Add load test harness for pool and fleet sizing

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.
This commit is contained in:
benjamin.baker
2026-09-07 12:39:53 -04:00
parent 187d371453
commit 0d5b9730e3
10 changed files with 939 additions and 0 deletions

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# Sizing-simulation overlay. NOT part of the shipped image.
#
# Layers gevent onto the built production image so the gevent worker model can
# be measured against the gthread baseline under identical application code.
# Delete with the rest of scripts/loadtest once sizing questions are settled.
FROM shopdb-flask-wilm-api:latest
USER root
RUN pip install --no-cache-dir "gevent==25.9.1"

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"""Patch-day burst simulator: synchronized cold start of an endpoint fleet.
WHY this is separate from mixed_workload.py: that harness RAMPS agents in over
~20s and measures steady state, which deliberately avoids a thundering herd.
Patch day is the opposite case and stresses different machinery:
- a fresh TLS handshake per agent, all at once (handshakes are CPU-heavy)
- _resolve_asset_for_hostname runs on every arrival, so the DB pool is hit by
a synchronized burst rather than the smooth churn of steady state
- no warm connections in the pool, no warm caches
Modelled on the real agent (verified in agent/ShopDbEndpointAgent.Core/):
- CommandWorker.ExecuteAsync polls IMMEDIATELY, no startup delay, no jitter
- TelemetryWorker also reports immediately; its jitter applies only BETWEEN
runs, so first contact is synchronized too. Patch day is therefore TWO
simultaneous bursts per endpoint, not one.
- transient failures retry at a FIXED 10s (TransientRetryDelay), not
exponential-with-jitter, so a herd that fails together re-arrives together
--arrivalseconds is the spread of the reboot window. 0 means every agent hits at
once (single maintenance window, worst case); 60 approximates a staged ring.
Stdlib asyncio only, so it needs no dependency install in the container.
Usage:
python burst_arrival.py --fleet 700 --arrivalseconds 0 --seconds 120
"""
import argparse
import asyncio
import json
import os
import random
import ssl
import statistics
import time
STOP = False
def percentile(values, fraction):
if not values:
return 0.0
ordered = sorted(values)
index = min(int(len(ordered) * fraction), len(ordered) - 1)
return ordered[index]
async def request(host, port, context, method, path, timeout,
api_key=None, body=None):
"""One HTTP/1.1 request over a FRESH connection, so each call pays a full
TLS handshake - which is the point on patch day."""
started = time.monotonic()
writer = None
try:
reader, writer = await asyncio.wait_for(
asyncio.open_connection(host, port, ssl=context), timeout=timeout)
handshake = time.monotonic() - started
headers = [
'%s %s HTTP/1.1' % (method, path),
'Host: %s' % host,
'Accept: application/json',
'Connection: close',
]
if api_key:
headers.append('X-API-Key: %s' % api_key)
payload = b''
if body is not None:
payload = json.dumps(body).encode()
headers.append('Content-Type: application/json')
headers.append('Content-Length: %d' % len(payload))
writer.write(('\r\n'.join(headers) + '\r\n\r\n').encode() + payload)
await writer.drain()
header = await asyncio.wait_for(reader.readuntil(b'\r\n'), timeout=timeout)
status = int(header.split()[1])
await asyncio.wait_for(reader.read(), timeout=timeout)
return status, time.monotonic() - started, handshake
except Exception as error:
return type(error).__name__, time.monotonic() - started, None
finally:
if writer is not None:
try:
writer.close()
except Exception:
pass
def record(results, bucket, status, elapsed, handshake=None, first=False):
entry = results.setdefault(bucket, {
'times': [], 'status': {}, 'handshakes': [], 'firsttimes': []})
entry['times'].append(elapsed * 1000.0)
if handshake is not None:
entry['handshakes'].append(handshake * 1000.0)
if first:
entry['firsttimes'].append(elapsed * 1000.0)
key = str(status)
entry['status'][key] = entry['status'].get(key, 0) + 1
async def agent(index, host, port, context, api_key, results, arrivalseconds):
"""One endpoint coming back from a patch reboot.
