SGLang CI Workflow Orchestration Guide

This skill covers the CI infrastructure layer — how tests are dispatched, gated, and fast-failed across stages. For test authoring (templates, fixtures, registration, model selection), see the write-sglang-test skill.

Naming Conventions

• Suite: base-{a,b,c}-test-{gpu_count}-gpu-{hardware} (e.g., base-b-test-1-gpu-small)
• Test group: Directory-level registered test group under test/registered/ (e.g., hicache maps to test/registered/hicache/test_*.py)
• CI runner: {gpu_count}-gpu-{hardware} (e.g., 1-gpu-5090, 4-gpu-h100, 8-gpu-h200)

Key Files

Architecture Overview

 ┌──────────────┐
 │ build kernel │
 └──────┬───────┘
        │
        ├─ check-changes ──── detects which packages changed
        │                      (main_package, sgl_kernel, jit_kernel, multimodal_gen)
        │
        ├─ call-gate ──────── pr-gate.yml (draft? label? rate limit?)
        │
        ├─────────────────────────────────────────────────────┐
        │                                                     │
        ▼                                                     │
 ┌─────────────────────────────────────┐                      │
 │          Base A (~3 min)            │                      │
 │         pre-flight check            │                      │
 │                                     │                      │
 │  ┌─────────────────────────────┐    │                      │
 │  │ base-a-test-1-gpu-small    │    │                      │
 │  │ (small GPUs)                │    │                      │
 │  └─────────────────────────────┘    │                      │
 │  ┌─────────────────────────────┐    │                      │
 │  │ base-a-test-cpu            │    │                      │
 │  │ (CPU)                       │    │                      │
 │  └─────────────────────────────┘    │                      │
 └──────┬──────────────────────────────┘                      │
        │                                                     │
        ▼                                                     ▼
 ┌─────────────────────────────────────┐          ┌──────────────────────────┐
 │          Base B (~30 min)           │          │      kernel test         │
 │            base tests               │          └──────────────────────────┘
 │                                     │          ┌──────────────────────────┐
 │  ┌─────────────────────────────┐    │          │   multimodal gen test    │
 │  │ base-b-test-1-gpu-small    │    │          └──────────────────────────┘
 │  │ (small GPUs, e.g. 5090)     │    │
 │  └─────────────────────────────┘    │
 │  ┌─────────────────────────────┐    │
 │  │ base-b-test-1-gpu-large    │    │
 │  │ (large GPUs, e.g. H100)     │    │
 │  └─────────────────────────────┘    │
 │  ┌─────────────────────────────┐    │
 │  │ base-b-test-2-gpu-large    │    │
 │  │ (large GPUs, e.g. H100)     │    │
 │  └─────────────────────────────┘    │
 └──────┬──────────────────────────────┘
        │
        ▼
 ┌─────────────────────────────────────┐
 │          Base C (~30 min)           │
 │          advanced tests             │
 │                                     │
 │  ┌─────────────────────────────┐    │
 │  │ base-c-test-4-gpu-h100     │    │
 │  │ (H100 GPUs)                 │    │
 │  └─────────────────────────────┘    │
 │  ┌─────────────────────────────┐    │
 │  │ base-c-test-8-gpu-h200     │    │
 │  │ (8 x H200 GPUs)             │    │
 │  └─────────────────────────────┘    │
 │  ┌─────────────────────────────┐    │
 │  │ base-c-test-4-gpu-b200     │    │
 │  │ (4 x B200 GPUs)             │    │
 │  └─────────────────────────────┘    │
 │  ┌─────────────────────────────┐    │
 │  │ Other advanced tests        │    │
 │  │ (DeepEP, PD Disagg, GB300)  │    │
 │  └─────────────────────────────┘    │
 └──────┬──────────────────────────────┘
        │
        ▼
 ┌─────────────────────────────────────┐
 │         pr-test-finish              │
 │  aggregates all results, fails if   │
 │  any job failed/cancelled           │
 └─────────────────────────────────────┘

Every stage test job includes a check-pr-test-health step after checkout — if any job in the run has already failed, the job fast-fails (red X) with a root cause annotation.

Scheduled runs skip wait-for-base-* jobs, running all stages in parallel. Fast-fail is also disabled.

