제26강: AI 기반 성능 프로파일링과 최적화

실시간 성능 프로파일링 도구

// profiler/AIPerformanceProfiler.ts
import { CursorAI } from '@cursor/api';
import { performance, PerformanceObserver } from 'perf_hooks';
import * as v8 from 'v8';
import * as pprof from 'pprof';

export class AIPerformanceProfiler {
    private cursor: CursorAI;
    private metrics: Map;
    private anomalyDetector: AnomalyDetector;
    private optimizer: PerformanceOptimizer;
    private isProfilingActive: boolean = false;

    constructor() {
        this.cursor = new CursorAI();
        this.metrics = new Map();
        this.anomalyDetector = new AnomalyDetector();
        this.optimizer = new PerformanceOptimizer();
        this.setupObservers();
    }

    async startProfiling(config: ProfilingConfig): Promise {
        this.isProfilingActive = true;
        
        // CPU 프로파일링 시작
        if (config.cpu) {
            await pprof.time.start({
                durationMillis: config.duration || 60000,
                intervalMicros: 1000
            });
        }

        // 메모리 프로파일링 시작
        if (config.memory) {
            this.startMemoryProfiling();
        }

        // 네트워크 프로파일링
        if (config.network) {
            this.startNetworkProfiling();
        }

        // 실시간 분석 시작
        this.startRealtimeAnalysis();
    }

    private setupObservers() {
        // Performance Observer 설정
        const obs = new PerformanceObserver((list) => {
            for (const entry of list.getEntries()) {
                this.recordMetric(entry);
                
                // 실시간 이상 탐지
                if (this.anomalyDetector.isAnomaly(entry)) {
                    this.handleAnomaly(entry);
                }
            }
        });

        obs.observe({ 
            entryTypes: ['measure', 'function', 'mark', 'navigation', 'resource'] 
        });

        // V8 이벤트 리스너
        if (v8.setFlagsFromString) {
            v8.setFlagsFromString('--expose-gc');
        }
    }

    private async recordMetric(entry: PerformanceEntry) {
        const metric: PerformanceMetric = {
            name: entry.name,
            type: entry.entryType,
            startTime: entry.startTime,
            duration: entry.duration,
            timestamp: Date.now(),
            metadata: await this.enrichMetadata(entry)
        };

        const key = `${entry.entryType}:${entry.name}`;
        if (!this.metrics.has(key)) {
            this.metrics.set(key, []);
        }
        
        this.metrics.get(key)!.push(metric);

        // 버퍼 크기 제한
        const buffer = this.metrics.get(key)!;
        if (buffer.length > 10000) {
            buffer.shift();
        }
    }

    private async enrichMetadata(entry: PerformanceEntry): Promise {
        const metadata: any = {};

        // 스택 트레이스 수집
        if (entry.duration > 100) { // 100ms 이상 소요된 작업
            metadata.stackTrace = new Error().stack;
        }

        // 메모리 상태
        metadata.memory = process.memoryUsage();

        // CPU 사용률
        metadata.cpuUsage = process.cpuUsage();

        return metadata;
    }

    async analyzePerformance(): Promise {
        const report: PerformanceReport = {
            summary: await this.generateSummary(),
            bottlenecks: await this.identifyBottlenecks(),
            memoryLeaks: await this.detectMemoryLeaks(),
            optimizations: await this.suggestOptimizations(),
            predictions: await this.predictFutureIssues()
        };

        return report;
    }

    private async identifyBottlenecks(): Promise {
        const bottlenecks: Bottleneck[] = [];
        
        // 각 메트릭 카테고리 분석
        for (const [key, metrics] of this.metrics) {
            const analysis = await this.analyzeMetricPattern(metrics);
            
            if (analysis.isBottleneck) {
                bottlenecks.push({
                    type: analysis.type,
                    location: analysis.location,
                    impact: analysis.impact,
                    frequency: analysis.frequency,
                    suggestions: await this.generateOptimizationSuggestions(analysis)
                });
            }
        }

        // AI로 복잡한 패턴 분석
        const aiAnalysis = await this.performAIAnalysis();
        bottlenecks.push(...aiAnalysis.bottlenecks);

        return bottlenecks.sort((a, b) => b.impact - a.impact);
    }

    private async performAIAnalysis(): Promise {
        const metricsSnapshot = this.exportMetricsForAI();
        
        const prompt = `
성능 메트릭을 분석하여 병목 지점과 최적화 기회를 찾아주세요:

