Agent skill

redis-caching-patterns

Redis caching strategies for MCP servers - cache invalidation, TTL management, pub/sub patterns, and performance optimization

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SKILL.md

Redis Caching Patterns Skill

Description

This skill provides battle-tested Redis caching strategies for high-performance MCP servers managing fleet-scale operations. It covers intelligent cache invalidation, TTL optimization, real-time pub/sub patterns, and performance monitoring.

Core Capabilities:

  • Cache invalidation strategies (time-based, event-based, manual)
  • TTL optimization for different data types (ephemeral vs persistent)
  • Pub/sub patterns for real-time agent notifications
  • Cache-aside, write-through, and read-through patterns
  • Performance monitoring and cache hit ratio optimization
  • Distributed caching for multi-instance MCP servers

When to Use This Skill

Use this skill when you need to:

  • Design caching strategies for MCP resources or tools
  • Optimize performance for fleet-scale operations (100+ miners)
  • Implement real-time updates via Redis pub/sub
  • Reduce gRPC call overhead with intelligent caching
  • Handle cache invalidation when data changes
  • Monitor cache effectiveness and tune TTLs

Trigger Phrases:

  • "Design cache strategy for fleet metrics"
  • "Implement Redis caching for miner status"
  • "Add pub/sub for real-time updates"
  • "Optimize cache TTL for this data"
  • "Handle cache invalidation when config changes"

Don't use this skill for:

  • In-memory caching (use Map or LRU cache instead)
  • Session storage (use Redis but different patterns)
  • Message queuing (use Bull or BullMQ instead)
  • Database replacement (cache is supplementary)

Prerequisites

Knowledge Requirements

  1. Redis Fundamentals

    • Key-value storage and data structures
    • TTL (time-to-live) and expiration
    • Pub/sub messaging patterns
    • Redis commands (GET, SET, SETEX, DEL, PUBLISH, SUBSCRIBE)

  2. Caching Theory

    • Cache-aside (lazy loading) pattern
    • Write-through vs write-back caching
    • Cache invalidation strategies
    • Cache stampede prevention

  3. MCP Server Architecture

    • Resource caching needs (see mcp-server-dev skill)
    • Tool optimization opportunities
    • Real-time update requirements

Environment Setup

typescript
// Required dependencies
{
  "ioredis": "^5.3.2",
  "@types/ioredis": "^5.0.0"
}

Project Context

  • Understanding of data access patterns (read-heavy vs write-heavy)
  • Knowledge of data freshness requirements
  • Integration points with gRPC client (see grpc-client-dev skill)

Workflow

Phase 1: Cache Strategy Design

1.1 Data Classification

Pattern: Classify Data by Caching Characteristics

typescript
// src/cache/cache-strategy.ts

export enum CacheStrategy {
  // Short TTL: Data changes frequently (5-30 seconds)
  EPHEMERAL = 'EPHEMERAL',

  // Medium TTL: Data changes occasionally (1-5 minutes)
  MODERATE = 'MODERATE',

  // Long TTL: Data rarely changes (10-60 minutes)
  STABLE = 'STABLE',

  // Event-based: Invalidate on specific events
  EVENT_DRIVEN = 'EVENT_DRIVEN',

  // No cache: Always fetch fresh
  NO_CACHE = 'NO_CACHE'
}

export interface CacheConfig {
  strategy: CacheStrategy;
  ttl: number; // seconds
  invalidateOn?: string[]; // Event names
  namespace: string; // Key prefix
}

// Example: Fleet data classification
const CACHE_CONFIGS: Record<string, CacheConfig> = {
  'miner:status': {
    strategy: CacheStrategy.EPHEMERAL,
    ttl: 10, // 10 seconds
    namespace: 'cache:miner:status'
  },
  'fleet:summary': {
    strategy: CacheStrategy.EPHEMERAL,
    ttl: 30, // 30 seconds
    namespace: 'cache:fleet'
  },
  'miner:config': {
    strategy: CacheStrategy.EVENT_DRIVEN,
    ttl: 300, // 5 minutes fallback
    invalidateOn: ['miner:config:updated'],
    namespace: 'cache:miner:config'
  },
  'firmware:versions': {
    strategy: CacheStrategy.STABLE,
    ttl: 3600, // 1 hour
    namespace: 'cache:firmware'
  }
};

