posthog-performance-tuning skill

---
name: posthog-performance-tuning
description: |
  Optimize PostHog API performance with caching, batching, and connection pooling.
  Use when experiencing slow API responses, implementing caching strategies,
  or optimizing request throughput for PostHog integrations.
  Trigger with phrases like "posthog performance", "optimize posthog",
  "posthog latency", "posthog caching", "posthog slow", "posthog batch".
allowed-tools: Read, Write, Edit
version: 1.0.0
license: MIT
author: Jeremy Longshore <[email protected]>
---

# PostHog Performance Tuning

## Overview
Optimize PostHog API performance with caching, batching, and connection pooling.

## Prerequisites
- PostHog 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
```typescript
import { LRUCache } from 'lru-cache';

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

async function cachedPostHogRequest<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)
```typescript
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

```typescript
import DataLoader from 'dataloader';

const posthogLoader = new DataLoader<string, any>(
  async (ids) => {
    // Batch fetch from PostHog
    const results = await posthogClient.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([
  posthogLoader.load('id-1'),
  posthogLoader.load('id-2'),
  posthogLoader.load('id-3'),
]);
```

## Connection Optimization

```typescript
import { Agent } from 'https';

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

const client = new PostHogClient({
  apiKey: process.env.POSTHOG_API_KEY!,
  httpAgent: agent,
});
```

## Pagination Optimization

```typescript
async function* paginatedPostHogList<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 paginatedPostHogList(cursor =>
  posthogClient.list({ cursor, limit: 100 })
)) {
  await process(item);
}
```

## Performance Monitoring

```typescript
async function measuredPostHogCall<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 PostHog 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
```typescript
const withPerformance = <T>(name: string, fn: () => Promise<T>) =>
  measuredPostHogCall(name, () =>
    cachedPostHogRequest(`cache:${name}`, fn)
  );
```

## Resources
- [PostHog Performance Guide](https://docs.posthog.com/performance)
- [DataLoader Documentation](https://github.com/graphql/dataloader)
- [LRU Cache Documentation](https://github.com/isaacs/node-lru-cache)

## Next Steps
For cost optimization, see `posthog-cost-tuning`.