Fires its telemetry report and its first command poll at the same instant,
mirroring the two workers both starting with no delay.
"""
if arrivalseconds > 0:
await asyncio.sleep(random.uniform(0, arrivalseconds))
hostname = 'LOADTEST%04d' % (index + 1)
async def telemetry():
status, elapsed, handshake = await request(
host, port, context, 'POST', '/api/collector/heartbeat',
timeout=120.0, api_key=api_key, body={'hostname': hostname})
record(results, 'telemetry_firstcontact', status, elapsed, handshake,
first=True)
telemetry_task = asyncio.ensure_future(telemetry())
path = '/api/endpoints/commands/next?hostname=%s' % hostname
first = True
while not STOP:
status, elapsed, handshake = await request(
host, port, context, 'GET', path, timeout=120.0, api_key=api_key)
record(results, 'fleet', status, elapsed, handshake, first=first)
if first:
first = False
if not isinstance(status, int):
# Mirrors CommandWorker TransientRetryDelay: fixed 10s, no jitter,
# so a herd that fails together re-arrives together.
await asyncio.sleep(10.0)
else:
await asyncio.sleep(0.05)
await telemetry_task
async def ui_user(host, port, context, results, think_seconds):
while not STOP:
status, elapsed, handshake = await request(
host, port, context, 'GET', '/api/dashboard/health', timeout=120.0)
record(results, 'ui', status, elapsed, handshake)
await asyncio.sleep(think_seconds)
async def main():
global STOP
parser = argparse.ArgumentParser()
parser.add_argument('--fleet', type=int, default=700)
parser.add_argument('--users', type=int, default=5)
parser.add_argument('--arrivalseconds', type=float, default=0.0)
parser.add_argument('--seconds', type=int, default=120)
parser.add_argument('--host', default='api')
parser.add_argument('--port', type=int, default=5001)
parser.add_argument('--think', type=float, default=3.0)
arguments = parser.parse_args()
api_key = os.environ.get('LOADTEST_TOKEN', '')
if not api_key:
raise SystemExit('LOADTEST_TOKEN not set')
context = ssl.create_default_context()
context.check_hostname = False
context.verify_mode = ssl.CERT_NONE
results = {}
tasks = []
for _ in range(arguments.users):
tasks.append(asyncio.ensure_future(ui_user(
arguments.host, arguments.port, context, results,
arguments.think)))
# Let the UI baseline establish before the storm hits.
await asyncio.sleep(5.0)
burst_started = time.monotonic()
for index in range(arguments.fleet):
tasks.append(asyncio.ensure_future(agent(
index, arguments.host, arguments.port, context, api_key, results,
arguments.arrivalseconds)))
await asyncio.sleep(arguments.seconds)
STOP = True
await asyncio.sleep(2.0)
for task in tasks:
task.cancel()
summary = {
'fleet': arguments.fleet,
'arrivalseconds': arguments.arrivalseconds,
'users': arguments.users,
'seconds': arguments.seconds,
'classes': {},
}
for bucket, entry in sorted(results.items()):
times = entry['times']
block = {
'samples': len(times),
'status': entry['status'],
'median_ms': round(statistics.median(times), 1) if times else 0.0,
'p95_ms': round(percentile(times, 0.95), 1),
'max_ms': round(max(times), 1) if times else 0.0,
}
if entry['handshakes']:
block['handshake_median_ms'] = round(
statistics.median(entry['handshakes']), 1)
block['handshake_p95_ms'] = round(
percentile(entry['handshakes'], 0.95), 1)
block['handshake_max_ms'] = round(max(entry['handshakes']), 1)
if entry['firsttimes']:
block['firstcontact_median_ms'] = round(
statistics.median(entry['firsttimes']), 1)
block['firstcontact_p95_ms'] = round(
percentile(entry['firsttimes'], 0.95), 1)
block['firstcontact_max_ms'] = round(max(entry['firsttimes']), 1)
summary['classes'][bucket] = block
print(json.dumps(summary, indent=2))
if __name__ == '__main__':
asyncio.run(main())

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"""Force SQLAlchemy pool sizing for a pool-comparison run.
