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/typescript
/caching

Caching Guide

Overview

NitroStack provides built-in caching capabilities to improve performance and reduce redundant operations. Use the @Cache decorator to automatically cache tool responses.

Basic Caching

Using @Cache Decorator

import { Tool, Cache } from 'nitrostack';

@Tool({ name: 'get_config' })
@Cache({ ttl: 3600 })  // Cache for 1 hour
async getConfig(input: any, ctx: ExecutionContext) {
  const config = await this.configService.load();
  return config;
}

Cache Options

interface CacheOptions {
  ttl: number;                              // Time to live in seconds
  key?: (input: any) => string;            // Custom cache key function
  invalidateOn?: string[];                 // Events that invalidate cache
}

TTL (Time To Live)

Common TTL Values

// 5 minutes - frequently changing data
@Cache({ ttl: 300 })

// 1 hour - semi-static data
@Cache({ ttl: 3600 })

// 1 day - static configuration
@Cache({ ttl: 86400 })

// 1 week - rarely changing data
@Cache({ ttl: 604800 })

Dynamic TTL

@Tool({ name: 'get_weather' })
@Cache({
  ttl: (input) => {
    // Cache current weather for 10 minutes
    // Cache forecast for 1 hour
    return input.type === 'current' ? 600 : 3600;
  }
})
async getWeather(input: any) {
  // ...
}

Custom Cache Keys

Simple Key

@Tool({ name: 'get_product' })
@Cache({
  ttl: 600,
  key: (input) => `product:${input.product_id}`
})
async getProduct(input: any) {
  return await this.productService.findById(input.product_id);
}

Composite Key

@Tool({ name: 'search_products' })
@Cache({
  ttl: 300,
  key: (input) => `products:${input.category}:${input.page}:${input.sort}`
})
async searchProducts(input: any) {
  return await this.productService.search(input);
}

User-Specific Cache

@Tool({ name: 'get_recommendations' })
@UseGuards(JWTGuard)
@Cache({
  ttl: 1800,
  key: (input, ctx) => `recommendations:${ctx.auth?.subject}`
})
async getRecommendations(input: any, ctx: ExecutionContext) {
  const userId = ctx.auth?.subject;
  return await this.recommendationService.getFor(userId);
}

Cache Invalidation

Event-Based Invalidation

@Tool({ name: 'get_product' })
@Cache({
  ttl: 3600,
  key: (input) => `product:${input.id}`,
  invalidateOn: ['product.updated', 'product.deleted']
})
async getProduct(input: any) {
  // Cache invalidated when these events are emitted
}

@Tool({ name: 'update_product' })
async updateProduct(input: any, ctx: ExecutionContext) {
  const product = await this.productService.update(input);
  
  // Invalidate cache
  ctx.emit('product.updated', { id: product.id });
  
  return product;
}

Manual Invalidation

@Injectable()
export class CacheService {
  async invalidate(key: string): Promise<void> {
    // Remove from cache
  }
  
  async invalidatePattern(pattern: string): Promise<void> {
    // Remove all keys matching pattern
    // e.g., 'product:*'
  }
  
  async clear(): Promise<void> {
    // Clear entire cache
  }
}

// Usage
@Tool({ name: 'clear_cache' })
@UseGuards(AdminGuard)
async clearCache(input: any) {
  await this.cacheService.clear();
  return { success: true };
}

Cache Strategies

Cache-Aside (Lazy Loading)

@Injectable()
export class ProductService {
  constructor(
    private db: DatabaseService,
    private cache: CacheService
  ) {}
  
  async findById(id: string) {
    // Check cache first
    const cached = await this.cache.get(`product:${id}`);
    if (cached) return cached;
    
    // Load from database
    const product = await this.db.queryOne(
      'SELECT * FROM products WHERE id = ?',
      [id]
    );
    
    // Store in cache
    await this.cache.set(`product:${id}`, product, 3600);
    
    return product;
  }
}

Write-Through

async updateProduct(id: string, data: any) {
  // Update database
  await this.db.execute(
    'UPDATE products SET name = ? WHERE id = ?',
    [data.name, id]
  );
  
  // Update cache immediately
  const product = await this.db.queryOne(
    'SELECT * FROM products WHERE id = ?',
    [id]
  );
  await this.cache.set(`product:${id}`, product, 3600);
  
  return product;
}

Write-Behind

async updateProduct(id: string, data: any) {
  // Update cache immediately
  await this.cache.set(`product:${id}`, data, 3600);
  
  // Queue database update
  await this.queue.add('update-product', { id, data });
  
  return data;
}

Cache Storage Backends

In-Memory (Default)