Decision Matrix:

Data Type Change Frequency Read Pattern Recommended Strategy TTL
Miner status Every 1-5s Very high (100+ req/s) EPHEMERAL 10s
Fleet metrics Every 10-30s High (10-50 req/s) EPHEMERAL 30s
Miner config On update Medium (1-10 req/s) EVENT_DRIVEN 5m
Firmware list Daily Low (<1 req/s) STABLE 1h
Pool URLs Rarely Low STABLE 12h

1.2 Key Naming Convention

Pattern: Hierarchical Namespace with Versioning

typescript
// src/cache/keys.ts

export class CacheKeys {
  private static VERSION = 'v1';

  /**
   * Generate cache key for miner status
   */
  static minerStatus(minerId: string): string {
    return `${this.VERSION}:cache:miner:${minerId}:status`;
  }

  /**
   * Generate cache key for fleet summary
   */
  static fleetSummary(tenantId?: string): string {
    const tenant = tenantId || 'global';
    return `${this.VERSION}:cache:fleet:${tenant}:summary`;
  }

  /**
   * Generate cache key for miner config
   */
  static minerConfig(minerId: string): string {
    return `${this.VERSION}:cache:miner:${minerId}:config`;
  }

  /**
   * Generate pattern for deleting all miner keys
   */
  static minerPattern(minerId: string): string {
    return `${this.VERSION}:cache:miner:${minerId}:*`;
  }

  /**
   * Generate pattern for fleet keys
   */
  static fleetPattern(tenantId?: string): string {
    const tenant = tenantId || '*';
    return `${this.VERSION}:cache:fleet:${tenant}:*`;
  }
}

Rationale:

  • Version prefix: Allows global cache invalidation by bumping version
  • Hierarchical structure: Enables pattern-based deletion
  • Scoped by entity: Easy to invalidate all keys for a miner/fleet
  • No colons in IDs: Prevents key conflicts

Phase 2: Cache Implementation Patterns

2.1 Cache-Aside (Lazy Loading)

Pattern: Read-Through with Fallback

typescript
// src/cache/cache-aside.ts
import Redis from 'ioredis';

export class CacheAsideService {
  constructor(private redis: Redis) {}

  /**
   * Get from cache with fallback to source
   */
  async getOrFetch<T>(
    key: string,
    fetchFn: () => Promise<T>,
    ttl: number
  ): Promise<T> {
    // Try cache first
    const cached = await this.redis.get(key);

    if (cached) {
      try {
        return JSON.parse(cached) as T;
      } catch (error) {
        // Invalid JSON in cache, fall through to fetch
        await this.redis.del(key);
      }
    }

    // Cache miss - fetch from source
    const data = await fetchFn();

    // Store in cache with TTL
    await this.redis.setex(
      key,
      ttl,
      JSON.stringify(data)
    );

    return data;
  }

  /**
   * Get miner status with cache-aside pattern
   */
  async getMinerStatus(
    minerId: string,
    fetchStatus: () => Promise<MinerStatus>
  ): Promise<MinerStatus> {
    return this.getOrFetch(
      CacheKeys.minerStatus(minerId),
      fetchStatus,
      10 // 10 second TTL
    );
  }
}

Usage in MCP Resource:

typescript
// Example: MCP resource using cache-aside
@resource({
  uri: "braiins:///miner/{minerId}/status",
  mimeType: "application/json"
})
async getMinerStatus(minerId: string): Promise<MinerStatus> {
  return this.cacheService.getMinerStatus(minerId, async () => {
    // Only called on cache miss
    const status = await this.grpcClient.getStatus(minerId);
    return status;
  });
}