WHY this exists: shopdb/config.py does not read pool size from the environment,
so a test container cannot be pointed at a different pool without a code change.
This patches Config.SQLALCHEMY_ENGINE_OPTIONS at import time, before create_app
builds the engine, purely so a bigger pool can be MEASURED before deciding
whether to make it permanent.
Not for production use. Mounted into a throwaway container as sitecustomize.py,
which Python imports automatically at startup.
"""
import os
from shopdb.config import Config
_size = int(os.environ.get('FORCE_POOL_SIZE', '5'))
_overflow = int(os.environ.get('FORCE_MAX_OVERFLOW', '10'))
_options = dict(Config.SQLALCHEMY_ENGINE_OPTIONS)
_options['pool_size'] = _size
_options['max_overflow'] = _overflow
Config.SQLALCHEMY_ENGINE_OPTIONS = _options

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"""Mint a temporary collector token for the load test, or revoke it after.
WHY a minted token: plugin.endpoints.envkeyfallback is false, which is the
agent kill switch working as intended - the env key no longer authorizes. The
harness therefore needs a real managed token scoped collector.ingest.endpoints,
exactly like a live agent.
The token is named LOADTEST so revoke() removes only this one and never touches
the real agent keys.
Usage (inside the api container, with PYTHONPATH=/app and cwd /app):
python loadtest_token.py mint # prints the secret once
python loadtest_token.py revoke
"""
import sys
from shopdb import create_app, db
from shopdb.core.models.apitoken import ApiToken
TOKEN_NAME = 'LOADTEST temporary collector token'
SCOPE = 'collector.ingest.endpoints'
def mint():
existing = ApiToken.query.filter_by(name=TOKEN_NAME).first()
if existing is not None:
db.session.delete(existing)
db.session.commit()
owner = ApiToken.query.filter(
ApiToken.scopes.like('%' + SCOPE + '%')).first()
if owner is None:
raise SystemExit('no existing collector token to copy ownership from')
secret = ApiToken.generate_secret()
token = ApiToken(
userid=owner.userid,
name=TOKEN_NAME,
tokenprefix=ApiToken.prefix_of(secret),
tokenhash=ApiToken.hash_secret(secret),
)
token.scopelist = [SCOPE]
db.session.add(token)
db.session.commit()
print(secret)
def revoke():
removed = ApiToken.query.filter_by(name=TOKEN_NAME).delete()
db.session.commit()
print('revoked %d loadtest token(s)' % removed)
if __name__ == '__main__':
action = sys.argv[1] if len(sys.argv) > 1 else ''
app = create_app()
with app.app_context():
if action == 'mint':
mint()
elif action == 'revoke':
revoke()
else:
print(__doc__)
sys.exit(2)

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"""Mixed-workload generator for sizing simulations.
WHY this shape: sizing cannot be judged from long-poll agents alone. The four
traffic classes have different concurrency costs, and only their SUM decides
whether a worker model holds:
fleet long-poll agents, one continuously-held connection each
ui human users clicking, latency-sensitive, the actual symptom
integration Maximo / ServiceNow style collector clients on a fixed interval
kiosk USB kiosk endpoints, public routes, low rate
The fleet class is what saturates a thread pool; the ui class is what a person
notices. Measuring them together is the point - a model that keeps agents happy
while starving the UI has failed even though every agent request succeeded.
Runs INSIDE a container on the compose network. Generating from the Windows host
would put host ephemeral-port and TLS-handshake limits in the measurement path,
which would look like server saturation but would not be.
Stdlib asyncio only, so it needs no dependency install in the container.
