appfolio-performance-tuning

Testing & Quality

Optimize AppFolio API performance with caching and batch operations. Trigger: "appfolio performance".

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Source SKILL.md: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/HEAD/plugins/saas-packs/appfolio-pack/skills/appfolio-performance-tuning/SKILL.md

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AppFolio Performance Tuning

Overview

AppFolio's property management API handles bulk tenant queries, property portfolio pagination, and work order batch processing. Large portfolios with thousands of units generate heavy read traffic on listing endpoints. Optimizing cache lifetimes for slow-changing property data, batching work order updates, and pooling HTTP connections reduces API call volume by 60-80% and cuts dashboard load times from seconds to sub-second.

Caching Strategy

const cache = new Map<string, { data: any; expiry: number }>();
const TTL = { properties: 300_000, tenants: 120_000, units: 300_000, workOrders: 60_000 };

async function cached(key: string, ttlKey: keyof typeof TTL, fn: () => Promise<any>) {
  const entry = cache.get(key);
  if (entry && entry.expiry > Date.now()) return entry.data;
  const data = await fn();
  cache.set(key, { data, expiry: Date.now() + TTL[ttlKey] });
  return data;
}

Batch Operations

async function batchWorkOrders(client: any, ids: string[], batchSize = 25) {
  const results = [];
  for (let i = 0; i < ids.length; i += batchSize) {
    const batch = ids.slice(i, i + batchSize);
    const res = await Promise.all(batch.map(id => client.http.get(`/work_orders/${id}`)));
    results.push(...res.map(r => r.data));
    if (i + batchSize < ids.length) await new Promise(r => setTimeout(r, 200));
  }
  return results;
}

Connection Pooling

import { Agent } from 'https';
const agent = new Agent({ keepAlive: true, maxSockets: 10, maxFreeSockets: 5, timeout: 30_000 });
// Pass to axios/fetch: { httpsAgent: agent }

Rate Limit Management

async function withRateLimit(fn: () => Promise<any>): Promise<any> {
  const res = await fn();
  const remaining = parseInt(res.headers['x-ratelimit-remaining'] || '100');
  if (remaining < 5) {
    const retryAfter = parseInt(res.headers['retry-after'] || '2') * 1000;
    await new Promise(r => setTimeout(r, retryAfter));
  }
  return res;
}

Monitoring

const metrics = { apiCalls: 0, cacheHits: 0, errors: 0, totalLatency: 0 };
function track(startMs: number, hit: boolean, error?: boolean) {
  metrics.apiCalls++; metrics.totalLatency += Date.now() - startMs;
  if (hit) metrics.cacheHits++; if (error) metrics.errors++;
}
// Log: avg latency, cache hit rate, error rate per minute

Performance Checklist

Cache property and unit listings with 5-min TTL
Use incremental sync via last_modified timestamps
Batch work order updates in groups of 25
Enable HTTP keep-alive with connection pooling
Parse rate limit headers and back off proactively
Parallelize independent dashboard queries with Promise.all
Monitor cache hit ratio (target > 70%)
Set request timeouts to 30s to avoid hung connections

Error Handling

Issue	Cause	Fix
429 Too Many Requests	Exceeded API rate limit	Parse Retry-After header, exponential backoff
Stale tenant data	Cache TTL too long	Reduce tenant cache to 2 min, add cache-bust on writes
Timeout on portfolio list	Large dataset with no pagination	Add page_size=100 and cursor-based iteration
Connection reset	Socket exhaustion	Enable keep-alive agent with maxSockets cap

Resources

Next Steps

See appfolio-reference-architecture.