2.2 Write-Through Caching

Pattern: Update Cache on Write

typescript
// src/cache/write-through.ts

export class WriteThroughService {
  constructor(
    private redis: Redis,
    private repository: MinerRepository
  ) {}

  /**
   * Update miner config with write-through
   */
  async updateMinerConfig(
    minerId: string,
    config: MinerConfig
  ): Promise<void> {
    // Write to source of truth (database)
    await this.repository.update(minerId, config);

    // Update cache immediately
    const key = CacheKeys.minerConfig(minerId);
    await this.redis.setex(
      key,
      300, // 5 minute TTL
      JSON.stringify(config)
    );
  }

  /**
   * Read with guaranteed fresh data
   */
  async getMinerConfig(minerId: string): Promise<MinerConfig | null> {
    const key = CacheKeys.minerConfig(minerId);
    const cached = await this.redis.get(key);

    if (cached) {
      return JSON.parse(cached) as MinerConfig;
    }

    // Cache miss - fetch and populate
    const config = await this.repository.findById(minerId);
    if (config) {
      await this.redis.setex(key, 300, JSON.stringify(config));
    }

    return config;
  }
}

2.3 Event-Based Invalidation

Pattern: Invalidate on Data Change

typescript
// src/cache/invalidation.ts

export class CacheInvalidationService {
  constructor(private redis: Redis) {}

  /**
   * Invalidate miner-related caches
   */
  async invalidateMiner(minerId: string): Promise<void> {
    const keys = [
      CacheKeys.minerStatus(minerId),
      CacheKeys.minerConfig(minerId)
    ];

    await this.redis.del(...keys);
  }

  /**
   * Invalidate all fleet caches
   */
  async invalidateFleet(tenantId?: string): Promise<void> {
    const pattern = CacheKeys.fleetPattern(tenantId);

    // Find all matching keys
    const keys = await this.scanKeys(pattern);

    if (keys.length > 0) {
      await this.redis.del(...keys);
    }
  }

  /**
   * Scan for keys matching pattern (cursor-based to avoid blocking)
   */
  private async scanKeys(pattern: string): Promise<string[]> {
    const keys: string[] = [];
    let cursor = '0';

    do {
      const [nextCursor, batch] = await this.redis.scan(
        cursor,
        'MATCH',
        pattern,
        'COUNT',
        100
      );

      cursor = nextCursor;
      keys.push(...batch);
    } while (cursor !== '0');

    return keys;
  }
}

// Integration with repository
export class MinerRepository {
  async update(minerId: string, data: Partial<MinerEntity>): Promise<MinerEntity> {
    // Update database
    const updated = await this.db.update(minerId, data);

    // Invalidate caches
    await this.cacheInvalidation.invalidateMiner(minerId);
    await this.cacheInvalidation.invalidateFleet(); // Fleet metrics include this miner

    return updated;
  }
}

Phase 3: Redis Pub/Sub for Real-Time Updates

3.1 Publisher Pattern

Pattern: Publish Events on Data Change

typescript
// src/cache/publisher.ts

export class CacheEventPublisher {
  constructor(private redis: Redis) {}

  /**
   * Publish miner status update
   */
  async publishMinerStatus(minerId: string, status: MinerStatus): Promise<void> {
    const channel = `events:miner:${minerId}:status`;
    const message = JSON.stringify({
      minerId,
      status,
      timestamp: new Date().toISOString()
    });

    await this.redis.publish(channel, message);
  }

  /**
   * Publish fleet-wide event
   */
  async publishFleetEvent(event: string, data: unknown): Promise<void> {
    const channel = 'events:fleet';
    const message = JSON.stringify({
      event,
      data,
      timestamp: new Date().toISOString()
    });

    await this.redis.publish(channel, message);
  }
}

// Usage in gRPC stream handler
export class MinerStatusStream {
  async handleStatusUpdate(minerId: string, status: MinerStatus): Promise<void> {
    // Update cache
    const key = CacheKeys.minerStatus(minerId);
    await this.redis.setex(key, 30, JSON.stringify(status));

