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#!/usr/bin/env python2.7
# Copyright 2015-2016, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following disclaimer
# in the documentation and/or other materials provided with the
# distribution.
# * Neither the name of Google Inc. nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import datetime
import os
import re
import resource
import select
import subprocess
import sys
import time
from stress_test_utils import EventType
from stress_test_utils import BigQueryHelper
# TODO (sree): Write a python grpc client to directly query the metrics instead
# of calling metrics_client
def _get_qps(metrics_cmd):
qps = 0
try:
# Note: gpr_log() writes even non-error messages to stderr stream. So it is
# important that we set stderr=subprocess.STDOUT
p = subprocess.Popen(args=metrics_cmd,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
retcode = p.wait()
(out_str, err_str) = p.communicate()
if retcode != 0:
print 'Error in reading metrics information'
print 'Output: ', out_str
else:
# The overall qps is printed at the end of the line
m = re.search('\d+$', out_str)
qps = int(m.group()) if m else 0
except Exception as ex:
print 'Exception while reading metrics information: ' + str(ex)
return qps
def run_client():
"""This is a wrapper around the stress test client and performs the following:
1) Create the following two tables in Big Query:
(i) Summary table: To record events like the test started, completed
successfully or failed
(ii) Qps table: To periodically record the QPS sent by this client
2) Start the stress test client and add a row in the Big Query summary
table
3) Once every few seconds (as specificed by the poll_interval_secs) poll
the status of the stress test client process and perform the
following:
3.1) If the process is still running, get the current qps by invoking
the metrics client program and add a row in the Big Query
Qps table. Sleep for a duration specified by poll_interval_secs
3.2) If the process exited successfully, add a row in the Big Query
Summary table and exit
3.3) If the process failed, add a row in Big Query summary table and
wait forever.
NOTE: This script typically runs inside a GKE pod which means
that the pod gets destroyed when the script exits. However, in
case the stress test client fails, we would not want the pod to
be destroyed (since we might want to connect to the pod for
examining logs). This is the reason why the script waits forever
in case of failures
"""
# Set the 'core file' size to 'unlimited' so that 'core' files are generated
# if the client crashes (Note: This is not relevant for Java and Go clients)
resource.setrlimit(resource.RLIMIT_CORE,
(resource.RLIM_INFINITY, resource.RLIM_INFINITY))
env = dict(os.environ)
image_type = env['STRESS_TEST_IMAGE_TYPE']
stress_client_cmd = env['STRESS_TEST_CMD'].split()
args_str = env['STRESS_TEST_ARGS_STR']
metrics_client_cmd = env['METRICS_CLIENT_CMD'].split()
metrics_client_args_str = env['METRICS_CLIENT_ARGS_STR']
run_id = env['RUN_ID']
pod_name = env['POD_NAME']
logfile_name = env.get('LOGFILE_NAME')
poll_interval_secs = float(env['POLL_INTERVAL_SECS'])
project_id = env['GCP_PROJECT_ID']
dataset_id = env['DATASET_ID']
summary_table_id = env['SUMMARY_TABLE_ID']
qps_table_id = env['QPS_TABLE_ID']
# The following parameter is to inform us whether the stress client runs
# forever until forcefully stopped or will it naturally stop after sometime.
# This way, we know that the stress client process should not terminate (even
# if it does with a success exit code) and flag the termination as a failure
will_run_forever = env.get('WILL_RUN_FOREVER', '1')
bq_helper = BigQueryHelper(run_id, image_type, pod_name, project_id,
dataset_id, summary_table_id, qps_table_id)
bq_helper.initialize()
# Create BigQuery Dataset and Tables: Summary Table and Metrics Table
if not bq_helper.setup_tables():
print 'Error in creating BigQuery tables'
return
start_time = datetime.datetime.now()
logfile = None
details = 'Logging to stdout'
if logfile_name is not None:
print 'Opening logfile: %s ...' % logfile_name
details = 'Logfile: %s' % logfile_name
logfile = open(logfile_name, 'w')
metrics_cmd = metrics_client_cmd + [x
for x in metrics_client_args_str.split()]
stress_cmd = stress_client_cmd + [x for x in args_str.split()]
details = '%s, Metrics command: %s, Stress client command: %s' % (
details, str(metrics_cmd), str(stress_cmd))
# Update status that the test is starting (in the status table)
bq_helper.insert_summary_row(EventType.STARTING, details)
print 'Launching process %s ...' % stress_cmd
stress_p = subprocess.Popen(args=stress_cmd,
stdout=logfile,
stderr=subprocess.STDOUT)
qps_history = [1, 1, 1] # Maintain the last 3 qps readings
qps_history_idx = 0 # Index into the qps_history list
is_running_status_written = False
is_error = False
while True:
# Check if stress_client is still running. If so, collect metrics and upload
# to BigQuery status table
# If stress_p.poll() is not None, it means that the stress client terminated
if stress_p.poll() is not None:
end_time = datetime.datetime.now().isoformat()
event_type = EventType.SUCCESS
details = 'End time: %s' % end_time
if will_run_forever == '1' or stress_p.returncode != 0:
event_type = EventType.FAILURE
details = 'Return code = %d. End time: %s' % (stress_p.returncode,
end_time)
is_error = True
bq_helper.insert_summary_row(event_type, details)
print details
break
if not is_running_status_written:
bq_helper.insert_summary_row(EventType.RUNNING, '')
is_running_status_written = True
# Stress client still running. Get metrics
qps = _get_qps(metrics_cmd)
qps_recorded_at = datetime.datetime.now().isoformat()
print 'qps: %d at %s' % (qps, qps_recorded_at)
# If QPS has been zero for the last 3 iterations, flag it as error and exit
qps_history[qps_history_idx] = qps
qps_history_idx = (qps_history_idx + 1) % len(qps_history)
if sum(qps_history) == 0:
details = 'QPS has been zero for the last %d seconds - as of : %s' % (
poll_interval_secs * 3, qps_recorded_at)
is_error = True
bq_helper.insert_summary_row(EventType.FAILURE, details)
print details
break
# Upload qps metrics to BiqQuery
bq_helper.insert_qps_row(qps, qps_recorded_at)
time.sleep(poll_interval_secs)
if is_error:
print 'Waiting indefinitely..'
select.select([], [], [])
print 'Completed'
return
if __name__ == '__main__':
run_client()
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