메트릭 데이터:
${JSON.stringify(metricsSnapshot, null, 2)}

다음을 분석해주세요:
1. 반복적인 성능 저하 패턴
2. 리소스 사용 이상 징후
3. 응답 시간 증가 추세
4. 메모리 누수 가능성
5. 비효율적인 알고리즘 사용

각 문제에 대해:
- 근본 원인
- 영향도 (1-10)
- 구체적인 해결 방안
- 예상 성능 개선율
`;

        const response = await this.cursor.ai.generateCode(prompt);
        return JSON.parse(response);
    }

    private async detectMemoryLeaks(): Promise {
        const leaks: MemoryLeak[] = [];
        
        // 힙 스냅샷 비교
        const heapSnapshots = await this.collectHeapSnapshots();
        
        for (let i = 1; i < heapSnapshots.length; i++) {
            const diff = await this.compareHeapSnapshots(
                heapSnapshots[i - 1],
                heapSnapshots[i]
            );
            
            // 지속적으로 증가하는 객체 탐지
            const growingObjects = diff.filter(obj => 
                obj.retainedSizeDiff > 0 && 
                obj.instanceCountDiff > 0
            );
            
            for (const obj of growingObjects) {
                if (this.isLikelyLeak(obj)) {
                    leaks.push({
                        className: obj.className,
                        retainedSize: obj.retainedSize,
                        instanceCount: obj.instanceCount,
                        growthRate: obj.growthRate,
                        stackTrace: await this.findAllocationStack(obj),
                        severity: this.calculateLeakSeverity(obj),
                        fix: await this.suggestLeakFix(obj)
                    });
                }
            }
        }

        return leaks;
    }

    private async suggestOptimizations(): Promise {
        const optimizations: Optimization[] = [];
        
        // 1. 함수 실행 시간 최적화
        const slowFunctions = await this.identifySlowFunctions();
        for (const func of slowFunctions) {
            const optimization = await this.optimizeFunction(func);
            if (optimization) {
                optimizations.push(optimization);
            }
        }

        // 2. 렌더링 최적화
        const renderingIssues = await this.analyzeRendering();
        optimizations.push(...renderingIssues.optimizations);

        // 3. 네트워크 최적화
        const networkOptimizations = await this.analyzeNetworkPerformance();
        optimizations.push(...networkOptimizations);

        // 4. 번들 크기 최적화
        const bundleOptimizations = await this.analyzeBundleSize();
        optimizations.push(...bundleOptimizations);

        return optimizations.sort((a, b) => b.estimatedImprovement - a.estimatedImprovement);
    }

    private async optimizeFunction(func: SlowFunction): Promise {
        const code = await this.getFunctionCode(func);
        
        const prompt = `
다음 함수의 성능을 최적화해주세요:

함수명: ${func.name}
평균 실행 시간: ${func.avgDuration}ms
호출 빈도: ${func.callCount}/분

코드:
\`\`\`javascript
${code}
\`\`\`

최적화 제안:
1. 알고리즘 개선
2. 불필요한 연산 제거
3. 캐싱 적용
4. 비동기 처리
5. 메모이제이션

최적화된 코드와 예상 개선율을 제공해주세요.
`;

        const response = await this.cursor.ai.generateCode(prompt);
        const optimization = JSON.parse(response);

        return {
            type: 'function',
            target: func.name,
            currentPerformance: func.avgDuration,
            estimatedImprovement: optimization.improvementPercentage,
            suggestion: optimization.description,
            code: optimization.optimizedCode,
            risk: optimization.risk || 'low'
        };
    }

    private async predictFutureIssues(): Promise {
        const predictions: PerformancePrediction[] = [];
        
        // 시계열 분석으로 트렌드 예측
        for (const [key, metrics] of this.metrics) {
            const trend = this.analyzeTrend(metrics);
            
            if (trend.isWorrying) {
                const prediction = await this.generatePrediction(key, trend);
                predictions.push(prediction);
            }
        }

        // ML 모델로 복잡한 패턴 예측
        const mlPredictions = await this.runMLPrediction();
        predictions.push(...mlPredictions);

        return predictions;
    }

    private analyzeTrend(metrics: PerformanceMetric[]): TrendAnalysis {
        if (metrics.length < 10) {
            return { isWorrying: false };
        }

        // 이동 평균 계산
        const windowSize = Math.min(10, Math.floor(metrics.length / 3));
        const movingAverages = [];
        
        for (let i = windowSize; i < metrics.length; i++) {
            const window = metrics.slice(i - windowSize, i);
            const avg = window.reduce((sum, m) => sum + m.duration, 0) / windowSize;
            movingAverages.push(avg);
        }

