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#!/usr/bin/env pmpython
"""Test pmdaopentelemetry via exposing fake endpoints -*- python -*- """
#
# Copyright (C) 2025 Red Hat.
#
# This program is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 2 of the License, or (at your
# option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
# or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
# for more details.
#
import time
import re
import queue
import threading
import socket
from http.server import HTTPServer, BaseHTTPRequestHandler
import argparse
import json
from copy import deepcopy
activeEndpoint = dict()
def write_endpoint_metadata(args=None, endpoint=None):
endpointStr = "http://{}:{}/{}{}".format("localhost", args.addr[1], args.url, endpoint)
f = open('{}/{}'.format(str(args.output), "source"+str(endpoint)+".url"), 'w')
f.write("{}\n".format(endpointStr))
f.close()
class FakeEndpoint(BaseHTTPRequestHandler):
def sample_gauge_data(self, iteration=None, instances=None, metrics=None, endpointNum=None):
gauge_value = 12.1
instance_scale = 1
instance_count = 0
format_name = 'sample_gauge{:04d}'.format(endpointNum)
format_desc = 'sample_gauge{:04d} instance scale {}, value scale {}'.format(endpointNum, instance_scale, gauge_value)
gauge_string = {'name': 'sample_gauge', 'unit': '1', 'description': 'description', 'gauge': {'aggregationTemporality': '2', 'isMonotonic': 'True', 'dataPoints': [{'asDouble': '5', 'timeUnixNano': '1544712660300000000', 'attributes': [{'key': 'labels', 'value': {'stringValue': 'some.interesting.labels'}}]}]}}
points = gauge_string['gauge']['dataPoints'][0]
gauge_string['name'] = format_name
gauge_string['description'] = format_desc
data = []
for i in range(instances):
copy = deepcopy(points)
format_instname = "{{bar=\'{:.1f}\'}}".format(i * instance_scale)
format_value = "{:.1f}".format((int(iteration) * instance_count * gauge_value))
inst_dict = {'key': 'instance', 'value': {'stringValue': format_instname}}
copy['asDouble'] = format_value
copy['attributes'].append(inst_dict)
data.append(copy)
instance_count += 1
gauge_string['gauge']['dataPoints'] = data
return gauge_string
def sample_counter_data(self, iteration=None, instances=None, metrics=None, endpointNum=None):
counter_value = 1.70205394e+08
instance_scale = 0.7
instance_count = 0
format_name = 'sample_counter{:04d}'.format(endpointNum)
format_desc = 'sample_counter{:04d} instance scale {} value scale {}'.format(endpointNum, instance_scale, counter_value)
counter_string = {'name': 'sample_counter', 'unit': '1', 'description': 'description', 'sum': {'aggregationTemporality': '2', 'isMonotonic': 'True', 'dataPoints': [{'asDouble': 10, 'timeUnixNano': '1544712660300000000', 'attributes': [{'key': 'labels', 'value': {'stringValue': 'some.interesting.labels'}}]}]}}
points = counter_string['sum']['dataPoints'][0]
counter_string['name'] = format_name
counter_string['description'] = format_desc
data = []
for i in range(instances):
copy = deepcopy(points)
format_instname = "{{baz=\'{:.1f}\'}}".format(i * instance_scale)
format_value = "{:.8e}".format((int(iteration) * instance_count * counter_value))
inst_dict = {'key': 'instance', 'value': {'stringValue': format_instname}}
copy['asDouble'] = format_value
copy['attributes'].append(inst_dict)
data.append(copy)
instance_count += 1
counter_string['sum']['dataPoints'] = data
return counter_string
def sample_summary_data(self, iteration=None, instances=None, metrics=None, endpointNum=None):
summary_value_q0 = 0.000159623
summary_value_sum = 1.3912067700000001
summary_value_count = 1818
instance_scale = 0.25
instance_count = 0
format_name = 'sample_summary{:04d}'.format(endpointNum)
format_desc = 'sample_summary{:04d} instance scale {} value scale {}'.format(endpointNum, instance_scale, summary_value_q0)
format_count = '{:d}'.format((int(iteration) * int(summary_value_count)))
format_sum = '{:16f}'.format((int(iteration) * float(summary_value_sum)))
summary_string = {'name': 'my.summary', 'description': '', 'unit': '', 'summary': {'dataPoints': [{'attributes': [{'key': 'labels', 'value': {'stringValue': 'some.interesting.labels'}}], 'timeUnixNano': 1741190626268846852, 'count': 1, 'sum': 99.9, 'quantileValues': []}]}}
