[ci feature] add ci monitor (#10872)
This commit is contained in:
Xiaoyu Zhang
389
scripts/ci_monitor/ci_analyzer.py
Executable file
389
scripts/ci_monitor/ci_analyzer.py
Executable file
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#!/usr/bin/env python3
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"""
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SGLang CI Analyzer
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Simple tool to analyze CI failures for SGLang project
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"""
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import argparse
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import json
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import os
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import sys
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import time
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from collections import Counter, defaultdict
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from datetime import datetime
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from typing import Dict, List
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import requests
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class SGLangCIAnalyzer:
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"""SGLang CI Analyzer"""
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def __init__(self, token: str):
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self.token = token
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self.base_url = "https://api.github.com"
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self.repo = "sgl-project/sglang"
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self.headers = {
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"Authorization": f"token {token}",
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"Accept": "application/vnd.github.v3+json",
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"User-Agent": "SGLang-CI-Analyzer/1.0",
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}
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self.session = requests.Session()
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self.session.headers.update(self.headers)
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def get_recent_runs(self, limit: int = 100) -> List[Dict]:
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"""Get recent CI run data"""
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print(f"Fetching {limit} recent CI runs...")
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all_runs = []
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page = 1
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per_page = 100
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while len(all_runs) < limit:
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url = f"{self.base_url}/repos/{self.repo}/actions/runs"
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params = {"per_page": min(per_page, limit - len(all_runs)), "page": page}
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try:
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response = self.session.get(url, params=params)
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response.raise_for_status()
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data = response.json()
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if not data.get("workflow_runs"):
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break
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all_runs.extend(data["workflow_runs"])
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print(f"Fetched {len(all_runs)} runs so far...")
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if len(data["workflow_runs"]) < per_page:
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break
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page += 1
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time.sleep(0.1) # Avoid API rate limits
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except requests.exceptions.RequestException as e:
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print(f"Error fetching CI data: {e}")
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break
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return all_runs[:limit]
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def analyze_ci_failures(self, runs: List[Dict]) -> Dict:
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"""Analyze CI failure patterns"""
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print("Analyzing CI failure data...")
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# SGLang specific job categories
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job_categories = {
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"sgl-kernel": [
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"sgl-kernel-build-wheels",
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"sgl-kernel-unit-test",
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"sgl-kernel-mla-test",
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],
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"unit-test": [
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"unit-test-frontend",
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"unit-test-backend-1-gpu",
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"unit-test-backend-2-gpu",
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"unit-test-backend-4-gpu",
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"unit-test-backend-8-gpu",
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],
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"performance": [
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"performance-test-1-gpu-part-1",
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"performance-test-1-gpu-part-2",
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"performance-test-2-gpu",
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],
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"accuracy": ["accuracy-test-1-gpu", "accuracy-test-2-gpu"],
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"deepep": ["unit-test-deepep-4-gpu", "unit-test-deepep-8-gpu"],
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"b200": ["unit-test-backend-4-gpu-b200"],
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}
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stats = {
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"total_runs": len(runs),
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"failed_runs": 0,
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"successful_runs": 0,
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"cancelled_runs": 0,
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"skipped_runs": 0,
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"category_failures": defaultdict(int),
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"job_failures": defaultdict(int),
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"failure_patterns": defaultdict(int),
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"job_failure_links": defaultdict(
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list
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), # Store recent failure links for each job
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"job_last_success": {}, # Store last successful run for each job
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}
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total_runs = len(runs)
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for i, run in enumerate(runs, 1):
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# Show progress every 10% or every 50 runs, whichever is smaller
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if i % max(1, min(50, total_runs // 10)) == 0 or i == total_runs:
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progress = (i / total_runs) * 100
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print(f"Progress: {i}/{total_runs} ({progress:.1f}%)")
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run_status = run.get("conclusion", "unknown")
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workflow_name = run.get("name", "Unknown")
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run_id = run.get("id")
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run_number = run.get("run_number")
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created_at = run.get("created_at")
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# Count run status
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if run_status == "failure":
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stats["failed_runs"] += 1
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elif run_status == "success":
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stats["successful_runs"] += 1
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elif run_status == "cancelled":
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stats["cancelled_runs"] += 1