    // Publish event for real-time subscribers
    await this.publisher.publishMinerStatus(minerId, status);
  }
}

3.2 Subscriber Pattern

Pattern: Subscribe to Events for Real-Time MCP Resources

typescript
// src/cache/subscriber.ts

export class CacheEventSubscriber {
  private subscriber: Redis;
  private handlers: Map<string, ((message: string) => void)[]> = new Map();

  constructor(redisConfig: RedisOptions) {
    // Create dedicated Redis connection for pub/sub
    this.subscriber = new Redis(redisConfig);
  }

  /**
   * Subscribe to miner status events
   */
  async subscribeMinerStatus(
    minerId: string,
    handler: (status: MinerStatus) => void
  ): Promise<void> {
    const channel = `events:miner:${minerId}:status`;

    if (!this.handlers.has(channel)) {
      await this.subscriber.subscribe(channel);

      this.subscriber.on('message', (ch, message) => {
        if (ch === channel) {
          const handlers = this.handlers.get(channel) || [];
          handlers.forEach(h => h(message));
        }
      });
    }

    const handlers = this.handlers.get(channel) || [];
    handlers.push((message: string) => {
      try {
        const parsed = JSON.parse(message);
        handler(parsed.status);
      } catch (error) {
        console.error('Failed to parse status message:', error);
      }
    });
    this.handlers.set(channel, handlers);
  }

  /**
   * Unsubscribe from channel
   */
  async unsubscribe(channel: string): Promise<void> {
    await this.subscriber.unsubscribe(channel);
    this.handlers.delete(channel);
  }

  /**
   * Dispose all subscriptions
   */
  async dispose(): Promise<void> {
    for (const channel of this.handlers.keys()) {
      await this.subscriber.unsubscribe(channel);
    }
    this.handlers.clear();
    await this.subscriber.quit();
  }
}

Phase 4: Performance Optimization

4.1 Cache Stampede Prevention

Pattern: Single-Flight for Expensive Operations

typescript
// src/cache/single-flight.ts

export class SingleFlightCache {
  private inflightRequests: Map<string, Promise<unknown>> = new Map();

  constructor(private redis: Redis) {}

  /**
   * Ensure only one request fetches data at a time
   */
  async getOrFetchSingleFlight<T>(
    key: string,
    fetchFn: () => Promise<T>,
    ttl: number
  ): Promise<T> {
    // Check cache first
    const cached = await this.redis.get(key);
    if (cached) {
      return JSON.parse(cached) as T;
    }

    // Check if fetch is already in progress
    const inflight = this.inflightRequests.get(key);
    if (inflight) {
      return inflight as Promise<T>;
    }

    // Start fetch and store promise
    const fetchPromise = (async () => {
      try {
        const data = await fetchFn();
        await this.redis.setex(key, ttl, JSON.stringify(data));
        return data;
      } finally {
        this.inflightRequests.delete(key);
      }
    })();

    this.inflightRequests.set(key, fetchPromise);
    return fetchPromise;
  }
}

4.2 Cache Warming

Pattern: Proactive Cache Population

typescript
// src/cache/warming.ts

export class CacheWarmingService {
  constructor(
    private redis: Redis,
    private minerRepo: MinerRepository,
    private grpcClient: BraiinsMinerClient
  ) {}

  /**
   * Warm cache for all active miners
   */
  async warmMinerCaches(): Promise<void> {
    const miners = await this.minerRepo.findAll({ status: 'active' });

    // Warm in parallel with controlled concurrency
    const concurrency = 10;
    for (let i = 0; i < miners.data.length; i += concurrency) {
      const batch = miners.data.slice(i, i + concurrency);

      await Promise.allSettled(
        batch.map(miner => this.warmMinerCache(miner.id))
      );
    }
  }