Usage:
python mixed_workload.py --fleet 300 --users 5 --seconds 120
"""
import argparse
import asyncio
import json
import os
import ssl
import statistics
import time
STOP = False
def percentile(values, fraction):
if not values:
return 0.0
ordered = sorted(values)
index = min(int(len(ordered) * fraction), len(ordered) - 1)
return ordered[index]
async def request(host, port, context, method, path, timeout,
api_key=None, bearer=None, body=None):
"""One HTTP/1.1 request over a fresh connection. Returns (status, seconds)."""
started = time.monotonic()
writer = None
try:
reader, writer = await asyncio.wait_for(
asyncio.open_connection(host, port, ssl=context), timeout=timeout)
headers = [
'%s %s HTTP/1.1' % (method, path),
'Host: %s' % host,
'Accept: application/json',
'Connection: close',
]
if api_key:
headers.append('X-API-Key: %s' % api_key)
if bearer:
headers.append('Authorization: Bearer %s' % bearer)
payload = b''
if body is not None:
payload = json.dumps(body).encode()
headers.append('Content-Type: application/json')
headers.append('Content-Length: %d' % len(payload))
blob = ('\r\n'.join(headers) + '\r\n\r\n').encode() + payload
writer.write(blob)
await writer.drain()
header = await asyncio.wait_for(reader.readuntil(b'\r\n'), timeout=timeout)
status = int(header.split()[1])
await asyncio.wait_for(reader.read(), timeout=timeout)
return status, time.monotonic() - started
except Exception as error:
return type(error).__name__, time.monotonic() - started
finally:
if writer is not None:
try:
writer.close()
except Exception:
pass
def record(results, bucket, status, elapsed):
entry = results.setdefault(bucket, {'times': [], 'status': {}})
entry['times'].append(elapsed * 1000.0)
key = str(status)
entry['status'][key] = entry['status'].get(key, 0) + 1
async def fleet_agent(index, host, port, context, api_key, results):
"""Mirrors CommandWorker.cs: re-poll immediately after each response."""
hostname = 'LOADTEST%04d' % (index + 1)
path = '/api/endpoints/commands/next?hostname=%s' % hostname
while not STOP:
status, elapsed = await request(
host, port, context, 'GET', path, timeout=120.0, api_key=api_key)
record(results, 'fleet', status, elapsed)
await asyncio.sleep(0.05)
async def ui_user(host, port, context, bearer, results, think_seconds):
"""A human clicking around. Latency here is the user-visible symptom."""
paths = ['/api/dashboard/health', '/api/endpoints?page=1&per_page=25',
'/api/assets?page=1&per_page=25']
cursor = 0
while not STOP:
path = paths[cursor % len(paths)]
cursor += 1
# Unauthenticated probe still measures queueing; auth only changes the
# handler cost, not whether a worker slot was available to accept it.
status, elapsed = await request(
host, port, context, 'GET', path, timeout=120.0, bearer=bearer)
record(results, 'ui', status, elapsed)
await asyncio.sleep(think_seconds)
async def integration_client(name, host, port, context, api_key, results,
interval):
"""Maximo / ServiceNow style poller on a fixed interval."""
while not STOP:
status, elapsed = await request(
host, port, context, 'GET', '/api/collector/status',
timeout=120.0, api_key=api_key)
record(results, 'integration', status, elapsed)
await asyncio.sleep(interval)
async def kiosk_endpoint(index, host, port, context, results, interval):
"""USB kiosk terminal. Public route, low rate."""
path = '/api/usb/kiosk/device/LOADTESTKIOSK%d' % (index + 1)
while not STOP:
status, elapsed = await request(
host, port, context, 'GET', path, timeout=120.0)
record(results, 'kiosk', status, elapsed)
await asyncio.sleep(interval)
async def main():
global STOP
parser = argparse.ArgumentParser()
parser.add_argument('--fleet', type=int, default=300)
parser.add_argument('--users', type=int, default=5)
parser.add_argument('--integrations', type=int, default=2)
parser.add_argument('--kiosks', type=int, default=8)
parser.add_argument('--seconds', type=int, default=120)
parser.add_argument('--host', default='api')
parser.add_argument('--port', type=int, default=5001)
parser.add_argument('--think', type=float, default=3.0)
parser.add_argument('--integration-interval', type=float, default=30.0)
parser.add_argument('--kiosk-interval', type=float, default=15.0)
parser.add_argument('--rampseconds', type=float, default=20.0)
arguments = parser.parse_args()
api_key = os.environ.get('LOADTEST_TOKEN', '')
if not api_key:
raise SystemExit('LOADTEST_TOKEN not set')
bearer = os.environ.get('LOADTEST_JWT') or None
context = ssl.create_default_context()
context.check_hostname = False
context.verify_mode = ssl.CERT_NONE
results = {}
tasks = []