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elif run_status == "skipped":
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stats["skipped_runs"] += 1
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# Get detailed job information for all runs
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jobs = self._get_job_details(run_id)
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run_url = f"https://github.com/{self.repo}/actions/runs/{run_id}"
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pr_info = self._get_pr_info(run)
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for job in jobs:
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job_name = job.get("name", "Unknown")
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job_conclusion = job.get("conclusion", "unknown")
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# Filter out non-specific CI jobs
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if job_name not in [
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"check-changes",
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"pr-test-finish",
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"pr-test-h20-finish",
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"lint",
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]:
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# Record successful jobs (update last success)
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if job_conclusion == "success":
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stats["job_last_success"][job_name] = {
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"url": run_url,
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"run_number": run_number,
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"created_at": created_at,
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"pr_info": pr_info,
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}
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# Record failed jobs
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elif job_conclusion == "failure" and run_status == "failure":
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stats["job_failures"][job_name] += 1
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# Store failure link (keep only last 3 for each job)
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if len(stats["job_failure_links"][job_name]) < 3:
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stats["job_failure_links"][job_name].append(
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{
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"url": run_url,
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"run_number": run_number,
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"created_at": created_at,
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"pr_info": pr_info,
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}
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)
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# Categorize failed jobs
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for category, jobs_list in job_categories.items():
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if any(
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job_pattern in job_name for job_pattern in jobs_list
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):
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stats["category_failures"][category] += 1
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break
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# Analyze failure patterns
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self._analyze_failure_pattern(job, stats)
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time.sleep(0.1) # Avoid API rate limits
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return stats
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def _get_job_details(self, run_id: int) -> List[Dict]:
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"""Get job details for a specific run"""
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url = f"{self.base_url}/repos/{self.repo}/actions/runs/{run_id}/jobs"
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try:
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response = self.session.get(url)
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response.raise_for_status()
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return response.json().get("jobs", [])
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except:
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return []
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def _get_pr_info(self, run: Dict) -> Dict:
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"""Get PR information from a run"""
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pr_info = {
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"pr_number": None,
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"author": run.get("head_commit", {})
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.get("author", {})
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.get("name", "Unknown"),
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"head_sha": run.get("head_sha", ""),
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"head_branch": run.get("head_branch", ""),
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}
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# Try to extract PR number from pull_requests
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pull_requests = run.get("pull_requests", [])
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if pull_requests:
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pr_info["pr_number"] = pull_requests[0].get("number")
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return pr_info
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def _analyze_failure_pattern(self, job: Dict, stats: Dict):
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"""Analyze failure patterns"""
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job_name = job.get("name", "")
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steps = job.get("steps", [])
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for step in steps:
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if step.get("conclusion") == "failure":
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step_name = step.get("name", "")
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# SGLang specific failure pattern recognition
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if "timeout" in step_name.lower():
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stats["failure_patterns"]["Timeout"] += 1
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elif "test" in step_name.lower() and "unit" in job_name.lower():
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stats["failure_patterns"]["Unit Test Failure"] += 1
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elif "performance" in job_name.lower():
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stats["failure_patterns"]["Performance Test Failure"] += 1
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elif "accuracy" in job_name.lower():
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stats["failure_patterns"]["Accuracy Test Failure"] += 1
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elif "build" in step_name.lower():
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stats["failure_patterns"]["Build Failure"] += 1
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elif "install" in step_name.lower():
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stats["failure_patterns"]["Dependency Installation Failure"] += 1
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elif "gpu" in job_name.lower():
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stats["failure_patterns"]["GPU Related Failure"] += 1
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else:
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stats["failure_patterns"]["Other"] += 1
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def generate_report(self, stats: Dict):
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"""Generate CI analysis report"""
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print("\n" + "=" * 60)
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print("SGLang CI Analysis Report")
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print("=" * 60)
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# Overall statistics
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total = stats["total_runs"]
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failed = stats["failed_runs"]
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success = stats["successful_runs"]
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cancelled = stats["cancelled_runs"]
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skipped = stats["skipped_runs"]
