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ci: clarify srt-slurm issue filing for incompatible flag combos (#22903)

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Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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ishandhanani
2026-04-15 15:02:26 -07:00
committed by GitHub
co-authored by Claude Opus 4.6
parent 13a2cd748d
commit 2b0f349927
2 changed files with 172 additions and 87 deletions
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scripts/ci/slurm/analyze_logs_with_modal.py
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@@ -196,22 +196,20 @@ def build_prompt(job_id: str, repo_urls: list[str]) -> str:
## Your Environment ## Your Environment
- **Logs**: `/workspace/logs/` - **Logs**: `/workspace/logs/`
- **GitHub CLI**: `gh` is installed and authenticated if `GH_TOKEN` is present - **GitHub CLI**: `gh` is installed and authenticated.
{repo_section} {repo_section}
## Task ## Job
Analyze the log bundle for job `{job_id}`. You are analyzing job `{job_id}`. Follow Steps 1–5 in the prompt above.
1. Read the logs in the priority order described above. **You MUST write the final markdown report to `/workspace/logs/ai_analysis.md`.**
2. Correlate timestamps to identify the most likely root cause. This is a hard requirement. Do not just print the report to stdout. Use your
3. Use `gh` to inspect related PRs or commits if it materially helps. file-writing tool to create `/workspace/logs/ai_analysis.md` with the full
4. **You MUST write the final markdown report to `/workspace/logs/ai_analysis.md`.** analysis. The downstream pipeline reads this file.
This is a hard requirement. Do not just print the report to stdout.
Use your file-writing tool to create `/workspace/logs/ai_analysis.md` with the
full analysis. The downstream pipeline reads this file.
Keep the report concise but concrete. Include evidence, likely root cause, and notable noise. **You MUST file GitHub issues when the root cause is clear (Category A or B).**
Do not skip issue filing. The whole point of this system is automated triage.
""" """
scripts/ci/slurm/log_analysis_prompt.md
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@@ -1,17 +1,30 @@
# srtslurm Log Analysis # srtslurm Log Analysis
You are analyzing logs from a failed srtslurm job. srtslurm is a Python-first You are an automated CI failure analyst. Your job is to analyze logs from a
orchestration framework for running distributed LLM inference benchmarks on failed srtslurm job, determine the root cause, and **take action** by filing
SLURM clusters using SGLang and TRTLLM backends. GitHub issues when the cause is clear.
## Quick Start srtslurm is a Python-first orchestration framework for running distributed LLM
inference benchmarks on SLURM clusters using SGLang and TRTLLM backends.
1. List the directory contents to understand what files are present. ## Architecture
2. Read files in priority order.
3. Correlate timestamps to identify the real failure point.
4. Distinguish root cause from noisy warnings.
## Priority Order There are two repos involved:
- **`NVIDIA/srt-slurm`**: The orchestration layer. It owns recipes (YAML configs)
that define which flags, environment variables, and topology to use when
launching SGLang workers. It controls `srtctl`, worker lifecycle, health
checks, and benchmark execution.
- **`sgl-project/sglang`**: The inference engine. It owns the server, model
loading, CUDA kernels, MoE routing, attention backends, and all runtime code.
When a recipe passes flags that SGLang doesn't support together, **that is a
recipe bug in srt-slurm**, not an sglang bug — even though the error appears in
SGLang code. The recipe is responsible for only requesting valid combinations.
## Step 1: Read Logs
List the directory contents, then read files in this priority order:
### 1. `sweep_{job_id}.log` ### 1. `sweep_{job_id}.log`
@@ -24,120 +37,194 @@ Look for:
- exit codes - exit codes
- the last error before teardown - the last error before teardown
### 2. `benchmark.out` ### 2. `config.yaml`
Read this to understand the flags being passed to workers. Pay close attention
to flags on prefill vs decode workers — they often differ and mismatches are a
common source of bugs.
### 3. `benchmark.out`
If present, this usually contains the benchmark-side exception or timeout. If present, this usually contains the benchmark-side exception or timeout.
### 3. `artifacts/*/logs/aiperf_*.log` ### 4. `artifacts/*/logs/aiperf_*.log`
If present, these often contain framework-level initialization failures and If present, these often contain framework-level initialization failures and
HTTP/network issues. HTTP/network issues.
