ci(kimi): add aggregated nightly smoke test

[sara4dev]

Summary

Run the upstream Kimi-K2.5 aggregated Eagle3/KV-router recipe as a functional nightly after the TensorRT-LLM image is published. The Kustomize overlay uses one aggregate replica across two GB200 nodes (8 GPUs), the populated shared model cache, immutable nightly image, and GCP scheduling. No model-download job is run.

Reuse the upstream deployment and AIPerf manifests directly. Limit trace replay to concurrency 1 and 60 seconds, retaining the upstream five-request warmup. Use the cached trace dataset and collect run-scoped results through the frontend. Kimi and DeepSeek share preflight, deployment, diagnostics, result verification, artifact upload, and cleanup.

Validation

• Rebased onto main (1a26bf9cb7); the Kimi render is byte-identical to the validated run. Workflow lint and scoped pre-commit checks passed.

• Deterministic render, native v1alpha1 recipe validator, server-side dry run, focused actionlint/ShellCheck, and scoped pre-commit checks passed.

• Confirmed the trace dataset exists on the shared cache. The rendered upstream benchmark command is unchanged.

• Validation run at 23b44f07fb passed: all three serving pods Ready with zero restarts, five successful warmup requests, and 200 successful trace requests with zero errors.

• Artifacts uploaded and independently verified. Recipe resources, pods, and credentials were cleaned; the shared namespace remains Active and model-cache PVC Bound.

Refs OPS-8639.

Summary by CodeRabbit

• Chores
  • Added automated nightly smoke testing for Kimi K2.5 aggregated deployments.
  • Added reusable performance-test workflows for Kimi K2.5 and DeepSeek V4 Pro, including optional preflight validation.
  • Nightly CI now includes the Kimi K2.5 test and waits for its result before sending notifications.
  • Updated runner configuration to support an additional deployment-testing runner.

[coderabbitai]

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Walkthrough

Adds Kimi K2.5 aggregation deployment resources and a reusable performance workflow. The workflow supports Kimi and DeepSeek recipes, and nightly CI invokes the Kimi smoke workflow.

Changes

Aggregated Performance Workflows

Layer / File(s)	Summary
Kimi deployment and benchmark resources .github/ci/kimi-k25-agg/*	Adds the Kustomization, deployment configuration, and benchmark Job for Kimi K2.5 aggregation.
Shared workflow setup and validation .github/workflows/shared-recipe-perf.yml	Defines workflow inputs and recipe settings, renders manifests, and performs preflight, resource ownership, cache PVC, and credential checks.
Deployment, benchmark, and result lifecycle .github/workflows/shared-recipe-perf.yml	Creates and monitors deployments and benchmark Jobs, collects and validates results, cleans up run resources, and uploads artifacts.
Nightly workflow integration and CI configuration .github/workflows/kimi-k25-nightly.yml, .github/workflows/deepseek-v4-pro-nightly.yml, .github/workflows/nightly-ci.yml, .github/actionlint.yaml, .github/filters.yaml	Adds the Kimi nightly workflow and CI job, switches DeepSeek to the shared workflow, and updates runner labels and the CI filter.

Priority: ➖ Normal

Estimated code review effort: 4 (Complex) | ~45 minutes

Merge Risk: 🔵 Low · up to 47edd

This change adds a nightly Kimi smoke test and moves DeepSeek onto a shared workflow. One small diagnostic gap remains: if copying benchmark results from the pod fails, the copy step can still report success. The later results check would then fail without showing why. The PR is mergeable, ideally after adding pipefail.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Description check	⚠️ Warning	The description provides detailed scope and validation results, but it does not follow the required template headings and omits the required Related Issues section and reviewer-start guidance.	Add the required Overview, Details, Where should the reviewer start?, and Related Issues sections. Replace "Refs OPS-8639" with the required linked-issue format, or check the no-related-issue confirmation box.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly and concisely describes the main change: adding an aggregated Kimi nightly smoke test.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check. Docstring coverage is scoped to functions touched by this diff. Analyzed 0 functions across 0…
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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Actionable comments posted: 1

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🤖 Prompt to fix review comments

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Inline comments:
Review comments at @.github/workflows/shared-recipe-perf.yml:
- Around line 230-236: Enable pipefail for the artifact-copy pipeline in the
pod-extraction step so failures from the kubectl exec tar producer propagate
instead of being masked by the local tar command.

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📥 Commits

Reviewing files that changed from the base of the PR and between 1a26bf9 and 47eddf0.