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success_rate = (success / total * 100) if total > 0 else 0
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print(f"\nOverall Statistics:")
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print(f" Total runs: {total}")
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print(f" Successful: {success}")
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print(f" Failed: {failed}")
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print(f" Cancelled: {cancelled}")
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print(f" Skipped: {skipped}")
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print(f" Success rate: {success_rate:.1f}%")
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# Category failure statistics
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if stats["category_failures"]:
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print(f"\nCategory Failure Statistics:")
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for category, count in sorted(
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stats["category_failures"].items(), key=lambda x: x[1], reverse=True
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):
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print(f" {category}: {count} failures")
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# Most frequently failed jobs with links
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if stats["job_failures"]:
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print(f"\nMost Frequently Failed Jobs (Top 50):")
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for i, (job, count) in enumerate(
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sorted(stats["job_failures"].items(), key=lambda x: x[1], reverse=True)[
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:50
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],
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1,
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):
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print(f" {i:2d}. {job}: {count} times")
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# Show last successful run
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if job in stats["job_last_success"]:
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last_success = stats["job_last_success"][job]
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success_date = datetime.fromisoformat(
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last_success["created_at"].replace("Z", "+00:00")
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)
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pr_info = last_success["pr_info"]
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pr_text = ""
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if pr_info["pr_number"]:
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pr_text = (
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f" (PR #{pr_info['pr_number']} by {pr_info['author']})"
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)
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else:
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pr_text = f" by {pr_info['author']}"
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print(
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f" Last Success: Run #{last_success['run_number']} ({success_date.strftime('%Y-%m-%d %H:%M')}){pr_text}: {last_success['url']}"
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)
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# Show recent failure links
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if (
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job in stats["job_failure_links"]
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and stats["job_failure_links"][job]
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):
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print(" Recent Failures:")
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for link_info in stats["job_failure_links"][job]:
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created_at = datetime.fromisoformat(
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link_info["created_at"].replace("Z", "+00:00")
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)
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# Format PR info for failures
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pr_info = link_info.get("pr_info", {})
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pr_text = ""
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if pr_info.get("pr_number"):
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pr_text = f" (PR #{pr_info['pr_number']} by {pr_info.get('author', 'Unknown')})"
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else:
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pr_text = f" by {pr_info.get('author', 'Unknown')}"
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print(
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f" - Run #{link_info['run_number']} ({created_at.strftime('%Y-%m-%d %H:%M')}){pr_text}: {link_info['url']}"
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)
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# Failure pattern analysis
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if stats["failure_patterns"]:
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print(f"\nFailure Pattern Analysis:")
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for pattern, count in sorted(
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stats["failure_patterns"].items(), key=lambda x: x[1], reverse=True
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):
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print(f" {pattern}: {count} times")
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print("\n" + "=" * 60)
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def save_detailed_report(self, stats: Dict, output_file: str = "ci_analysis.json"):
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"""Save detailed report to file"""
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with open(output_file, "w", encoding="utf-8") as f:
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json.dump(stats, f, ensure_ascii=False, indent=2)
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print(f"\nDetailed report saved to: {output_file}")
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def main():
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parser = argparse.ArgumentParser(description="SGLang CI Analyzer")
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parser.add_argument("--token", required=True, help="GitHub Personal Access Token")
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parser.add_argument(
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"--limit",
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type=int,
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default=100,
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help="Number of runs to analyze (default: 100)",
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)
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parser.add_argument(
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"--output",
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default="ci_analysis.json",
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help="Output file (default: ci_analysis.json)",
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)
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args = parser.parse_args()
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# Create analyzer
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analyzer = SGLangCIAnalyzer(args.token)
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try:
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# Get CI run data
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runs = analyzer.get_recent_runs(args.limit)
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if not runs:
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print("No CI run data found")
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return
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# Analyze failures
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stats = analyzer.analyze_ci_failures(runs)
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# Generate report
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analyzer.generate_report(stats)
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# Save detailed report
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analyzer.save_detailed_report(stats, args.output)
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except Exception as e:
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print(f"Error during analysis: {e}")
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sys.exit(1)
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if __name__ == "__main__":
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main()
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