0d5b9730e3
Adds the scripts used to size the connection pool and validate fleet polling under load: burst arrival and mixed workload drivers, pool and resource samplers, a UI probe, host seed/drop SQL, and a gevent Dockerfile. Hosts are addressed by compose service name (api:5001) rather than a local path, so the harness runs against any stack rather than one machine. loadtest_token.py mints a scoped collector token named LOADTEST and prints the secret once, then revokes only that token by name so a real collector token is never touched. envkeyfallback is false, so the harness needs a genuine managed token rather than an env key.
79 lines
2.6 KiB
Python
79 lines
2.6 KiB
Python
"""Measure UI latency against the API, independent of any load generator.
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WHY separate from poll_fleet.py: when the probe shares an event loop with the
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simulated fleet, generator-side scheduling can starve the probe and produce UI
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latencies that are an artifact of the harness rather than of the server. Run
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this in its own container, concurrently with the fleet, so the two cannot
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interfere.
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Usage:
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python ui_probe.py --seconds 90 --interval 1.0
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"""
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import argparse
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import json
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import ssl
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import statistics
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import time
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import urllib.request
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def percentile(values, fraction):
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if not values:
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return 0.0
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ordered = sorted(values)
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index = min(int(len(ordered) * fraction), len(ordered) - 1)
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return ordered[index]
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument('--seconds', type=int, default=90)
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parser.add_argument('--interval', type=float, default=1.0)
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parser.add_argument('--url',
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default='https://api:5001/api/dashboard/health')
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parser.add_argument('--timeout', type=float, default=120.0)
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arguments = parser.parse_args()
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context = ssl.create_default_context()
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context.check_hostname = False
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context.verify_mode = ssl.CERT_NONE
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durations = []
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failures = {}
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deadline = time.monotonic() + arguments.seconds
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while time.monotonic() < deadline:
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started = time.monotonic()
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try:
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request = urllib.request.Request(arguments.url)
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with urllib.request.urlopen(
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request, timeout=arguments.timeout,
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context=context) as response:
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response.read()
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if response.status == 200:
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durations.append(time.monotonic() - started)
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else:
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key = str(response.status)
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failures[key] = failures.get(key, 0) + 1
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except Exception as error:
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key = type(error).__name__
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failures[key] = failures.get(key, 0) + 1
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remaining = arguments.interval - (time.monotonic() - started)
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if remaining > 0:
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time.sleep(remaining)
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print(json.dumps({
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'ui_samples': len(durations) + sum(failures.values()),
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'ui_ok_200': len(durations),
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'ui_failures': failures,
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'ui_median_ms': round(statistics.median(durations) * 1000, 1)
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if durations else None,
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'ui_p95_ms': round(percentile(durations, 0.95) * 1000, 1)
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if durations else None,
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'ui_max_ms': round(max(durations) * 1000, 1) if durations else None,
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}, indent=2))
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if __name__ == '__main__':
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main()
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