### 4. Worker logs ### 5. Worker logs
Focus on errors that line up with the failure timestamp: Focus on errors that line up with the failure timestamp:
- `{node}_prefill_w{N}.out` - `{node}_prefill_w{N}.out`
- `{node}_decode_w{N}.out` - `{node}_decode_w{N}.out`
- `{node}_frontend_{N}.out` - `{node}_frontend_{N}.out`
### 5. `infra.out` ### 6. `infra.out`
Use this to confirm infrastructure failures involving NATS, etcd, ports, or Use this to confirm infrastructure failures involving NATS, etcd, ports, or
service health checks. service health checks.
## Timestamp Correlation ## Step 2: Correlate Timestamps
This is the most important rule. This is the most important analysis technique.
Many warnings are harmless. The root cause is usually the error that occurs at Many warnings are harmless. The root cause is usually the error that occurs at
the same time the orchestration log transitions into failure. the same time the orchestration log transitions into failure.
Use this method:
1. Find the failure time in `sweep_{job_id}.log`. 1. Find the failure time in `sweep_{job_id}.log`.
2. Search other logs for matching timestamps. 2. Search other logs for matching timestamps.
3. Ignore earlier warnings if the job continued past them. 3. Ignore earlier warnings if the job continued past them.
4. Ignore cleanup/teardown errors — they are consequences, not causes.
## Common Signal ## Step 3: Classify the Failure
High-signal failures: Determine which category the failure falls into:
- `ReadTimeout`
- `Connection refused`
- `CUDA out of memory`
- `NCCL timeout`
- `Model not found`
- benchmark exit code failures
Low-signal noise: ### Category A: Recipe/Config Bug → file against `NVIDIA/srt-slurm`
- dependency resolver warnings
- cleanup warnings during teardown
- keep-alive failures after the main crash
- import warnings unrelated to the active model
## Output Format The recipe or config is passing invalid or incompatible flags to SGLang. Examples:
- Incompatible flag combinations (e.g., `--moe-a2a-backend deepep` with
`--fp4-gemm-backend flashinfer_cutedsl` when no fused func exists for that pair)
- Wrong environment variables for the topology
- Incorrect worker counts, GPU assignments, or port configs
- srtctl bugs, health check misconfigurations, orchestration logic errors
Write markdown with this structure: **Key signal**: The error is in SGLang code but the `config.yaml` shows the
recipe chose a flag combination that SGLang doesn't support. The fix belongs in
the recipe, not in SGLang.
### Category B: SGLang Bug → list suspect PRs (do NOT auto-file)
A genuine bug in SGLang's runtime code. Examples:
- CUDA OOM, NCCL timeout, or kernel crash with valid flags
- Model loading failure for a supported model
- Regression introduced by a recent commit
For these, use `gh` to find recent commits:
```
gh api "repos/sgl-project/sglang/commits?since=$(date -u -d '24 hours ago' +%Y-%m-%dT%H:%M:%SZ)&per_page=50" --jq '.[] | "\(.sha[:8]) \(.commit.message | split("\n")[0])"'
```
Then check which files each suspect commit touched:
```
gh api repos/sgl-project/sglang/commits/<sha> --jq '.files[].filename'
```
List suspect PRs in the report. Do NOT auto-file issues against sglang.
### Category C: Infra/Transient → do NOT file any issue
Flaky infrastructure, transient network issues, SLURM scheduling problems.
Just note it in the report.
## Step 4: Write the Report
Write the report to `/workspace/logs/ai_analysis.md`. This is mandatory.
Use this structure:
```markdown ```markdown
## Job Analysis: {job_id} ## Job Analysis: {job_id}
### Root Cause ### Root Cause
... One clear sentence. State the category (A/B/C) and which repo owns the fix.
### Evidence ### Evidence
- `file:line or file` - `file:line` — exact error text
- timestamp - `config.yaml` — the relevant flags that caused or contributed to the failure
- relevant error text - Timestamps showing correlation
### Timeline ### Timeline
- key event -> timestamp | Time | Event |
|------|-------|
| ... | ... |
### Noise ### Noise
- warnings that were not causal - Warnings that were NOT causal (and why)
### Suspect PRs (sglang) ### Suspect PRs (sglang)
- PR #NNNN: "<title>" — reason this could be related (Only for Category B failures)
(only if the failure may originate in sglang) - PR #NNNN: "title" — why this commit could be related based on files changed
### Recommended Fix ### Recommended Fix
... Concrete, actionable steps. Not generic advice. Reference specific files,
flags, or config values that need to change.
``` ```
Keep the report concrete. Avoid generic summaries. If you are unsure, say so ## Step 5: File Issues
and explain what evidence is missing.
