---

name: windsurf-performance-tuning description: | Optimize Windsurf API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for Windsurf integrations. Trigger with phrases like "windsurf performance", "optimize windsurf", "windsurf latency", "windsurf caching", "windsurf slow", "windsurf batch". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io compatible-with: claude-code, codex, openclaw

Windsurf Performance Tuning

Overview

Optimize Windsurf API performance with caching, batching, and connection pooling.

Prerequisites

• Windsurf SDK installed
• Understanding of async patterns
• Redis or in-memory cache available (optional)
• Performance monitoring in place

Latency Benchmarks

| Operation | P50 | P95 | P99 | |-----------|-----|-----|-----| | Read | 50ms | 150ms | 300ms | | Write | 100ms | 250ms | 500ms | | List | 75ms | 200ms | 400ms |

Caching Strategy

Response Caching

import { LRUCache } from 'lru-cache';

const cache = new LRUCache<string, any>({
  max: 1000,
  ttl: 60000, // 1 minute
  updateAgeOnGet: true,
});

async function cachedWindsurfRequest<T>(
  key: string,
  fetcher: () => Promise<T>,
  ttl?: number
): Promise<T> {
  const cached = cache.get(key);
  if (cached) return cached as T;

  const result = await fetcher();
  cache.set(key, result, { ttl });
  return result;
}

Redis Caching (Distributed)

import Redis from 'ioredis';

const redis = new Redis(process.env.REDIS_URL);

async function cachedWithRedis<T>(
  key: string,
  fetcher: () => Promise<T>,
  ttlSeconds = 60
): Promise<T> {
  const cached = await redis.get(key);
  if (cached) return JSON.parse(cached);

  const result = await fetcher();
  await redis.setex(key, ttlSeconds, JSON.stringify(result));
  return result;
}

Request Batching

import DataLoader from 'dataloader';

const windsurfLoader = new DataLoader<string, any>(
  async (ids) => {
    // Batch fetch from Windsurf
    const results = await windsurfClient.batchGet(ids);
    return ids.map(id => results.find(r => r.id === id) || null);
  },
  {
    maxBatchSize: 100,
    batchScheduleFn: callback => setTimeout(callback, 10),
  }
);

// Usage - automatically batched
const [item1, item2, item3] = await Promise.all([
  windsurfLoader.load('id-1'),
  windsurfLoader.load('id-2'),
  windsurfLoader.load('id-3'),
]);

Connection Optimization

import { Agent } from 'https';

// Keep-alive connection pooling
const agent = new Agent({
  keepAlive: true,
  maxSockets: 10,
  maxFreeSockets: 5,
  timeout: 30000,
});

const client = new WindsurfClient({
  apiKey: process.env.WINDSURF_API_KEY!,
  httpAgent: agent,
});

Pagination Optimization

async function* paginatedWindsurfList<T>(
  fetcher: (cursor?: string) => Promise<{ data: T[]; nextCursor?: string }>
): AsyncGenerator<T> {
  let cursor: string | undefined;

  do {
    const { data, nextCursor } = await fetcher(cursor);
    for (const item of data) {
      yield item;
    }
    cursor = nextCursor;
  } while (cursor);
}

// Usage
for await (const item of paginatedWindsurfList(cursor =>
  windsurfClient.list({ cursor, limit: 100 })
)) {
  await process(item);
}

Performance Monitoring

async function measuredWindsurfCall<T>(
  operation: string,
  fn: () => Promise<T>
): Promise<T> {
  const start = performance.now();
  try {
    const result = await fn();
    const duration = performance.now() - start;
    console.log({ operation, duration, status: 'success' });
    return result;
  } catch (error) {
    const duration = performance.now() - start;
    console.error({ operation, duration, status: 'error', error });
    throw error;
  }
}

Instructions

Step 1: Establish Baseline

Measure current latency for critical Windsurf operations.

Step 2: Implement Caching

Add response caching for frequently accessed data.

Step 3: Enable Batching

Use DataLoader or similar for automatic request batching.

Step 4: Optimize Connections

Configure connection pooling with keep-alive.

Output

• Reduced API latency
• Caching layer implemented
• Request batching enabled
• Connection pooling configured

Error Handling

| Issue | Cause | Solution | |-------|-------|----------| | Cache miss storm | TTL expired | Use stale-while-revalidate | | Batch timeout | Too many items | Reduce batch size | | Connection exhausted | No pooling | Configure max sockets | | Memory pressure | Cache too large | Set max cache entries |

Examples

Quick Performance Wrapper

const withPerformance = <T>(name: string, fn: () => Promise<T>) =>
  measuredWindsurfCall(name, () =>
    cachedWindsurfRequest(`cache:${name}`, fn)
  );

Resources

• Windsurf Performance Guide
• DataLoader Documentation
• LRU Cache Documentation

Next Steps

For cost optimization, see windsurf-cost-tuning.