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caching-strategist

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Caching Strategist

缓存策略设计

Design effective caching strategies for performance and consistency.
为性能与一致性设计有效的缓存策略。

Cache Layers

缓存层级

CDN: Static assets, public pages (TTL: days/weeks) Application Cache (Redis): API responses, sessions (TTL: minutes/hours) Database Cache: Query results (TTL: seconds/minutes) Client Cache: Browser/app local cache
CDN: 静态资源、公共页面（TTL：天/周） 应用层缓存（Redis）: API响应、会话（TTL：分钟/小时） 数据库缓存: 查询结果（TTL：秒/分钟） 客户端缓存: 浏览器/应用本地缓存

Cache Key Strategy

缓存键策略

typescript
// Hierarchical key structure
const CACHE_KEYS = {
  user: (id: string) => `user:${id}`,
  userPosts: (userId: string, page: number) => `user:${userId}:posts:${page}`,
  post: (id: string) => `post:${id}`,
  postComments: (postId: string) => `post:${postId}:comments`,
};

// Include version in keys for easy invalidation
const CACHE_VERSION = "v1";
const key = `${CACHE_VERSION}:${CACHE_KEYS.user(userId)}`;
typescript
// Hierarchical key structure
const CACHE_KEYS = {
  user: (id: string) => `user:${id}`,
  userPosts: (userId: string, page: number) => `user:${userId}:posts:${page}`,
  post: (id: string) => `post:${id}`,
  postComments: (postId: string) => `post:${postId}:comments`,
};

// Include version in keys for easy invalidation
const CACHE_VERSION = "v1";
const key = `${CACHE_VERSION}:${CACHE_KEYS.user(userId)}`;

TTL Strategy

TTL策略

typescript
const TTL = {
  // Frequently changing
  REALTIME: 10, // 10 seconds
  SHORT: 60, // 1 minute

  // Moderate updates
  MEDIUM: 300, // 5 minutes
  STANDARD: 3600, // 1 hour

  // Rarely changing
  LONG: 86400, // 1 day
  VERY_LONG: 604800, // 1 week
};

// Usage
await redis.setex(key, TTL.MEDIUM, JSON.stringify(data));
typescript
const TTL = {
  // Frequently changing
  REALTIME: 10, // 10 seconds
  SHORT: 60, // 1 minute

  // Moderate updates
  MEDIUM: 300, // 5 minutes
  STANDARD: 3600, // 1 hour

  // Rarely changing
  LONG: 86400, // 1 day
  VERY_LONG: 604800, // 1 week
};

// Usage
await redis.setex(key, TTL.MEDIUM, JSON.stringify(data));

Cache-Aside Pattern

旁路缓存模式

typescript
export const getCachedUser = async (userId: string): Promise<User> => {
  const key = CACHE_KEYS.user(userId);

  // Try cache first
  const cached = await redis.get(key);
  if (cached) {
    return JSON.parse(cached);
  }

  // Cache miss - fetch from DB
  const user = await db.users.findById(userId);

  // Store in cache
  await redis.setex(key, TTL.STANDARD, JSON.stringify(user));

  return user;
};
typescript
export const getCachedUser = async (userId: string): Promise<User> => {
  const key = CACHE_KEYS.user(userId);

  // Try cache first
  const cached = await redis.get(key);
  if (cached) {
    return JSON.parse(cached);
  }

  // Cache miss - fetch from DB
  const user = await db.users.findById(userId);

  // Store in cache
  await redis.setex(key, TTL.STANDARD, JSON.stringify(user));

  return user;
};

Cache Invalidation

缓存失效

typescript
// Invalidate on update
export const updateUser = async (userId: string, data: UpdateUserDto) => {
  const user = await db.users.update(userId, data);

  // Invalidate cache
  await redis.del(CACHE_KEYS.user(userId));

  // Invalidate related caches
  await redis.del(CACHE_KEYS.userPosts(userId, "*"));

  return user;
};

// Tag-based invalidation
const addCacheTags = (key: string, tags: string[]) => {
  tags.forEach((tag) => {
    redis.sadd(`cache_tag:${tag}`, key);
  });
};

const invalidateByTag = async (tag: string) => {
  const keys = await redis.smembers(`cache_tag:${tag}`);
  if (keys.length) {
    await redis.del(...keys);
    await redis.del(`cache_tag:${tag}`);
  }
};
typescript
// Invalidate on update
export const updateUser = async (userId: string, data: UpdateUserDto) => {
  const user = await db.users.update(userId, data);

  // Invalidate cache
  await redis.del(CACHE_KEYS.user(userId));

  // Invalidate related caches
  await redis.del(CACHE_KEYS.userPosts(userId, "*"));

  return user;
};

