A Load-Testing Playbook for Free AI Servers (and Why I Wrote One)

A developer created a 30-line load tester using asyncio and aiohttp to evaluate free AI server tiers before building on them. The script sends concurrent HTTP requests to a health endpoint and reports status codes and latencies, helping developers avoid unexpected 503s and hangs. The developer tested it against MonkeyCode's free server, exposing a cold-start delay on the first request.

Free AI servers are dangerously easy to trust. The docs promise zero cost, the setup takes minutes, and your first curl returns a perfect 200. Then your second user shows up, and the server starts answering with 503s or, worse, hangs forever. I've been burned by this pattern enough times that I finally wrote a 30-line load tester to check a free tier before I build anything on it. Here's the script, how to run it, and how to read the numbers without fooling yourself. The idea is simple: fire a fixed number of concurrent HTTP requests at a health endpoint, record status codes and latencies, and let the results speak. I used asyncio and aiohttp because they handle concurrency without spawning a thread per request, which would skew the test on a small machine. python import asyncio import time import aiohttp async def hit session, url, results : start = time.perf counter try: async with session.get url as resp: await resp.read status = resp.status except Exception as exc: status = type exc . name results.append status, time.perf counter - start async def main url, concurrency, total : results = async with aiohttp.ClientSession as session: tasks = for in range total : tasks.append hit session, url, results if len tasks = concurrency: await asyncio.gather tasks tasks = if tasks: await asyncio.gather tasks return results if name == " main ": import sys url = sys.argv 1 if len sys.argv 1 else "https://example.com/health" concurrency = int sys.argv 2 if len sys.argv 2 else 20 total = int sys.argv 3 if len sys.argv 3 else 200 results = asyncio.run main url, concurrency, total ok = r for r in results if r 0 == 200 errors = r for r in results if r 0 = 200 latencies = r 1 for r in ok print f"Total: {len results }" print f"OK: {len ok }" print f"Errors: {len errors }" if latencies: print f"Avg latency: {sum latencies / len latencies :.3f}s" print f"Max latency: {max latencies :.3f}s" if errors: print f"First error type: {errors 0 0 }" Save it as loadtest.py , install aiohttp with pip install aiohttp , and point it at your endpoint. The script sends requests in batches, so it won't flood the server with 200 simultaneous sockets on a tiny free instance. Start with a gentle baseline: one request, then ten, then fifty. I usually run this sequence: python loadtest.py https://your-free-server.example.com/health 1 10 python loadtest.py https://your-free-server.example.com/health 10 100 python loadtest.py https://your-free-server.example.com/health 50 500 The first run tells you the raw latency. The second reveals connection limits. The third shows how the server behaves under sustained pressure. Three numbers matter most: MonkeyCode is an open-source project that caught my attention because it bundles free model access with a free server option, which is exactly the combination that needs this kind of testing. Disclosure: This article was prepared as part of MonkeyCode's product outreach. I ran the load tester against a small service deployed on their free server, and the process was genuinely useful: it gave me concrete numbers before I wrote any application code, and it exposed a cold-start delay on the first request that I would have missed otherwise. The free tier is not a production SLA, and I don't treat it as one. But for a prototype or a weekend project, knowing that the server can handle 20 concurrent requests with a 400ms average latency is enough to move forward. The tester doesn't validate model quality or token limits, so I check the current docs for those numbers before committing. This script only measures HTTP behavior, not model correctness, token throughput, or data privacy. If you're building something that handles sensitive information, a shared free server is the wrong choice regardless of load test results. Also, a single endpoint test won't catch every failure mode: database connections, background workers, and cold starts all hide behind the health check. Run the tester against the actual routes your users will hit, not just /health . If you're already on a paid platform with a guaranteed SLA, you don't need this playbook. But if you're evaluating a free tier for a side project, or you're tired of discovering limits after your users do, spend ten minutes with this script first. The numbers will tell you more than any README promise.