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Significantly rewrite tools/gke/run_stress_tests_on_gke.py and make

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everything configurable
pull/5402/head
Sree Kuchibhotla 9 years ago
parent f63c49238e
commit 61c134f5f8
2 changed files with 387 additions and 201 deletions
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  1. 47
      tools/gke/kubernetes_api.py
  2. 497
      tools/gke/run_stress_tests_on_gke.py

47
tools/gke/kubernetes_api.py
Unescape View File

@ -50,7 +50,8 @@ def _make_pod_config(pod_name, image_name, container_port_list, cmd_list,
'name': pod_name,
'image': image_name,
'ports': [{'containerPort': port,
'protocol': 'TCP'} for port in container_port_list],
'protocol': 'TCP'}
for port in container_port_list],
'imagePullPolicy': 'Always'
}
]
@ -222,3 +223,47 @@ def delete_pod(kube_host, kube_port, namespace, pod_name):
del_url = 'http://%s:%d/api/v1/namespaces/%s/pods/%s' % (kube_host, kube_port,
namespace, pod_name)
return _do_delete(del_url, 'Delete Pod')
def create_pod_and_service(kube_host, kube_port, namespace, pod_name,
image_name, container_port_list, cmd_list, arg_list,
env_dict, is_headless_service):
"""A simple helper function that creates a pod and a service (if pod creation was successful)."""
is_success = create_pod(kube_host, kube_port, namespace, pod_name, image_name,
container_port_list, cmd_list, arg_list, env_dict)
if not is_success:
print 'Error in creating Pod'
return False
is_success = create_service(
kube_host,
kube_port,
namespace,
pod_name, # Use pod_name for service
pod_name,
container_port_list, # Service port list same as container port list
container_port_list,
is_headless_service)
if not is_success:
print 'Error in creating Service'
return False
print 'Successfully created the pod/service %s' % pod_name
return True
def delete_pod_and_service(kube_host, kube_port, namespace, pod_name):
""" A simple helper function that calls delete_pod and delete_service """
is_success = delete_pod(kube_host, kube_port, namespace, pod_name)
if not is_success:
print 'Error in deleting pod %s' % pod_name
return False
# Note: service name assumed to the the same as pod name
is_success = delete_service(kube_host, kube_port, namespace, pod_name)
if not is_success:
print 'Error in deleting service %s' % pod_name
return False
print 'Successfully deleted the Pod/Service: %s' % pod_name
return True

497
tools/gke/run_stress_tests_on_gke.py
Unescape View File

@ -27,6 +27,7 @@
# 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 argparse
import datetime
import os
import subprocess
@ -40,17 +41,52 @@ from stress_test_utils import BigQueryHelper
import kubernetes_api
GRPC_ROOT = os.path.abspath(os.path.join(os.path.dirname(sys.argv[0]), '../..'))
os.chdir(GRPC_ROOT)
_GRPC_ROOT = os.path.abspath(os.path.join(
os.path.dirname(sys.argv[0]), '../..'))
os.chdir(_GRPC_ROOT)
# num of seconds to wait for the GKE image to start and warmup
_GKE_IMAGE_WARMUP_WAIT_SECS = 60
class BigQuerySettings:
_SERVER_POD_NAME = 'stress-server'
_CLIENT_POD_NAME_PREFIX = 'stress-client'
_DATASET_ID_PREFIX = 'stress_test'
_SUMMARY_TABLE_ID = 'summary'
_QPS_TABLE_ID = 'qps'
def __init__(self, run_id, dataset_id, summary_table_id, qps_table_id):
self.run_id = run_id
self.dataset_id = dataset_id
self.summary_table_id = summary_table_id
self.qps_table_id = qps_table_id
_DEFAULT_DOCKER_IMAGE_NAME = 'grpc_stress_test'
# The default port on which the kubernetes proxy server is started on localhost
# (i.e kubectl proxy --port=<port>)
_DEFAULT_KUBERNETES_PROXY_PORT = 8001
# How frequently should the stress client wrapper script (running inside a GKE
# container) poll the health of the stress client (also running inside the GKE
# container) and upload metrics to BigQuery
_DEFAULT_STRESS_CLIENT_POLL_INTERVAL_SECS = 60
# The default setting for stress test server and client
_DEFAULT_STRESS_SERVER_PORT = 8080
_DEFAULT_METRICS_PORT = 8081
_DEFAULT_TEST_CASES_STR = 'empty_unary:1,large_unary:1,client_streaming:1,server_streaming:1,empty_stream:1'