points = summary_string['summary']['dataPoints'][0]
summary_string['name'] = format_name
summary_string['description'] = format_desc
points["count"] = format_count
points["sum"] = format_sum
for i in range(instances):
points["quantileValues"].append({'quantile': (i * instance_scale), 'value': (int(iteration) * instance_count * float(summary_value_q0))})
instance_count += 1
return summary_string
def sample_histogram_data(self, iteration=None, instances=None, metrics=None, endpointNum=None):
histogram_value_l1 = 5945
histogram_value_sum = 45157
histogram_value_count = 18135
instance_scale = 2
instance_count = 0
format_name = 'sample_histogram{:04d}'.format(endpointNum)
format_desc = 'sample_histogram{:04d} instance scale {} value scale {} (sample histogram has instances)'.format(endpointNum, instance_scale, histogram_value_l1)
format_count = "{:d}".format((int(instances) * int(histogram_value_count)))
format_sum = "{:d}".format((int(instances) * int(histogram_value_sum)))
histogram_string = {'name': 'my.histogram', 'description': '', 'unit': '', 'histogram': {'dataPoints': [{'attributes': [{}], 'timeUnixNano': 1741190626268846852, 'count': 1, 'sum': 99.9, 'bucketCounts': [], 'explicitBounds': [], 'min': 99.9, 'max': 99.9, 'exemplars': []}], 'aggregationTemporality': 2}}
points = histogram_string['histogram']['dataPoints'][0]
histogram_string['name'] = format_name
histogram_string['description'] = format_desc
points["count"] = format_count
points["sum"] = format_sum
for i in range(instances):
points["bucketCounts"].append((int(iteration) * instance_count * histogram_value_l1))
points["explicitBounds"].append((i * instance_scale))
instance_count += 1
points["bucketCounts"].append(0)
return histogram_string
def start_string(self):
start = {'resourceMetrics': [{'resource': {'attributes': [{'key': 'service.name', 'value': {'stringValue': 'my.service'}}]}, 'scopeMetrics': [{'scope': {'name': 'my.library', 'version': '1.0.0', 'attributes': [{'key': 'my.scope.attribute', 'value': {'stringValue': 'some.scope.attribute'}}]}, 'metrics': []}]}]}
return start
def format_opentelemetry_output(self, metrics=None, iteration=None, instances=None, error=None, endpointNum=None):
metrics_remaining = metrics
endpoint_string = self.start_string()
helper = endpoint_string['resourceMetrics'][0]['scopeMetrics'][0]['metrics']
while metrics_remaining >= 0:
helper.append(self.sample_gauge_data(iteration, instances, metrics_remaining, (metrics-metrics_remaining)))
metrics_remaining -= 1
iteration += 1
if metrics_remaining <= 0:
break
helper.append(self.sample_counter_data(iteration, instances, metrics_remaining, (metrics-metrics_remaining)))
metrics_remaining -= 1
iteration += 1
if metrics_remaining <= 0:
break
helper.append(self.sample_summary_data(iteration, instances, metrics_remaining, (metrics-metrics_remaining)))
# metrics_remaining -= 4
metrics_remaining -= instances
iteration += 1
if metrics_remaining <= 0:
break
helper.append(self.sample_histogram_data(iteration, instances, metrics_remaining, (metrics-metrics_remaining)))
# metrics_remaining -= 5
metrics_remaining -= instances
iteration += 1
endpoint_string = json.dumps(endpoint_string, sort_keys=False, indent=4, separators=(',', ': '))
if error is not None:
return endpoint_string[:int(len(endpoint_string)/int(error))]
else:
return endpoint_string
def do_GET(self):
time.sleep(float(self.server.args.delay))
if len(activeEndpoint) > 0:
endpoint_regex = re.compile(str(self.server.args.url))
iteration = re.split(endpoint_regex, self.path)
if len(iteration) > 1 and int(iteration[1]) in activeEndpoint:
endpointNum = int(iteration[1])
if int(self.server.args.error) and not activeEndpoint[endpointNum] % int(self.server.args.error) and activeEndpoint[endpointNum]:
error = int(self.server.args.error)
else:
error = None
self.send_response(200)
self.end_headers()
self.wfile.write(self.format_opentelemetry_output(int(self.server.args.metrics), endpointNum*(activeEndpoint[endpointNum]), int(self.server.args.instances), error, endpointNum).encode()) # multiply by activeendpoint value or something?
