Files
shopdb-flask/scripts/loadtest/mixed_workload.py
cproudlock 534f179ee6 Make main the lean product a site receives
main was 16 days and 259 commits behind the line the product is actually built
on, at contract 0.30.0 against 0.35.0, with no per-PC credential code at all. It
was neither current nor curated - just stale. This brings it forward and, at the
same time, makes it mean something: main is what a receiving site installs, and
nothing else.

WHAT IT CARRIES. Twelve plugins - backups, computers, endpoints, guides,
knowledgebase, machines, network, notifications, printers, slides, tools,
warranty - plus applications, which is manifest-less core and always ships. The
only manifest dependency inside that set is endpoints on computers, and both are
in it, so the closure is self-contained.

WHAT IT DOES NOT. employees, geenforce, measuringtools, printedparts and usb
stay on the site line. So do the Windows installer tree, the VM rehearsal
helpers, the agent tooling config, one site's data loader, the internal audit
and findings records, and the planner spreadsheet. 1,135 tracked files against
1,438.

A REMOVAL THAT BREAKS THE APP IS NOT A REMOVAL, and two nearly shipped:

deploy/site-profile-universal.json still named all seventeen plugins. It is the
file docs/DEPLOY.md tells a site to provision from, so a fresh install would
have failed at `flask plugin apply-profile` with PluginError - the first thing a
receiving site does, broken by the branch meant to serve them. It now names the
twelve that exist, and its comment says the two must agree.

agent/ was never refreshed. Whoever populated this branch copied shopdb/,
plugins/, frontend/ and tests/ from the site line and left the agent tree at its
September state: 22 C# and PowerShell sources missing, including AgentCredentials,
EnrollmentService, AgentHttpFactory and the fleet-alert client, plus one file the
site line had deleted still present. The old tree is internally consistent, so it
compiles, and nothing in CI builds it - every gate was green over a server that
speaks enrollment and per-PC credentials to a bundled agent source that cannot.
Resynced whole.

DECISIONS THIS ENCODES, rather than defers:

- The plugin-authoring lab builds printedparts, whose manifest depends on
  employees, so it could not stay. The lab remains on the site line and main
  ships no build-along tutorial. That is a real loss for an adopting developer
  and is recorded here rather than discovered later.
- Recognition, Training and Recertification notifications are no longer seeded.
  Each splits one notification into a card per employee and renders a photo,
  which needs a plugin this branch does not bundle. Seeding them would offer an
  author a type that cannot resolve anybody. A site that installs employees gets
  them from that plugin's own seed.
- Windows/IIS is documented as the legacy path throughout, and the README leads
  with Docker, because that is what a receiving site gets.

The API description is regenerated for THIS branch - 347 paths and 483
operations, down from 415 and 573 - so the published contract describes what is
here rather than what the site line serves. docs/CONFIG.md lost the two
measuring-tool label keys the code no longer declares, which two lanes had
decided opposite ways.

Suite: 3124 passed, 6 skipped. Naming and style gates pass. The docs gates run
rather than skip, and every index line count is derived from the file it names.
2026-09-19 11:24:40 -04:00

219 lines
8.2 KiB
Python

"""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 unauthenticated display 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):
"""Unauthenticated display screen. Public route, low rate."""
path = '/api/dashboarddefaults/display-role'
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())