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.
69 lines
2.1 KiB
Python
69 lines
2.1 KiB
Python
"""Sample live MySQL connection counts at high frequency.
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WHY: pool pressure from a long-poll fleet is BURSTY. The route releases its
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connection before sleeping and re-acquires on wake, so the interesting number is
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the peak concurrent checkout during a wake burst, not the steady-state count. A
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slow sampler misses it entirely.
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Runs on the HOST (needs the docker CLI).
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Usage:
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python sample_dbconns.py --seconds 120 --interval 0.25
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"""
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import argparse
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import json
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import statistics
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import subprocess
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import time
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QUERY = ("SELECT COUNT(*), SUM(command<>'Sleep') "
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"FROM information_schema.processlist WHERE user='shopdb';")
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument('--container', default='shopdb-flask-wilm-db-1')
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parser.add_argument('--seconds', type=int, default=120)
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parser.add_argument('--interval', type=float, default=0.25)
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arguments = parser.parse_args()
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total_samples = []
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active_samples = []
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deadline = time.monotonic() + arguments.seconds
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command = ('mysql -u root -p$MYSQL_ROOT_PASSWORD -N -B -e "%s"' % QUERY)
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while time.monotonic() < deadline:
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try:
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output = subprocess.check_output(
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['docker', 'exec', arguments.container, 'sh', '-c', command],
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stderr=subprocess.DEVNULL, text=True).strip()
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except subprocess.CalledProcessError:
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break
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if not output:
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break
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parts = output.split()
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total_samples.append(int(parts[0]))
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active_samples.append(int(parts[1]) if parts[1] != 'NULL' else 0)
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time.sleep(arguments.interval)
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def summarize(values):
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if not values:
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return {'samples': 0}
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ordered = sorted(values)
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index = min(int(len(ordered) * 0.95), len(ordered) - 1)
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return {
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'samples': len(values),
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'median': statistics.median(values),
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'p95': ordered[index],
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'max': max(values),
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}
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print(json.dumps({
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'connections': summarize(total_samples),
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'active_queries': summarize(active_samples),
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}, indent=2))
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if __name__ == '__main__':
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main()
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