Initial checkin of gRPC to third_party/

third_party/grpc/tools/gcp/stress_test/run_client.py

+#!/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 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
+  """
+  env = dict(os.environ)
+  image_type = env['STRESS_TEST_IMAGE_TYPE']
+  image_name = env['STRESS_TEST_IMAGE']
+  args_str = env['STRESS_TEST_ARGS_STR']
+  metrics_client_image = env['METRICS_CLIENT_IMAGE']
+  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']
+
+  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')
+
+  # Update status that the test is starting (in the status table)
+  bq_helper.insert_summary_row(EventType.STARTING, details)
+
+  metrics_cmd = [metrics_client_image
+                ] + [x for x in metrics_client_args_str.split()]
+  stress_cmd = [image_name] + [x for x in args_str.split()]
+
+  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_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:
+      end_time = datetime.datetime.now().isoformat()
+      event_type = EventType.SUCCESS
+      details = 'End time: %s' % end_time
+      if 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
+
+    # 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()