_DEFAULT_NUM_CHANNELS_PER_SERVER = 5
_DEFAULT_NUM_STUBS_PER_CHANNEL = 10
_DEFAULT_METRICS_COLLECTION_INTERVAL_SECS = 30
# Number of stress client instances to launch
_DEFAULT_NUM_CLIENTS = 3
# How frequently should this test monitor the health of Stress clients and
# Servers running in GKE
_DEFAULT_TEST_POLL_INTERVAL_SECS = 60
# Default run time for this test (2 hour)
_DEFAULT_TEST_DURATION_SECS = 7200
# The number of seconds it would take a GKE pod to warm up (i.e get to 'Running'
# state from the time of creation). Ideally this is something the test should
# automatically determine by using Kubernetes API to poll the pods status.
_DEFAULT_GKE_WARMUP_SECS = 60
class KubernetesProxy:
@ -76,11 +112,74 @@ class KubernetesProxy:
def __del__(self):
if self.p is not None:
print 'Shutting down Kubernetes proxy..'
self.p.kill()
class TestSettings:
def __init__(self, build_docker_image, test_poll_interval_secs,
test_duration_secs, kubernetes_proxy_port):
self.build_docker_image = build_docker_image
self.test_poll_interval_secs = test_poll_interval_secs
self.test_duration_secs = test_duration_secs
self.kubernetes_proxy_port = kubernetes_proxy_port
class GkeSettings:
def __init__(self, project_id, docker_image_name):
self.project_id = project_id
self.docker_image_name = docker_image_name
self.tag_name = 'gcr.io/%s/%s' % (project_id, docker_image_name)
class BigQuerySettings:
def __init__(self, run_id, dataset_id, summary_table_id, qps_table_id):
self.run_id = run_id
self.dataset_id = dataset_id
self.summary_table_id = summary_table_id
self.qps_table_id = qps_table_id
class StressServerSettings:
def __init__(self, server_pod_name, server_port):
self.server_pod_name = server_pod_name
self.server_port = server_port
class StressClientSettings:
def __init__(self, num_clients, client_pod_name_prefix, server_pod_name,
server_port, metrics_port, metrics_collection_interval_secs,
stress_client_poll_interval_secs, num_channels_per_server,
num_stubs_per_channel, test_cases_str):
self.num_clients = num_clients
self.client_pod_name_prefix = client_pod_name_prefix
self.server_pod_name = server_pod_name
self.server_port = server_port
self.metrics_port = metrics_port
self.metrics_collection_interval_secs = metrics_collection_interval_secs
self.stress_client_poll_interval_secs = stress_client_poll_interval_secs
self.num_channels_per_server = num_channels_per_server
self.num_stubs_per_channel = num_stubs_per_channel
self.test_cases_str = test_cases_str
# == Derived properties ==
# Note: Client can accept a list of server addresses (a comma separated list
# of 'server_name:server_port'). In this case, we only have one server
# address to pass
self.server_addresses = '%s.default.svc.cluster.local:%d' % (
server_pod_name, server_port)
self.client_pod_names_list = ['%s-%d' % (client_pod_name_prefix, i)
for i in range(1, num_clients + 1)]
def _build_docker_image(image_name, tag_name):
""" Build the docker image and add a tag """
print 'Building docker image: %s' % image_name
os.environ['INTEROP_IMAGE'] = image_name
# Note that 'BASE_NAME' HAS to be 'grpc_interop_stress_cxx' since the script
# build_interop_stress_image.sh invokes the following script:
@ -93,6 +192,7 @@ def _build_docker_image(image_name, tag_name):
print 'Error in building docker image'
return False
print 'Adding an additional tag %s to the image %s' % (tag_name, image_name)
cmd = ['docker', 'tag', '-f', image_name, tag_name]
p = subprocess.Popen(args=cmd)
retcode = p.wait()
@ -115,144 +215,86 @@ def _push_docker_image_to_gke_registry(docker_tag_name):
return True
def _launch_image_on_gke(kubernetes_api_server, kubernetes_api_port, namespace,
pod_name, image_name, port_list, cmd_list, arg_list,
env_dict, is_headless_service):
"""Creates a GKE Pod and a Service object for a given image by calling Kubernetes API"""
is_success = kubernetes_api.create_pod(
kubernetes_api_server,
kubernetes_api_port,
namespace,
pod_name,
image_name,
port_list, # The ports to be exposed on this container/pod