// Fast but not persistent
// Lost on server restart
// Single-server only

Redis

import { createClient } from 'redis';

@Injectable()
export class RedisCacheService {
  private client = createClient({
    url: process.env.REDIS_URL
  });
  
  async get(key: string): Promise<any> {
    const value = await this.client.get(key);
    return value ? JSON.parse(value) : null;
  }
  
  async set(key: string, value: any, ttl: number): Promise<void> {
    await this.client.setEx(
      key,
      ttl,
      JSON.stringify(value)
    );
  }
}

Memcached

import Memcached from 'memcached';

@Injectable()
export class MemcachedService {
  private client = new Memcached(process.env.MEMCACHED_SERVERS);
  
  async get(key: string): Promise<any> {
    return new Promise((resolve) => {
      this.client.get(key, (err, data) => {
        resolve(err ? null : data);
      });
    });
  }
}

Best Practices

1. Set Appropriate TTL

// ✅ Good - Match data volatility
@Cache({ ttl: 300 })  // 5 min for frequently changing data
@Cache({ ttl: 3600 }) // 1 hour for semi-static data
@Cache({ ttl: 86400 }) // 1 day for static data

// ❌ Avoid - Too long for dynamic data
@Cache({ ttl: 86400 })  // 1 day for stock prices

2. Use Specific Cache Keys

// ✅ Good - Specific keys
key: (input) => `product:${input.id}:${input.locale}`

// ❌ Avoid - Generic keys
key: (input) => `data:${input.id}`

3. Cache Expensive Operations

// ✅ Good - Cache database queries
@Cache({ ttl: 600 })
async searchProducts(input: any) {
  return await this.db.query(/* complex query */);
}

// ❌ Avoid - Caching simple operations
@Cache({ ttl: 600 })
async addNumbers(input: any) {
  return input.a + input.b;
}

4. Invalidate on Updates

// ✅ Good - Invalidate when data changes
@Tool({ name: 'get_user' })
@Cache({
  ttl: 3600,
  invalidateOn: ['user.updated']
})

// ❌ Avoid - No invalidation strategy
@Tool({ name: 'get_user' })
@Cache({ ttl: 3600 })  // Stale data possible

5. Monitor Cache Metrics

@Injectable()
export class CacheService {
  private hits = 0;
  private misses = 0;
  
  async get(key: string): Promise<any> {
    const value = await this.storage.get(key);
    
    if (value) {
      this.hits++;
    } else {
      this.misses++;
    }
    
    return value;
  }
  
  getMetrics() {
    const total = this.hits + this.misses;
    return {
      hits: this.hits,
      misses: this.misses,
      hitRate: total > 0 ? this.hits / total : 0
    };
  }
}

Performance Tips

1. Cache Hierarchies

// L1: In-memory cache (fastest)
// L2: Redis cache (fast)
// L3: Database (slowest)

async findProduct(id: string) {
  // Check L1
  let product = this.memoryCache.get(id);
  if (product) return product;
  
  // Check L2
  product = await this.redisCache.get(id);
  if (product) {
    this.memoryCache.set(id, product);
    return product;
  }
  
  // Check L3
  product = await this.db.findById(id);
  await this.redisCache.set(id, product);
  this.memoryCache.set(id, product);
  
  return product;
}

2. Cache Warm-Up

async onApplicationStart() {
  // Pre-load frequently accessed data
  const popular = await this.db.query(
    'SELECT * FROM products ORDER BY views DESC LIMIT 100'
  );
  
  for (const product of popular) {
    await this.cache.set(`product:${product.id}`, product, 3600);
  }
}

3. Compression

import { compress, decompress } from 'lz-string';

async set(key: string, value: any, ttl: number) {
  const compressed = compress(JSON.stringify(value));
  await this.storage.set(key, compressed, ttl);
}

async get(key: string) {
  const compressed = await this.storage.get(key);
  return compressed ? JSON.parse(decompress(compressed)) : null;
}

Troubleshooting

Cache Not Working

  1. Check TTL is set
  2. Verify cache service is injected
  3. Check cache key is consistent
  4. Monitor cache hit/miss ratio

Stale Data

  1. Reduce TTL
  2. Implement invalidation
  3. Use event-based clearing
  4. Add version to cache keys

Memory Issues

  1. Set max cache size
  2. Implement LRU eviction
  3. Use external cache (Redis)
  4. Reduce TTL

Next Steps

Pro Tip: Start with conservative TTLs and increase based on monitoring. It's easier to extend cache duration than to deal with stale data!

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