// Tag-based invalidation
const addCacheTags = (key: string, tags: string[]) => {
  tags.forEach((tag) => {
    redis.sadd(`cache_tag:${tag}`, key);
  });
};

const invalidateByTag = async (tag: string) => {
  const keys = await redis.smembers(`cache_tag:${tag}`);
  if (keys.length) {
    await redis.del(...keys);
    await redis.del(`cache_tag:${tag}`);
  }
};

Cache Warming

缓存预热

typescript
// Pre-populate cache for common queries
export const warmCache = async () => {
  const popularPosts = await db.posts.findPopular(100);

  for (const post of popularPosts) {
    const key = CACHE_KEYS.post(post.id);
    await redis.setex(key, TTL.LONG, JSON.stringify(post));
  }
};

// Schedule warming
cron.schedule("0 */6 * * *", warmCache); // Every 6 hours
typescript
// Pre-populate cache for common queries
export const warmCache = async () => {
  const popularPosts = await db.posts.findPopular(100);

  for (const post of popularPosts) {
    const key = CACHE_KEYS.post(post.id);
    await redis.setex(key, TTL.LONG, JSON.stringify(post));
  }
};

// Schedule warming
cron.schedule("0 */6 * * *", warmCache); // Every 6 hours

Cache Stampede Prevention

缓存击穿预防

typescript
// Use locks to prevent multiple simultaneous fetches
export const getCachedWithLock = async (
  key: string,
  fetchFn: () => Promise<any>
) => {
  const cached = await redis.get(key);
  if (cached) return JSON.parse(cached);

  const lockKey = `lock:${key}`;
  const acquired = await redis.set(lockKey, "1", "EX", 10, "NX");

  if (acquired) {
    try {
      // Fetch and cache
      const data = await fetchFn();
      await redis.setex(key, TTL.STANDARD, JSON.stringify(data));
      return data;
    } finally {
      await redis.del(lockKey);
    }
  } else {
    // Wait for other request to finish
    await new Promise((resolve) => setTimeout(resolve, 100));
    return getCachedWithLock(key, fetchFn);
  }
};
typescript
// Use locks to prevent multiple simultaneous fetches
export const getCachedWithLock = async (
  key: string,
  fetchFn: () => Promise<any>
) => {
  const cached = await redis.get(key);
  if (cached) return JSON.parse(cached);

  const lockKey = `lock:${key}`;
  const acquired = await redis.set(lockKey, "1", "EX", 10, "NX");

  if (acquired) {
    try {
      // Fetch and cache
      const data = await fetchFn();
      await redis.setex(key, TTL.STANDARD, JSON.stringify(data));
      return data;
    } finally {
      await redis.del(lockKey);
    }
  } else {
    // Wait for other request to finish
    await new Promise((resolve) => setTimeout(resolve, 100));
    return getCachedWithLock(key, fetchFn);
  }
};

Cache Correctness Checklist

缓存正确性检查清单

markdown
- [ ] Cache keys are unique and predictable
- [ ] TTL is appropriate for data freshness
- [ ] Invalidation happens on all updates
- [ ] Related caches invalidated together
- [ ] Cache stampede prevention in place
- [ ] Fallback to DB if cache fails
- [ ] Monitoring cache hit rate
- [ ] Cache size doesn't grow unbounded
- [ ] Sensitive data not cached or encrypted
- [ ] Cache warming for critical paths
markdown
- [ ] 缓存键唯一且可预测
- [ ] TTL设置符合数据新鲜度需求
- [ ] 所有更新操作均触发缓存失效
- [ ] 关联缓存同步失效
- [ ] 已部署缓存击穿预防机制
- [ ] 缓存失效时回退到数据库
- [ ] 监控缓存命中率
- [ ] 缓存大小不会无限制增长
- [ ] 敏感数据不缓存或已加密
- [ ] 关键路径已配置缓存预热

Best Practices

最佳实践

  • Cache immutable data aggressively
  • Short TTLs for frequently changing data
  • Invalidate on write, not on read
  • Monitor hit rates and adjust
  • Use tags for bulk invalidation
  • Prevent cache stampedes
  • Graceful degradation if cache down
  • 对不可变数据进行激进缓存
  • 频繁变更数据使用短TTL
  • 写入时触发失效，而非读取时
  • 监控命中率并按需调整
  • 使用标签进行批量失效
  • 预防缓存击穿
  • 缓存故障时优雅降级

Output Checklist

输出检查清单

  • Cache key naming strategy
  • TTL values per data type
  • Invalidation triggers documented
  • Cache-aside implementation
  • Stampede prevention
  • Cache warming strategy
  • Monitoring/metrics setup
  • Correctness checklist completed
  • 缓存键命名策略已确定
  • 各数据类型的TTL值已定义
  • 失效触发机制已记录
  • 旁路缓存模式已实现
  • 缓存击穿预防已部署
  • 缓存预热策略已制定
  • 监控/指标已配置
  • 正确性检查清单已完成