sglang-prod-incident-triage

Replay live SGLang serving faults into reproducible debug paths.

Updated Jun 4, 2026
One-click install
npx skills add https://github.com/annealing-inversion/sglang-kimi-deferral --skill sglang-prod-incident-triage-annealing-inversion
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sglang-prod-incident-triage
Source: https://github.com/annealing-inversion/sglang-kimi-deferral/tree/main/.claude/skills/sglang-prod-incident-triage
Command: npx skills add https://github.com/annealing-inversion/sglang-kimi-deferral --skill sglang-prod-incident-triage-annealing-inversion

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Replay-first debug flow to convert live SGLang serving problems into reproducible debugging pathways, enabling rapid diagnosis and containment.

Core Features & Use Cases

  • Replay-first incident triage workflow: collect a baseline bundle, capture failing request or crash dump, replay on a clean target, and progress tool-switching as the issue narrows.
  • Examples and guidance to drive decisions about which focused tools to use next.
  • Works with /health, /health_generate, /v1/loads, /metrics, and crash dumps.

Quick Start

Collect a baseline bundle from the live server, save the failing request or crash dump, and replay on a clean target before applying deeper diagnostics.

Frequently Asked Questions about sglang-prod-incident-triage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I debug SGLang serving issues like queue growth and latency regressions?

Debug SGLang serving issues by collecting a baseline bundle, saving the failing request or crash dump, replaying it on a clean target, and switching to focused diagnostic tools as the problem narrows.

What is replay-first incident triage for production LLM serving?

Replay-first incident triage converts live serving faults into reproducible debug paths. It enforces a structured workflow: capture a baseline bundle, save the failing request, replay on a clean target, and apply deeper diagnostics.

Which SGLang endpoints and artifacts do I need to collect for an incident baseline?

Collect baseline data from SGLang endpoints including /health, /health_generate, /v1/loads, /metrics, along with any crash dumps, to establish a baseline bundle for reproducing the serving issue.

Does this incident triage workflow work with distributed serving stalls and timeouts?

Yes, the incident triage workflow applies to distributed stalls, timeouts, throughput regressions, and crash dumps. It guides you from baseline collection to replay and focused tool-switching to isolate the root cause.

What's the best way to reproduce a live SGLang crash dump for debugging?

The best way to reproduce an SGLang crash dump is to save the failing request from the live server, isolate it, and replay the request on a clean target environment before applying deeper diagnostic tools.

Why does my SGLang production server experience health-check failures after a deployment?

Health-check failures require a structured triage workflow. Collect a baseline bundle from the live server, capture the failing request, replay it on a clean target, and switch to appropriate debugging tools to diagnose the regression.