📒 Files selected for processing (9)

• .github/actionlint.yaml
• .github/ci/kimi-k25-agg/kustomization.yaml
• .github/ci/kimi-k25-agg/patch-deploy.yaml
• .github/ci/kimi-k25-agg/patch-perf.yaml
• .github/filters.yaml
• .github/workflows/deepseek-v4-pro-nightly.yml
• .github/workflows/kimi-k25-nightly.yml
• .github/workflows/nightly-ci.yml
• .github/workflows/shared-recipe-perf.yml

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[dmitry-tokarev-nv]

I approve at 90c1ed7c1c. No P0, P1, or P2 is open. One P3 is below, and it does not block the merge. You resolved the CodeRabbit thread at shared-recipe-perf.yml:236 without a change, and my measurement agrees: each run step already uses bash --noprofile --norc -e -o pipefail.

• [P3] After a failed Deploy, the Collect step now fails too, because tar exits 2. shared-recipe-perf.yml:232 copies the run folder whenever the DGD exists. If the run folder does not exist, please skip the copy.

The P3, measured offline with a control, and a tested fix.

• Nightly 36688149628 shows the case. Its DeepSeek Deploy step timed out after 105 minutes, and the frontend Pod was 1/1 Running. On main, the Collect step then passed, because FRONTEND was empty.
• I ran the Collect step of this head offline. A kubectl stub runs tar in a Dynamo runtime image as the image user (uid 1000). With a DGD, a running frontend Pod, and no run folder, the step exits 2 for both recipes: tar: /opt/models/perf/ci-deepseek-v4-pro-agg-111-1: Cannot open: No such file or directory.
• The step saves the logs, events, and resources before the copy, so nothing is lost. The cost is a second red step, and its tar error does not name the Deploy failure.
• This change fixes it. With it, the failed-Deploy case exits 0. After a finished benchmark, the step copies the same 98 DeepSeek files and 15 Kimi files, and Verify passes. Without an export, Verify still fails.

-          if [[ -n "$pod" ]]; then
+          if [[ -n "$pod" ]] && "${k[@]}" exec -c "$container" "$pod" -- test -d "$directory"; then

What I measured at this head, with no contact to a cluster.

• Render: I ran the real Configure and Render steps offline with kubectl 1.36.3 (kustomize v5.8.1). With the inputs of run 36792015798, the Kimi render is byte-identical to the six files that its Render step wrote. The DeepSeek objects equal the objects that main renders at 1a26bf9cb7, apart from the run key, the Secret names, and the new ci-workflow label. The ComputeDomain now goes in through the new prerequisites step. A merge with the current main tip 522096a8e6 has the same .github and recipe trees, so it renders the same.
• Job, Collect, and Verify: I ran the rendered Jobs as root in python:3.12-slim on a Docker volume, and Collect as the frontend user. For DeepSeek, the Job leaves no inputs.json, Collect copies 98 files, and Verify passes for 7 concurrencies, the same as main. The Kimi Verify step passes on the real export of run 36792015798. It fails on each of 8 changed trees, for example a second trace folder after a Job retry.
• Lost runs: I ran the real step scripts against a kubectl stub. After a lost run, the next run of the same recipe deletes the objects and both Secrets of the lost run. When Kimi and DeepSeek run in one nightly, neither deletes an object of the other, and each artifact holds only its own results. A same-name object or Secret without the labels of this recipe stops the run and stays. A mutant that removes each guard brings its failure back.
• Images: Docker Hub serves python:3.12-slim for linux/amd64 and the busybox digest 9db7b599… for linux/arm64. A bogus tag or digest returns manifest unknown. In ECR, the source tag of the nightly TensorRT-LLM image has the arm64 digest b9f41d7f…, which run 36792015798 deployed from ACR. I have no access to ACR.
• Wiring: the new job needs trtllm-copy-to-acr and has the run_tests condition, and notify-slack waits for it. Kimi and DeepSeek use separate concurrency groups, the same runner label, and the same pinned actions. filters.yaml and actionlint.yaml do not change. actionlint 1.7.12 reports the same 77 findings at main and at this head, apart from line numbers. It catches 3 defects that I planted in the changed files.
• CodeRabbit thread: the log of run 36792015798 shows shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} for the Collect step. I also ran it offline. If tar in the Pod fails, this step exits 2, so a failed copy does not pass.
• Coverage: run 36792015798 is a dispatch of the Kimi workflow at 23b44f07fb. It did not run through nightly-ci.yml, and no leftover existed, so the recovery path did not run. The only DeepSeek run through shared-recipe-perf.yml, run 36671581462, was preflight-only. So the first nightly after the merge is the first GPU run of DeepSeek on this workflow.