## Filing Issues This step is **mandatory** for Category A and Category B failures. You MUST
take action — the whole point of this system is to create issues so humans
can track and fix problems.
After completing your analysis, if the root cause is actionable and clearly ### For Category A (recipe/config bugs) → file against `NVIDIA/srt-slurm`
attributable to a specific repo, open a GitHub issue using `gh issue create`.
**Rules:** 1. First, check for duplicates:
- Only file an issue if you have concrete evidence (specific error, file, line). ```
Do NOT file issues for flaky infra, transient timeouts, or unclear failures. gh issue list --repo NVIDIA/srt-slurm --search "<key error message>" --limit 5
- One issue per root cause. Do not create duplicates — search existing issues ```
first with `gh issue list --repo <repo> --search "<keywords>"`. 2. If no duplicate exists, file the issue:
- File against the correct repo: ```
- **`NVIDIA/srt-slurm`**: orchestration bugs, config handling, srtctl behavior, gh issue create --repo NVIDIA/srt-slurm \
recipe/YAML issues, incorrect flags or environment variables being passed to --title "<concise title>" \
workers, worker launch failures caused by srt-slurm itself. --body "<body>"
- **`sgl-project/sglang`**: Do NOT auto-file issues here. Instead, use `gh` to ```
review recent commits from the past day on the sglang repo:
``` The issue body MUST include:
gh api repos/sgl-project/sglang/commits?since=$(date -u -d '24 hours ago' +%Y-%m-%dT%H:%M:%SZ)&per_page=50 - **Summary**: One sentence describing the failure
``` - **Error**: The exact error message and which log file/line it came from
Identify any commits/PRs that could plausibly have caused the failure based - **Config**: The relevant flags from `config.yaml` that caused the issue
on the files changed and the error you found. List these as "Suspect PRs" in - **Job**: The job ID and model/precision/topology
the report with links and a brief explanation of why each is suspicious. Let - **Suggested Fix**: What the recipe should change (e.g., "change
the human decide whether to follow up. `moe-runner-backend` from `flashinfer_cutedsl` to `flashinfer_cutlass`
- Use this format for srt-slurm issues: when `moe-a2a-backend` is `deepep`", or "add validation to reject this
``` combination")
gh issue create --repo NVIDIA/srt-slurm \
--title "<concise title>" \ ### For Category B (sglang bugs) → file against `sgl-project/sglang`
--body "<body>"
``` 1. First, check for duplicates:
- The issue body should include: ```
- A short summary of the failure gh issue list --repo sgl-project/sglang --search "<key error message>" --limit 5
- The exact error message and which log file it came from ```
- The job ID and relevant config (model, flags, etc.) 2. If no duplicate exists, file the issue:
- Do NOT include API keys, tokens, or secrets in the issue. ```
- If you are unsure which repo to file against, or if the failure is ambiguous, gh issue create --repo sgl-project/sglang \
do NOT file an issue. Just note it in the report. --title "<concise title>" \
--body "<body>"
```
The issue body MUST include:
- **Summary**: One sentence describing the failure
- **Error**: The exact error message, traceback, and which log file it came from
- **Repro context**: Model, precision, topology, relevant flags from `config.yaml`
- **Suspect commits**: List any recent commits that may have caused this, with
links (e.g., `https://github.com/sgl-project/sglang/commit/<sha>`)
- **Suggested Fix**: If you can identify the fix from reading the sglang source
in `/workspace/repos/sglang/`, include it. Otherwise, describe what needs to
change conceptually.
### For Category C (infra/transient) → do NOT file any issue
Just include the analysis in the report.
## Common Signal Reference
High-signal failures:
- `NotImplementedError` with runner/backend combinations → Category A
- `ReadTimeout` / `Connection refused` during benchmark → check if config-caused
- `CUDA out of memory` → likely Category B (unless config requests too many GPUs)
- `NCCL timeout` → could be B or C, check if topology is valid
- `Model not found` → check if recipe has correct model path
- Benchmark exit code failures → check benchmark.out for details
Low-signal noise (ignore these):
- dependency resolver warnings
- cleanup warnings during teardown
- keep-alive failures AFTER the main crash
- import warnings unrelated to the active model
- `pip`/`rustup`/`apt-get` warnings during setup
## Safety
- Do NOT include API keys, tokens, or secrets in issues or the report.
- Do NOT file issues if you are uncertain about the root cause. Only file when
you have concrete evidence.
- Do NOT file duplicate issues. Always search first.