Fast-Fail Layers

4 layers of fast-fail, from fine to coarse:

• Layer 1: -f flag appended to all python3 -m pytest / unittest invocations in ci_utils.py
• Layer 2: --continue-on-error flag in run_suite.py — off for PRs, on for scheduled runs
• Layer 3: check-pr-test-health auto-detects schedule event and skips; filters out cascade failures to show only root cause jobs
• Layer 4: wait-for-base-* jobs are conditioned on github.event_name == 'pull_request' — skipped for scheduled runs

Execution Modes

Stage Gating (wait-for-jobs action)

wait-for-base-a and wait-for-base-b are lightweight ubuntu-latest jobs that poll the GitHub Actions API.

How it works:

1. Calls listJobsForWorkflowRun to list all jobs in the current run
2. Matches jobs by exact name or prefix (for matrix jobs, e.g., base-b-test-1-gpu-small (3))
3. If any matched job has conclusion === 'failure' → fail immediately (fast-fail)
4. If all matched jobs are completed and count matches expected_count → success
5. Otherwise → sleep poll-interval-seconds (default: 60s) and retry
6. Timeout after max-wait-minutes (240 min for base-a, 480 min for base-b)

Job specs example (base-b):

[
  {"prefix": "base-b-test-1-gpu-small", "expected_count": 8},
  {"prefix": "base-b-test-1-gpu-large", "expected_count": 14},
  {"prefix": "base-b-test-2-gpu-large", "expected_count": 4},
  {"prefix": "base-b-test-4-gpu-b200", "expected_count": 1}
]

Critical: expected_count must match the matrix size. If you add/remove matrix entries, update the wait job's spec accordingly.

PR only: Condition github.event_name == 'pull_request' && !inputs.target_stage — scheduled runs and /rerun-stage skip these entirely, allowing parallel execution.

Cross-Job Fast-Fail (check-pr-test-health action)

Composite action called after checkout in every stage test job (21 jobs total across pr-test.yml, pr-test-multimodal-gen.yml, pr-test-sgl-kernel.yml, pr-test-jit-kernel.yml).

How it works:

1. Queries listJobsForWorkflowRun for the current workflow run
2. Filters for root cause failures only — jobs with conclusion === 'failure' whose failing step is NOT check-pr-test-health (excludes cascade failures)
3. If root cause failures found → calls core.setFailed() with the list of root cause job names
4. If none → does nothing (step succeeds)

Cascade filtering: When job A fast-fails due to health check, it also has conclusion: failure. Without filtering, job B would list both the original failure AND job A's fast-fail. The filter checks each failed job's steps array — if the failing step name contains check-pr-test-health or Check PR test health, it's excluded from the root cause list.

Usage pattern:

steps:
  - name: Checkout code
    uses: actions/checkout@v4
    ...

  - uses: ./.github/actions/check-pr-test-health
    id: pr-test-health

  - name: Install dependencies        # skipped automatically if health check failed
    ...                                # (default if: success() is false)

  - name: Run test                     # also skipped
    ...

Visual effect: Job shows red X (failure) with error annotation showing root cause job names. Subsequent steps are naturally skipped (default if: success() is false after a failed step). No per-step if guards needed.

No stage filtering: Checks ALL jobs in the run, not just the current stage. Any failure anywhere triggers fast-fail.

Error message example:

Fast-fail: skipping — root cause job(s): base-b-test-1-gpu-small (0), base-b-test-1-gpu-small (1)

Within-Suite Failure Handling

Controlled by run_unittest_files() in python/sglang/test/ci/ci_utils.py.

Flags

Retry Classification

When a test fails and retry is enabled, the output is classified:

Non-retriable (checked first — real code errors): SyntaxError, ImportError, ModuleNotFoundError, NameError, TypeError, AttributeError, RuntimeError, CUDA out of memory, OOM, Segmentation fault, core dumped, ConnectionRefusedError, FileNotFoundError

Retriable (accuracy/performance): AssertionError with comparison patterns (not greater than, not less than, not equal to), accuracy, score, latency, throughput, timeout

Default: Unknown AssertionError → retriable. Other unknown failures → not retriable.