cmd_list, # The command that launches the stress server
arg_list,
env_dict # Environment variables to be passed to the pod
)
if not is_success:
print 'Error in creating Pod'
return False
is_success = kubernetes_api.create_service(
kubernetes_api_server,
kubernetes_api_port,
namespace,
pod_name, # Use the pod name for service name as well
pod_name,
port_list, # Service port list
port_list, # Container port list (same as service port list)
is_headless_service)
if not is_success:
print 'Error in creating Service'
return False
print 'Successfully created the pod/service %s' % pod_name
return True
def _delete_image_on_gke(kubernetes_proxy, pod_name_list):
"""Deletes a GKE Pod and Service object for given list of Pods by calling Kubernetes API"""
if not kubernetes_proxy.is_started:
print 'Kubernetes proxy must be started before calling this function'
return False
is_success = True
for pod_name in pod_name_list:
is_success = kubernetes_api.delete_pod(
'localhost', kubernetes_proxy.get_port(), 'default', pod_name)
if not is_success:
print 'Error in deleting pod %s' % pod_name
break
is_success = kubernetes_api.delete_service(
'localhost', kubernetes_proxy.get_port(), 'default',
pod_name) # service name same as pod name
if not is_success:
print 'Error in deleting service %s' % pod_name
break
if is_success:
print 'Successfully deleted the Pods/Services: %s' % ','.join(pod_name_list)
return is_success
def _launch_server(gcp_project_id, docker_image_name, bq_settings,
kubernetes_proxy, server_pod_name, server_port):
def _launch_server(gke_settings, stress_server_settings, bq_settings,
kubernetes_proxy):
""" Launches a stress test server instance in GKE cluster """
if not kubernetes_proxy.is_started:
print 'Kubernetes proxy must be started before calling this function'
return False
# This is the wrapper script that is run in the container. This script runs
# the actual stress test server
server_cmd_list = [
'/var/local/git/grpc/tools/run_tests/stress_test/run_server.py'
] # Process that is launched
server_arg_list = [] # run_server.py does not take any args (for now)
]
# run_server.py does not take any args from the command line. The args are
# instead passed via environment variables (see server_env below)
server_arg_list = []
# == Parameters to the server process launched in GKE ==
# The parameters to the script run_server.py are injected into the container
# via environment variables
server_env = {
'STRESS_TEST_IMAGE_TYPE': 'SERVER',
'STRESS_TEST_IMAGE': '/var/local/git/grpc/bins/opt/interop_server',
'STRESS_TEST_ARGS_STR': '--port=%s' % server_port,
'STRESS_TEST_ARGS_STR': '--port=%s' % stress_server_settings.server_port,
'RUN_ID': bq_settings.run_id,
'POD_NAME': server_pod_name,
'GCP_PROJECT_ID': gcp_project_id,
'POD_NAME': stress_server_settings.server_pod_name,
'GCP_PROJECT_ID': gke_settings.project_id,
'DATASET_ID': bq_settings.dataset_id,
'SUMMARY_TABLE_ID': bq_settings.summary_table_id,
'QPS_TABLE_ID': bq_settings.qps_table_id
}
# Launch Server
is_success = _launch_image_on_gke(
is_success = kubernetes_api.create_pod_and_service(
'localhost',
kubernetes_proxy.get_port(),
'default',
server_pod_name,
docker_image_name,
[server_port], # Port that should be exposed on the container
'default', # Use 'default' namespace
stress_server_settings.server_pod_name,
gke_settings.tag_name,
[stress_server_settings.server_port], # Port that should be exposed
server_cmd_list,
server_arg_list,
server_env,
True # Headless = True for server. Since we want DNS records to be greated by GKE
True # Headless = True for server. Since we want DNS records to be created by GKE
)
return is_success
def _launch_client(gcp_project_id, docker_image_name, bq_settings,
kubernetes_proxy, num_instances, client_pod_name_prefix,
server_pod_name, server_port):
def _launch_client(gke_settings, stress_server_settings, stress_client_settings,
bq_settings, kubernetes_proxy):
""" Launches a configurable number of stress test clients on GKE cluster """