# Ramp the fleet in rather than opening every connection at once. A
# thundering herd measures handshake burst capacity, not steady state.
stagger = arguments.rampseconds / max(arguments.fleet, 1)
async def staggered(index):
await asyncio.sleep(index * stagger)
await fleet_agent(index, arguments.host, arguments.port, context,
api_key, results)
for index in range(arguments.fleet):
tasks.append(asyncio.ensure_future(staggered(index)))
for _ in range(arguments.users):
tasks.append(asyncio.ensure_future(ui_user(
arguments.host, arguments.port, context, bearer, results,
arguments.think)))
for index in range(arguments.integrations):
tasks.append(asyncio.ensure_future(integration_client(
'integration%d' % index, arguments.host, arguments.port, context,
api_key, results, arguments.integration_interval)))
for index in range(arguments.kiosks):
tasks.append(asyncio.ensure_future(kiosk_endpoint(
index, arguments.host, arguments.port, context, results,
arguments.kiosk_interval)))
await asyncio.sleep(arguments.seconds)
STOP = True
await asyncio.sleep(2.0)
for task in tasks:
task.cancel()
summary = {
'fleet': arguments.fleet,
'users': arguments.users,
'integrations': arguments.integrations,
'kiosks': arguments.kiosks,
'seconds': arguments.seconds,
'classes': {},
}
for bucket, entry in sorted(results.items()):
times = entry['times']
summary['classes'][bucket] = {
'samples': len(times),
'status': entry['status'],
'median_ms': round(statistics.median(times), 1) if times else 0.0,
'p95_ms': round(percentile(times, 0.95), 1),
'max_ms': round(max(times), 1) if times else 0.0,
}
print(json.dumps(summary, indent=2))
if __name__ == '__main__':
asyncio.run(main())

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"""Async load generator for the endpoint command long-poll channel.
WHY this shape: the real agent (agent/ShopDbEndpointAgent.Core/CommandWorker.cs)
re-polls immediately on a 204, so every agent holds a connection essentially
continuously and fleet size IS the concurrency. This mirrors that loop rather
than issuing independent requests, so the measured concurrency matches a real
fleet of the same size.
Runs INSIDE a container on the compose network. Generating from the Windows host
would put host ephemeral-port and TLS-handshake limits in the measurement path,
which would look like server saturation but would not be.
While the fleet polls, a separate probe measures /api/dashboard/health - the
user-visible UI latency - because that, not agent latency, is the symptom that
matters for sizing.
Stdlib asyncio only, so it needs no dependency install in the container.
Usage:
python poll_fleet.py --agents 300 --seconds 90 --base https://api:5001
"""
import argparse
import asyncio
import json
import os
import ssl
import statistics
import time
STOP = False
def percentile(values, fraction):
if not values:
return 0.0
ordered = sorted(values)
index = min(int(len(ordered) * fraction), len(ordered) - 1)
return ordered[index]
async def request(host, port, context, path, api_key, timeout):
"""One HTTP/1.1 GET over a fresh connection. Returns (status, seconds)."""
started = time.monotonic()
writer = None
try:
reader, writer = await asyncio.wait_for(
asyncio.open_connection(host, port, ssl=context), timeout=timeout)
request_line = (
'GET %s HTTP/1.1\r\nHost: %s\r\nX-API-Key: %s\r\n'
'Accept: application/json\r\nConnection: close\r\n\r\n'
% (path, host, api_key))
writer.write(request_line.encode())
await writer.drain()
header = await asyncio.wait_for(reader.readuntil(b'\r\n'), timeout=timeout)
status = int(header.split()[1])
await asyncio.wait_for(reader.read(), timeout=timeout)
return status, time.monotonic() - started
except Exception as error:
return type(error).__name__, time.monotonic() - started
finally:
if writer is not None:
try:
writer.close()
except Exception:
pass
async def agent_loop(index, host, port, context, api_key, results, timeout):
"""Imitate one agent: poll, and on completion immediately poll again."""