        // 트렌드 계산
        const trend = this.calculateTrendSlope(movingAverages);
        
        return {
            isWorrying: trend.slope > 0.1 && trend.r2 > 0.7,
            slope: trend.slope,
            confidence: trend.r2,
            projection: this.projectFuture(trend, movingAverages)
        };
    }

    async applyOptimization(optimization: Optimization): Promise {
        console.log(`🔧 최적화 적용 중: ${optimization.target}`);
        
        // 백업 생성
        const backup = await this.createBackup(optimization.target);
        
        try {
            // 최적화 적용
            switch (optimization.type) {
                case 'function':
                    await this.applyFunctionOptimization(optimization);
                    break;
                case 'query':
                    await this.applyQueryOptimization(optimization);
                    break;
                case 'rendering':
                    await this.applyRenderingOptimization(optimization);
                    break;
                case 'caching':
                    await this.applyCachingStrategy(optimization);
                    break;
            }

            // 성능 검증
            const validation = await this.validateOptimization(optimization);
            
            if (validation.improved) {
                return {
                    success: true,
                    actualImprovement: validation.improvementPercentage,
                    message: `성능이 ${validation.improvementPercentage}% 개선되었습니다.`
                };
            } else {
                // 롤백
                await this.rollback(backup);
                return {
                    success: false,
                    message: '성능 개선이 확인되지 않아 롤백했습니다.'
                };
            }
        } catch (error) {
            await this.rollback(backup);
            throw error;
        }
    }
}

// 실시간 성능 모니터링 대시보드
export class PerformanceDashboard {
    private profiler: AIPerformanceProfiler;
    private websocket: WebSocket;
    private charts: Map;

    constructor() {
        this.profiler = new AIPerformanceProfiler();
        this.charts = new Map();
        this.setupRealtimeUpdates();
    }

    private setupRealtimeUpdates() {
        // 실시간 메트릭 스트리밍
        setInterval(async () => {
            const metrics = await this.profiler.getCurrentMetrics();
            this.updateCharts(metrics);
            this.broadcastMetrics(metrics);
        }, 1000);

        // AI 분석 주기적 실행
        setInterval(async () => {
            const analysis = await this.profiler.analyzePerformance();
            this.updateAnalysis(analysis);
        }, 30000); // 30초마다
    }

    private updateCharts(metrics: RealtimeMetrics) {
        // CPU 사용률 차트 업데이트
        this.updateChart('cpu', {
            timestamp: Date.now(),
            value: metrics.cpu.usage,
            threshold: 80
        });

        // 메모리 사용량 차트
        this.updateChart('memory', {
            timestamp: Date.now(),
            value: metrics.memory.heapUsed / metrics.memory.heapTotal * 100,
            threshold: 90
        });

        // 응답 시간 차트
        this.updateChart('responseTime', {
            timestamp: Date.now(),
            value: metrics.responseTime.p95,
            threshold: metrics.responseTime.sla
        });

        // 처리량 차트
        this.updateChart('throughput', {
            timestamp: Date.now(),
            value: metrics.throughput.requestsPerSecond
        });
    }

    async generatePerformanceReport(): Promise {
        const analysis = await this.profiler.analyzePerformance();
        
        return `
# 성능 분석 보고서

## 요약
- 전체 성능 점수: ${analysis.summary.overallScore}/100
- 주요 병목 지점: ${analysis.bottlenecks.length}개
- 메모리 누수 의심: ${analysis.memoryLeaks.length}개
- 최적화 제안: ${analysis.optimizations.length}개

## 상세 분석

### 1. 병목 지점
${analysis.bottlenecks.map(b => `
#### ${b.type} - ${b.location}
- 영향도: ${b.impact}/10
- 발생 빈도: ${b.frequency}회/분
- 권장 조치: ${b.suggestions.join(', ')}
`).join('\n')}

### 2. 메모리 분석
${analysis.memoryLeaks.map(leak => `
#### ${leak.className}
- 누수 크기: ${formatBytes(leak.retainedSize)}
- 인스턴스 수: ${leak.instanceCount}
- 심각도: ${leak.severity}
- 해결 방안: ${leak.fix}
`).join('\n')}