self.server.lock.acquire()
try:
activeEndpoint[endpointNum] += 1
if activeEndpoint[endpointNum] >= int(self.server.args.limit):
del activeEndpoint[endpointNum] #do we even really need to do this?
self.server.pqueue.task_done()
try:
_next = self.server.pqueue.get_nowait()
activeEndpoint[int(_next)] = 0
write_endpoint_metadata(self.server.args, _next)
except queue.Empty:
pass
finally:
self.server.lock.release()
else:
self.send_error(404)
return
class PrometheusEndpoint(threading.Thread):
def __init__(self, pqueue=None, args=None):
threading.Thread.__init__(self)
self.daemon = True
self.pqueue = pqueue
self.args = args
self.lock = threading.Lock()
self.server = None
self.start()
def run(self):
try:
endpoint = self.pqueue.get_nowait()
self.lock.acquire()
try:
activeEndpoint[endpoint] = 0
write_endpoint_metadata(self.args, endpoint)
finally:
self.lock.release()
except queue.Empty:
pass
finally:
httpd = HTTPServer(self.args.addr, FakeEndpoint, False)
httpd.socket = self.args.sock
httpd.pqueue = self.pqueue
httpd.delay = self.args.delay
httpd.args = self.args
httpd.server_bind = self.server_close = lambda self: None
httpd.lock = self.lock
self.server = httpd
self.server.serve_forever()
def parsing():
parser = argparse.ArgumentParser(description='Setup a number of fake opentelemetry endpoints for collection.')
parser.add_argument('--endpoints', default=2, help='number of opentelemetry endpoints to start at once')
parser.add_argument('--metrics', default=5, help='number of metrics per opentelemetry endpoint')
parser.add_argument('--instances', default=5, help='number of instances per metric')
parser.add_argument('--delay', default=0, help='delay time (seconds) for each "slow" node')
parser.add_argument('--limit', default=5, help='number of iterations/responses each endpoint limits itself to')
parser.add_argument('--total', default=5, help='total number of endpoints to run')
parser.add_argument('--port', default=10000, help='port to start fake endpoints on')
parser.add_argument('--error', default=0, help='create errornous data in opentelemetry endpoints')
parser.add_argument('--url', default="foo&endpoint=", help='url for the endpoint, the endpoint number must be the last part')
parser.add_argument('--output', default="/tmp", help='directory to create endpoint metadata in')
args = parser.parse_args()
return args
if __name__ == '__main__':
args = parsing()
pendpointQueue = queue.Queue()
addr = ('', int(args.port))
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
sock.bind(addr)
sock.listen(int(args.port))
args.addr = addr
args.sock = sock
for endpoint in range(int(args.total)):
pendpointQueue.put(endpoint)
pendpoints = [PrometheusEndpoint(pendpointQueue, args)
for i in range(int(args.endpoints))]
pendpointQueue.join()
sock.close()
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