hostname = 'LOADTEST%04d' % (index + 1)
path = '/api/endpoints/commands/next?hostname=' + hostname
while not STOP:
status, elapsed = await request(
host, port, context, path, api_key, timeout)
results.append((status, elapsed))
await asyncio.sleep(0)
async def main():
global STOP
parser = argparse.ArgumentParser()
parser.add_argument('--agents', type=int, required=True)
parser.add_argument('--seconds', type=int, default=90)
parser.add_argument('--host', default='api')
parser.add_argument('--port', type=int, default=5001)
parser.add_argument('--timeout', type=float, default=120.0)
parser.add_argument('--ramp', type=float, default=0.005)
arguments = parser.parse_args()
# A managed collector token, not the env key: the endpoints plugin has
# plugin.endpoints.envkeyfallback=false (the agent kill switch), so the env
# key no longer authorizes. See scripts/loadtest/loadtest_token.py.
api_key = os.environ.get('LOADTEST_TOKEN')
if not api_key:
raise SystemExit('LOADTEST_TOKEN not present in environment')
context = ssl.create_default_context()
context.check_hostname = False
context.verify_mode = ssl.CERT_NONE
results = []
tasks = []
started = time.monotonic()
for index in range(arguments.agents):
tasks.append(asyncio.create_task(agent_loop(
index, arguments.host, arguments.port, context, api_key,
results, arguments.timeout)))
if arguments.ramp:
await asyncio.sleep(arguments.ramp)
ramp_seconds = time.monotonic() - started
await asyncio.sleep(arguments.seconds)
STOP = True
for task in tasks:
task.cancel()
await asyncio.gather(*tasks, return_exceptions=True)
poll_ok = [d for s, d in results if s == 204]
poll_bad = [s for s, _ in results if s != 204]
failures = {}
for status in poll_bad:
failures[str(status)] = failures.get(str(status), 0) + 1
print(json.dumps({
'agents': arguments.agents,
'ramp_seconds': round(ramp_seconds, 1),
'duration_seconds': arguments.seconds,
'poll_completed': len(results),
'poll_ok_204': len(poll_ok),
'poll_failures': failures,
'poll_hold_median': round(statistics.median(poll_ok), 2) if poll_ok else None,
'poll_hold_p95': round(percentile(poll_ok, 0.95), 2) if poll_ok else None,
'poll_hold_max': round(max(poll_ok), 2) if poll_ok else None,
}, indent=2))
if __name__ == '__main__':
asyncio.run(main())

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"""Report SQLAlchemy pool saturation from inside the API container.
WHY: MySQL's max_connections is NOT the ceiling that binds first. The effective
limit is per-process: pool_size + max_overflow, multiplied by worker count.
With the defaults (5 + 10) and 4 workers that is 60, not 151. A peak of 52
therefore means 87 percent of the real ceiling, not 34 percent.
Prints the computed ceiling so a measured high-water mark can be compared
against the right number.
Usage (inside the api container, PYTHONPATH=/app):
python pool_status.py
"""
import json
import os
from shopdb import create_app
from shopdb.api import db
def main():
app = create_app(os.environ.get('FLASK_ENV', 'production'))
with app.app_context():
engine = db.engine
pool = engine.pool
size = pool.size()
overflow = getattr(pool, '_max_overflow', 0)
workers = int(os.environ.get('GUNICORN_WORKERS', '4'))
print(json.dumps({
'pool_class': type(pool).__name__,
'pool_size': size,
'max_overflow': overflow,
'per_worker_ceiling': size + overflow,
'workers': workers,
'effective_ceiling': (size + overflow) * workers,
'checkedout': pool.checkedout(),
'status': pool.status(),
}, indent=2))
if __name__ == '__main__':
main()

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

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"""Sample container CPU and memory during a sizing run.
WHY: the sizing table claims specific vCPU and RAM figures. Those can only be
confirmed by watching the container under load, not by reasoning about greenlet
size. This records peak RSS and CPU so a claimed "4 GB is enough" is either
demonstrated or falsified.
Runs on the HOST (needs the docker CLI), unlike the generators.