  /**
   * Warm cache for a specific miner
   */
  private async warmMinerCache(minerId: string): Promise<void> {
    try {
      const status = await this.grpcClient.getMinerStatus(minerId);

      const key = CacheKeys.minerStatus(minerId);
      await this.redis.setex(key, 30, JSON.stringify(status));
    } catch (error) {
      console.error(`Failed to warm cache for ${minerId}:`, error);
    }
  }

  /**
   * Schedule periodic cache warming
   */
  startPeriodicWarming(intervalMs: number = 60000): NodeJS.Timer {
    return setInterval(() => {
      void this.warmMinerCaches();
    }, intervalMs);
  }
}

4.3 Monitoring and Metrics

Pattern: Track Cache Performance

typescript
// src/cache/metrics.ts

export class CacheMetrics {
  private hits: number = 0;
  private misses: number = 0;
  private errors: number = 0;

  recordHit(): void {
    this.hits++;
  }

  recordMiss(): void {
    this.misses++;
  }

  recordError(): void {
    this.errors++;
  }

  getHitRatio(): number {
    const total = this.hits + this.misses;
    return total > 0 ? this.hits / total : 0;
  }

  getStats(): CacheStats {
    return {
      hits: this.hits,
      misses: this.misses,
      errors: this.errors,
      hitRatio: this.getHitRatio(),
      total: this.hits + this.misses
    };
  }

  reset(): void {
    this.hits = 0;
    this.misses = 0;
    this.errors = 0;
  }
}

// Instrumented cache service
export class InstrumentedCacheService {
  private metrics = new CacheMetrics();

  async get<T>(key: string): Promise<T | null> {
    try {
      const value = await this.redis.get(key);

      if (value) {
        this.metrics.recordHit();
        return JSON.parse(value) as T;
      } else {
        this.metrics.recordMiss();
        return null;
      }
    } catch (error) {
      this.metrics.recordError();
      throw error;
    }
  }

  getMetrics(): CacheStats {
    return this.metrics.getStats();
  }
}

Examples

Example 1: Complete MCP Resource with Caching

typescript
// src/mcp/resources/fleet-summary.ts

@resource({
  uri: "braiins:///fleet/summary",
  name: "Fleet Summary",
  description: "Aggregated metrics for all managed miners",
  mimeType: "application/json"
})
async getFleetSummary(tenantId?: string): Promise<FleetSummary> {
  return this.singleFlightCache.getOrFetchSingleFlight(
    CacheKeys.fleetSummary(tenantId),
    async () => {
      // Expensive operation - aggregates data from all miners
      const miners = await this.minerRepo.findByTenant(tenantId);

      const summary = {
        totalMiners: miners.length,
        onlineMiners: miners.filter(m => m.online).length,
        totalHashrate: miners.reduce((sum, m) => sum + m.hashrate, 0),
        avgTemperature: miners.reduce((sum, m) => sum + m.temperature, 0) / miners.length
      };

      return summary;
    },
    30 // 30 second TTL
  );
}

Example 2: Real-Time Updates via Pub/Sub

typescript
// src/mcp/resources/miner-status-stream.ts

@resource({
  uri: "braiins:///miner/{minerId}/status/stream",
  name: "Miner Status Stream",
  mimeType: "application/json"
})
async getMinerStatusStream(minerId: string): Promise<AsyncIterable<MinerStatus>> {
  const channel = `events:miner:${minerId}:status`;
  let subscriber: Redis;

  return {
    [Symbol.asyncIterator]() {
      return {
        async next() {
          if (!subscriber) {
            subscriber = new Redis(redisConfig);
            await subscriber.subscribe(channel);
          }

          return new Promise((resolve) => {
            subscriber.once('message', (ch, message) => {
              if (ch === channel) {
                const status = JSON.parse(message).status;
                resolve({ value: status, done: false });
              }
            });
          });
        },
        async return() {
          if (subscriber) {
            await subscriber.unsubscribe(channel);
            await subscriber.quit();
          }
          return { value: undefined, done: true };
        }
      };
    }
  };
}

