tools/gcp/stress_test/run_client.py - platform/external/grpc-grpc - Gitiles

 #!/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()
	#!/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()