How continue_on_error is set

In pr-test.yml's check-changes job:

• schedule runs or run_all_tests flag → continue_on_error = 'true'
• PR runs → continue_on_error = 'false'

Each test job propagates via:

env:
  CONTINUE_ON_ERROR_FLAG: ${{ needs.check-changes.outputs.continue_on_error == 'true' && '--continue-on-error' || '' }}
run: |
  python3 run_suite.py --hw cuda --suite <name> $CONTINUE_ON_ERROR_FLAG

Test Partitioning

Large suites are split across matrix jobs using the LPT (Longest Processing Time) heuristic in ci_register.py:auto_partition():

1. Sort tests by est_time descending, filename as tie-breaker (deterministic)
2. Greedily assign each test to the partition with smallest cumulative time
3. Result: roughly equal total time per partition

Partition table (CUDA per-commit suites):

Suite names are generated, not hand-written: each comes from a test's register_*_ci(stage=..., runner_config=...) as {stage}-test-{runner_config}, and runner_config maps to the Runner column via scripts/ci/runner_configs.yml.

Note: Kernel suites (base-b-kernel-*) run via pr-test-jit-kernel.yml and pr-test-sgl-kernel.yml, not the main pr-test.yml. base-c-test-8-gpu-b200 is registered in test/run_suite.py but not wired to PR CI. The GB200 job is currently commented out in pr-test.yml until a company-owned runner is provisioned. Multimodal diffusion uses python/sglang/multimodal_gen/test/run_suite.py, not test/run_suite.py.

Workflow usage:

strategy:
  matrix:
    partition: [0, 1, 2, 3, 4, 5, 6, 7]
steps:
  - run: python3 run_suite.py --hw cuda --suite base-b-test-1-gpu-small \
           --auto-partition-id ${{ matrix.partition }} --auto-partition-size 8

check-changes Job

Determines which test suites to run based on file changes.

Detection Methods

Output Flags

Note: In target_stage mode, sgl_kernel is only active when include_wheel_build=true. Without that opt-in, kernel-change reruns fail validation instead of running a target stage without freshly built wheels. Outside target_stage, sgl_kernel=true switches B200 jobs from 4-gpu-b200 / 4-gpu-b200-low-disk to 4-gpu-b200-kernel / 4-gpu-b200-kernel-low-disk.

Concurrency Control

group: pr-test-{event_name}-{branch}-{pr_sha}-{stage}

cancel-in-progress: true for pull_request events (new push cancels old run), false for workflow_call.

How To: Add a New Stage Job

1. Define the job in pr-test.yml with needs: [check-changes, call-gate, wait-for-base-X, ...]
2. Copy the if: condition pattern from an existing same-stage job (handles target_stage, schedule, main_package)
3. Add checkout step
4. Add check-pr-test-health step (after checkout) — if any prior job failed, core.setFailed() fires and all subsequent steps auto-skip via default if: success()
5. Add check-maintenance step
6. Add download-artifact step if sgl_kernel changed
7. Add install dependencies step
8. Add run test step with $CONTINUE_ON_ERROR_FLAG
9. Add upload-cuda-coredumps step with if: always()
10. Register the suite name in PER_COMMIT_SUITES in test/run_suite.py
11. If using matrix, add --auto-partition-id and --auto-partition-size to the run command
12. Update wait-for-base-X job spec with the new job name and expected_count (if matrix)
13. Add the job to pr-test-finish.needs list

How To: Debug CI Failures

Slash Commands

Handled by scripts/ci/utils/slash_command_handler.py → .github/workflows/slash-command-handler.yml.

Label-gated workflow dispatch (pr-test, pr-test-extra)

pr-test.yml and pr-test-extra.yml both listen for pull_request.labeled (in addition to opened/synchronize/reopened). The check-changes.if gate has two clauses:

1. For labeled events: the just-added label must be one of the gating labels (run-ci for pr-test, run-ci or run-ci-extra for pr-test-extra) — otherwise every unrelated label addition would dispatch a full CI run.
2. All events: the PR must currently carry the required labels.

This is what lets /tag-run-ci-label (and the extra variant) trigger a fresh CI run without an extra push.

Caveat — skipped runs cannot be un-skipped by run.rerun(): GitHub's rerun API reuses the original event payload, so rerunning a pull_request-event run that was skipped because of missing labels will skip again (label set in the frozen payload doesn't update). The only way to recover a label-skipped run is to add the missing label, which fires a fresh labeled event with the current label set. handle_rerun_failed_ci in the slash handler is for rerunning failed/non-label-skipped runs; it cannot revive label-skipped ones.