Quality Standards

Cache Implementation Checklist

  • TTL Configuration

    • TTLs are appropriate for data change frequency
    • No infinite TTLs (always expire eventually)
    • Different TTLs for different data types

  • Invalidation

    • Event-based invalidation for mutable data
    • Pattern-based deletion uses SCAN (not KEYS)
    • Cascade invalidation (miner → fleet)

  • Performance

    • Cache stampede prevention implemented
    • Parallel operations use Promise.allSettled
    • Connection pooling for Redis (ioredis default)

  • Monitoring

    • Cache hit ratio tracked
    • Metrics logged periodically
    • Target: >80% hit ratio for ephemeral data

  • Error Handling

    • Redis errors don't break application
    • Fallback to source on cache failure
    • Errors logged for debugging

Common Pitfalls

❌ Pitfall 1: Using KEYS for Pattern Deletion

Problem: KEYS blocks Redis and causes timeouts

typescript
// BAD: Blocks Redis
const keys = await redis.keys('cache:miner:*');
await redis.del(...keys);

Solution: Use SCAN with cursor

typescript
// GOOD: Non-blocking scan
async function deletePattern(pattern: string): Promise<void> {
  let cursor = '0';
  do {
    const [nextCursor, keys] = await redis.scan(cursor, 'MATCH', pattern, 'COUNT', 100);
    cursor = nextCursor;
    if (keys.length > 0) {
      await redis.del(...keys);
    }
  } while (cursor !== '0');
}

❌ Pitfall 2: Cache Stampede on Popular Keys

Problem: Many requests simultaneously fetch same data

typescript
// BAD: Every request fetches on cache miss
const cached = await redis.get(key);
if (!cached) {
  // 100 requests simultaneously call expensive fetchData()
  const data = await fetchData();
  await redis.set(key, JSON.stringify(data));
}

Solution: Use single-flight pattern

typescript
// GOOD: Only one request fetches
return singleFlightCache.getOrFetchSingleFlight(key, fetchData, ttl);

❌ Pitfall 3: Forgetting to Invalidate on Update

Problem: Stale data served after updates

typescript
// BAD: Cache not invalidated
async function updateMiner(minerId: string, config: MinerConfig) {
  await db.update(minerId, config);
  // Cache still has old data!
}

Solution: Always invalidate on write

typescript
// GOOD: Write-through with invalidation
async function updateMiner(minerId: string, config: MinerConfig) {
  await db.update(minerId, config);
  await redis.del(CacheKeys.minerConfig(minerId));
  await redis.del(CacheKeys.fleetSummary()); // Cascade
}

Integration with MCP Server

Complete Caching Layer

typescript
// src/cache/index.ts - Central caching service

export class MCPCacheService {
  private cacheAside: CacheAsideService;
  private writeThrough: WriteThroughService;
  private invalidation: CacheInvalidationService;
  private singleFlight: SingleFlightCache;
  private publisher: CacheEventPublisher;
  private subscriber: CacheEventSubscriber;
  private metrics: InstrumentedCacheService;

  constructor(redis: Redis) {
    this.cacheAside = new CacheAsideService(redis);
    this.writeThrough = new WriteThroughService(redis, minerRepo);
    this.invalidation = new CacheInvalidationService(redis);
    this.singleFlight = new SingleFlightCache(redis);
    this.publisher = new CacheEventPublisher(redis);
    this.subscriber = new CacheEventSubscriber(redisConfig);
    this.metrics = new InstrumentedCacheService(redis);
  }

  // Expose all caching patterns through unified interface
}

References

Version History:

  • 1.0.0 (2025-12-29): Initial release - Cache patterns, pub/sub, performance optimization

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