Scaling After Launch

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async function callAIWithBackoff<T>(
  fn: () => Promise<T>,
  maxRetries: number = 5,
  baseDelay: number = 1000
): Promise<T> {
  let lastError: Error;
  
  for (let attempt = 0; attempt < maxRetries; attempt++) {
    try {
      return await fn();
    } catch (error) {
      lastError = error as Error;

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class TokenAwareRateLimiter {
  private requestWindow: Map<string, number[]> = new Map();
  private tokenWindow: Map<string, number[]> = new Map();
  
  constructor(
    private maxRequestsPerMinute: number = 500,
    private maxTokensPerMinute: number = 150000,
    private windowMs: number = 60000
  ) {}

  async canProceed(key: string, estimatedTokens: number): Promise<{
    allowed: boolean;

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import Redis from 'ioredis';
import { createHash } from 'crypto';

class AIResponseCache {
  private redis: Redis;
  private defaultTTL = 3600; // 1 hour
  
  constructor() {
    this.redis = new Redis({
      host: process.env.REDIS_HOST,
      port: 6379,
      maxRetriesPerRequest: 3,

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import { Pool, PoolConfig } from 'pg';
import { EventEmitter } from 'events';

class MonitoredPool extends EventEmitter {
  private pool: Pool;
  private metrics = {
    totalConnections: 0,
    idleConnections: 0,
    waitingClients: 0,
    queryCount: 0,
    slowQueries: 0,
    errors: 0,

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import Bull from 'bull';

interface AIRequest {
  userId: string;
  prompt: string;
  priority: 'high' | 'normal' | 'low';
  timestamp: number;
}

const aiQueue = new Bull<AIRequest>('ai-processing', {
  redis: { host: process.env.REDIS_HOST },
  defaultJobOptions: {