### 3. 최적화 제안
${analysis.optimizations.map(opt => `
#### ${opt.target}
- 예상 개선율: ${opt.estimatedImprovement}%
- 위험도: ${opt.risk}
- 구현 방법:
\`\`\`javascript
${opt.code}
\`\`\`
`).join('\n')}

### 4. 향후 예측
${analysis.predictions.map(pred => `
- ${pred.metric}: ${pred.timeframe}내 ${pred.prediction}
  - 신뢰도: ${pred.confidence}%
  - 권장 조치: ${pred.recommendation}
`).join('\n')}
`;
    }
}

// 성능 최적화 자동화
export class AutoPerformanceOptimizer {
    private profiler: AIPerformanceProfiler;
    private config: OptimizerConfig;
    private optimizationHistory: OptimizationHistory[];

    constructor(config: OptimizerConfig) {
        this.profiler = new AIPerformanceProfiler();
        this.config = config;
        this.optimizationHistory = [];
    }

    async startAutoOptimization(): Promise {
        console.log('🤖 자동 성능 최적화 시작...');
        
        // 지속적인 모니터링 및 최적화
        setInterval(async () => {
            await this.optimizationCycle();
        }, this.config.interval || 300000); // 5분마다
    }

    private async optimizationCycle(): Promise {
        // 1. 성능 분석
        const analysis = await this.profiler.analyzePerformance();
        
        // 2. 최적화 대상 선정
        const targets = this.selectOptimizationTargets(analysis);
        
        // 3. 각 대상에 대해 최적화 수행
        for (const target of targets) {
            try {
                const result = await this.optimizeTarget(target);
                
                this.optimizationHistory.push({
                    timestamp: new Date(),
                    target: target.name,
                    result,
                    improvement: result.actualImprovement
                });
                
                // 성공적인 최적화 학습
                if (result.success) {
                    await this.learnFromSuccess(target, result);
                }
            } catch (error) {
                console.error(`최적화 실패: ${target.name}`, error);
            }
        }
        
        // 4. 보고서 생성
        await this.generateOptimizationReport();
    }

    private selectOptimizationTargets(analysis: PerformanceReport): OptimizationTarget[] {
        const targets: OptimizationTarget[] = [];
        
        // 자동 최적화 가능한 항목 필터링
        const autoOptimizable = analysis.optimizations.filter(opt => 
            opt.risk === 'low' && 
            opt.estimatedImprovement > this.config.minImprovement
        );
        
        // 우선순위 정렬
        return autoOptimizable
            .sort((a, b) => b.estimatedImprovement - a.estimatedImprovement)
            .slice(0, this.config.maxConcurrent || 3)
            .map(opt => ({
                name: opt.target,
                type: opt.type,
                optimization: opt
            }));
    }

    private async optimizeTarget(target: OptimizationTarget): Promise {
        console.log(`🎯 최적화 대상: ${target.name}`);
        
        // 사전 성능 측정
        const beforeMetrics = await this.measurePerformance(target);
        
        // 최적화 적용
        await this.profiler.applyOptimization(target.optimization);
        
        // 안정화 대기
        await this.waitForStabilization();
        
        // 사후 성능 측정
        const afterMetrics = await this.measurePerformance(target);
        
        // 개선율 계산
        const improvement = this.calculateImprovement(beforeMetrics, afterMetrics);
        
        return {
            success: improvement > 0,
            actualImprovement: improvement,
            beforeMetrics,
            afterMetrics
        };
    }

    private async learnFromSuccess(
        target: OptimizationTarget, 
        result: OptimizationResult
    ): Promise {
        // 성공적인 최적화 패턴 학습
        const pattern = {
            targetType: target.type,
            optimization: target.optimization,
            actualImprovement: result.actualImprovement,
            context: await this.captureContext()
        };
        
        // AI 모델 업데이트
        await this.updateOptimizationModel(pattern);
    }

    private async generateOptimizationReport(): Promise {
        const report = {
            period: {
                from: this.optimizationHistory[0]?.timestamp || new Date(),
                to: new Date()
            },
            totalOptimizations: this.optimizationHistory.length,
            successfulOptimizations: this.optimizationHistory.filter(h => h.result.success).length,
            totalImprovement: this.optimizationHistory.reduce((sum, h) => 
                sum + (h.improvement || 0), 0
            ),
            topOptimizations: this.optimizationHistory
                .sort((a, b) => (b.improvement || 0) - (a.improvement || 0))
                .slice(0, 5)
        };
        
        // 보고서 저장 및 알림
        await this.saveReport(report);
        await this.notifyStakeholders(report);
    }
}