Usage:
python sample_resources.py --container shopdb-sizing-api --seconds 120
"""
import argparse
import json
import re
import statistics
import subprocess
import time
def parse_size(text):
"""Docker stats prints like '1.234GiB' / '512MiB'. Return megabytes."""
match = re.match(r'^([0-9.]+)\s*([KMGT]?i?B)$', text.strip())
if not match:
return 0.0
value = float(match.group(1))
unit = match.group(2).upper().replace('I', '')
factors = {'B': 1.0 / (1024 * 1024), 'KB': 1.0 / 1024, 'MB': 1.0,
'GB': 1024.0, 'TB': 1024.0 * 1024.0}
return value * factors.get(unit, 1.0)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--container', required=True)
parser.add_argument('--seconds', type=int, default=120)
parser.add_argument('--interval', type=float, default=2.0)
arguments = parser.parse_args()
cpu_samples = []
memory_samples = []
deadline = time.monotonic() + arguments.seconds
while time.monotonic() < deadline:
try:
output = subprocess.check_output(
['docker', 'stats', '--no-stream', '--format',
'{{.CPUPerc}}|{{.MemUsage}}', arguments.container],
stderr=subprocess.DEVNULL, text=True).strip()
except subprocess.CalledProcessError:
break
if not output:
break
cpu_text, memory_text = output.split('|', 1)
cpu_samples.append(float(cpu_text.replace('%', '').strip()))
used = memory_text.split('/')[0]
memory_samples.append(parse_size(used))
time.sleep(arguments.interval)
def summarize(values):
if not values:
return {'samples': 0}
ordered = sorted(values)
index = min(int(len(ordered) * 0.95), len(ordered) - 1)
return {
'samples': len(values),
'median': round(statistics.median(values), 1),
'p95': round(ordered[index], 1),
'max': round(max(values), 1),
}
print(json.dumps({
'container': arguments.container,
'cpu_percent': summarize(cpu_samples),
'memory_mb': summarize(memory_samples),
}, indent=2))
if __name__ == '__main__':
main()

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"""Measure UI latency against the API, independent of any load generator.
WHY separate from poll_fleet.py: when the probe shares an event loop with the
simulated fleet, generator-side scheduling can starve the probe and produce UI
latencies that are an artifact of the harness rather than of the server. Run
this in its own container, concurrently with the fleet, so the two cannot
interfere.
Usage:
python ui_probe.py --seconds 90 --interval 1.0
"""
import argparse
import json
import ssl
import statistics
import time
import urllib.request
def percentile(values, fraction):
if not values:
return 0.0
ordered = sorted(values)
index = min(int(len(ordered) * fraction), len(ordered) - 1)
return ordered[index]
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--seconds', type=int, default=90)
parser.add_argument('--interval', type=float, default=1.0)
parser.add_argument('--url',
default='https://api:5001/api/dashboard/health')
parser.add_argument('--timeout', type=float, default=120.0)
arguments = parser.parse_args()
context = ssl.create_default_context()
context.check_hostname = False
context.verify_mode = ssl.CERT_NONE
durations = []
failures = {}
deadline = time.monotonic() + arguments.seconds
while time.monotonic() < deadline:
started = time.monotonic()
try:
request = urllib.request.Request(arguments.url)
with urllib.request.urlopen(
request, timeout=arguments.timeout,
context=context) as response:
response.read()
if response.status == 200:
durations.append(time.monotonic() - started)
else:
key = str(response.status)
failures[key] = failures.get(key, 0) + 1
except Exception as error:
key = type(error).__name__
failures[key] = failures.get(key, 0) + 1
remaining = arguments.interval - (time.monotonic() - started)
if remaining > 0:
time.sleep(remaining)
print(json.dumps({
'ui_samples': len(durations) + sum(failures.values()),
'ui_ok_200': len(durations),
'ui_failures': failures,
'ui_median_ms': round(statistics.median(durations) * 1000, 1)
if durations else None,
'ui_p95_ms': round(percentile(durations, 0.95) * 1000, 1)
if durations else None,
'ui_max_ms': round(max(durations) * 1000, 1) if durations else None,
}, indent=2))
if __name__ == '__main__':
main()