executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
posthog-performance-tuningOptimize 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".
Independent GitHub snapshot · Automated classification · Original documentation governs
Optimize PostHog API performance with caching, batching, and connection pooling.
| Operation | P50 | P95 | P99 |
|---|---|---|---|
| Read | 50ms | 150ms | 300ms |
| Write | 100ms | 250ms | 500ms |
| List | 75ms | 200ms | 400ms |
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;
}
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;
}
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'),
]);
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,
});
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);
}
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;
}
}
Measure current latency for critical PostHog operations.
Add response caching for frequently accessed data.
Use DataLoader or similar for automatic request batching.
Configure connection pooling with keep-alive.
| 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 |
const withPerformance = <T>(name: string, fn: () => Promise<T>) =>
measuredPostHogCall(name, () =>
cachedPostHogRequest(`cache:${name}`, fn)
);
For cost optimization, see posthog-cost-tuning.