal/controller/dynamocomponentdeployment_controller.godeploy/operator/internal/controller/dynamocomponentdeployment_controller_test.godeploy/operator/internal/features/gates.godocs/fern/pages/kubernetes/auto-deployment/auto-deploy-with-dgdr.mddocs/fern/pages/kubernetes/installation/install-dynamo.mddocs/fern/pages/kubernetes/installation/multinode-orchestration.md
💤 Files with no reviewable changes: 2
- deploy/helm/charts/platform/components/operator/files/role.yaml
- deploy/operator/cmd/main.go
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Previously reported defects still present:
- Original discussion: The native gang-scheduling instructions remain unusable for Dynamo-managed workloads: the operator creates LeaderWorkerSets without
spec.scheduling, exposes no creation-time configuration for it, and the field cannot be added after creation because it is immutable. The documentation should mark this path unsupported for Dynamo-managed LWS objects unless the operator adds a creation-time opt-in. - Original discussion: Verified still present: the documentation presents native Kubernetes gang scheduling as an available LWS integration, but Dynamo-generated LeaderWorkerSets omit
spec.scheduling, and no Dynamo configuration path supplies the required creation-time workload opt-in. The current text acknowledges that Dynamo does not set it automatically without explaining how a Dynamo-managed workload can set the immutable field, so users following this path will not actually receive native gang scheduling.
❌ Dynamo PR CI failed — run 40347183264 (attempt 1) on
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| Framework | Multi-GPU amd64 |
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| TRT-LLM | ❌ 1 |
Failure details
1 job failed: the TRT-LLM 2-GPU sequential pytest stage was cut off mid-run while tests/serve/test_trtllm.py::test_deployment[raw_embeddings_epd-2] was executing, so the stage verifier rejected it.
❌ trtllm-runtime / 2-GPU Test cuda13.1, amd64: pre_merge_gpu cut off mid-run during raw_embeddings_epd-2
Job: trtllm-runtime / 2-GPU Test cuda13.1, amd64 · Failed step: Verify test stages completed · Logs: gh run view --job 121664530976 -R ai-dynamo/dynamo --log-failed
collecting ... collected 4112 items / 4108 deselected / 6 skipped / 4 selected
tests/test_predownload_models.py::test_predownload_models[predownload_models_trtllm_gpu2] PASSED [ 25%]
tests/serve/test_trtllm.py::test_deployment[disaggregated-2] PASSED [ 50%]
tests/serve/test_trtllm.py::test_deployment[disaggregated_logprobs-2] PASSED [ 75%]
tests/serve/test_trtllm.py::test_deployment[raw_embeddings_epd-2]
##[group]Run actions/upload-artifact@...
...
##[warning]No files were found with the provided path: test-results/pytest_test_report_*.xml. No artifacts will be uploaded.
...
❌ pre_merge_gpu: reported success but recorded no exit code.
Its script was cut off mid-run, so the result is
unknown and cannot be treated as a pass.
##[error]A pytest stage did not record a passing result. See this step's log for the stage.
The Run GPU tests (sequential) step (15:30–15:38, ~8 min) ended abruptly while test_deployment[raw_embeddings_epd-2] was running: no PASSED/FAILED line, no pytest summary, and no JUnit XML was written, yet the step was reported as success. The verifier step then failed because the stage recorded no exit code. The log shows no assertion or traceback; the per-test log artifacts were skipped, so the cause (test process killed/hung vs. the runner's container exec being interrupted) is not visible here — the uploaded allure-results-trtllm-pre_merge_gpu-amd64-40347183264-121664530976 artifact may have more.
For agents
{"pr": 17070, "run_id": 40347183264, "run_attempt": 1, "head_sha": "56b43763ff9e8b638bee4f9fbc7d9f1952446129",
"failures": [{"job": "trtllm-runtime / 2-GPU Test cuda13.1, amd64", "job_id": 121664530976, "failed_step": "Verify test stages completed", "signature": "pre_merge_gpu cut off mid-run (no exit code recorded) during raw_embeddings_epd-2", "tests": ["tests/serve/test_trtllm.py::test_deployment[raw_embeddings_epd-2]"], "log_cmd": "gh run view --job 121664530976 -R ai-dynamo/dynamo --log-failed"}]}Posted automatically by Devin for run 40347183264. Updated on every full-CI run of this PR.
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Removed the three Chinese translations added in this PR to keep the operator fix focused. The Docs Website Composition Check failure was triggered by a limitation in We will address the resolver issue with regression coverage and restore the translations in a follow-up PR. Validation after removing the translations: no unresolved relative page links for either dev or release snapshots; docs lint passed with 0 errors. |
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The root cause of failing jobs will be resolved by #17285. |
Remove legacy per-replica LWS and PodGroup migration cleanup and document the required upgrade preparation. Closes ai-dynamo#15776 Signed-off-by: carlory <baofa.fan@daocloud.io>
Add matching Chinese installation, multinode orchestration, and DGDR deployment guides. Refs ai-dynamo#15776 Signed-off-by: carlory <baofa.fan@daocloud.io>
Remove the three translations added in this PR. Their roles API link exposes a translation-link resolver issue with inline code in link labels; handle the script fix and translations in a follow-up PR. Refs ai-dynamo#15776 Signed-off-by: carlory <baofa.fan@daocloud.io>
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After rebasing onto #17285, the deploy test failures are fixed. The only remaining failure is That job looks like an infrastructure interruption rather than a test failure. The Could a maintainer please re-run the failed jobs in https://github.com/ai-dynamo/dynamo/actions/runs/40347183264? I don't have permission to re-run them. Thanks! |
Summary
Allow LWS orchestration without requiring Volcano CRDs. The requirement
remained after Dynamo adopted native LWS scaling and stopped creating
PodGroups or forcing the Volcano scheduler.
PodGroup watches, RBAC, and scheme registration.
explicitly enabled.
deployments that still use the legacy per-replica resource layout.
deployment guides.
LWS scheduler configuration is managed separately. Native Kubernetes gang
scheduling support is outside this change.
Closes #15776
Validation
and that relative links point to existing files.
git diff --checkpassed for both commits.fern checkandfern docs broken-linkscould not run because the FernCLI is not installed.