if not kubernetes_proxy.is_started:
print 'Kubernetes proxy must be started before calling this function'
return False
server_address = '%s.default.svc.cluster.local:%d' % (server_pod_name,
server_port)
#TODO(sree) Make the whole client args configurable
test_cases_str = 'empty_unary:1,large_unary:1'
stress_client_arg_list = [
'--server_addresses=%s' % server_address,
'--test_cases=%s' % test_cases_str, '--num_stubs_per_channel=10'
'--server_addresses=%s' % stress_client_settings.server_addresses,
'--test_cases=%s' % stress_client_settings.test_cases_str,
'--num_stubs_per_channel=%d' %
stress_client_settings.num_stubs_per_channel
]
# This is the wrapper script that is run in the container. This script runs
# the actual stress client
client_cmd_list = [
'/var/local/git/grpc/tools/run_tests/stress_test/run_client.py'
]
# run_client.py takes no args. All args are passed as env variables
client_arg_list = []
# TODO(sree) Make this configurable (and also less frequent)
poll_interval_secs = 30
# run_client.py takes no args. All args are passed as env variables (see
# client_env)
client_arg_list = []
metrics_port = 8081
metrics_server_address = 'localhost:%d' % metrics_port
metrics_server_address = 'localhost:%d' % stress_client_settings.metrics_port
metrics_client_arg_list = [
'--metrics_server_address=%s' % metrics_server_address,
'--total_only=true'
]
# The parameters to the script run_client.py are injected into the container
# via environment variables
client_env = {
'STRESS_TEST_IMAGE_TYPE': 'CLIENT',
'STRESS_TEST_IMAGE': '/var/local/git/grpc/bins/opt/stress_test',
@ -260,27 +302,28 @@ def _launch_client(gcp_project_id, docker_image_name, bq_settings,
'METRICS_CLIENT_IMAGE': '/var/local/git/grpc/bins/opt/metrics_client',
'METRICS_CLIENT_ARGS_STR': ' '.join(metrics_client_arg_list),
'RUN_ID': bq_settings.run_id,
'POLL_INTERVAL_SECS': str(poll_interval_secs),
'GCP_PROJECT_ID': gcp_project_id,
'POLL_INTERVAL_SECS':
str(stress_client_settings.stress_client_poll_interval_secs),
'GCP_PROJECT_ID': gke_settings.project_id,
'DATASET_ID': bq_settings.dataset_id,
'SUMMARY_TABLE_ID': bq_settings.summary_table_id,
'QPS_TABLE_ID': bq_settings.qps_table_id
}
for i in range(1, num_instances + 1):
pod_name = '%s-%d' % (client_pod_name_prefix, i)
for pod_name in stress_client_settings.client_pod_names_list:
client_env['POD_NAME'] = pod_name
is_success = _launch_image_on_gke(
'localhost',
is_success = kubernetes_api.create_pod_and_service(
'localhost', # Since proxy is running on localhost
kubernetes_proxy.get_port(),
'default',
'default', # default namespace
pod_name,
docker_image_name,
[metrics_port], # Client pods expose metrics port
gke_settings.tag_name,
[stress_client_settings.metrics_port
], # Client pods expose metrics port
client_cmd_list,
client_arg_list,
client_env,
False # Client is not a headless service.
False # Client is not a headless service
)
if not is_success:
print 'Error in launching client %s' % pod_name
@ -289,20 +332,17 @@ def _launch_client(gcp_project_id, docker_image_name, bq_settings,
return True
def _launch_server_and_client(bq_settings, gcp_project_id, docker_image_name,
num_client_instances):
def _launch_server_and_client(gke_settings, stress_server_settings,
stress_client_settings, bq_settings,
kubernetes_proxy_port):
# Start kubernetes proxy
kubernetes_api_port = 9001
kubernetes_proxy = KubernetesProxy(kubernetes_api_port)
print 'Kubernetes proxy'
kubernetes_proxy = KubernetesProxy(kubernetes_proxy_port)
kubernetes_proxy.start()
# num of seconds to wait for the GKE image to start and warmup
image_warmp_secs = 60
server_pod_name = 'stress-server'
server_port = 8080
is_success = _launch_server(gcp_project_id, docker_image_name, bq_settings,
kubernetes_proxy, server_pod_name, server_port)
print 'Launching server..'
is_success = _launch_server(gke_settings, stress_server_settings, bq_settings,
kubernetes_proxy)
if not is_success:
print 'Error in launching server'
return False
@ -310,90 +350,87 @@ def _launch_server_and_client(bq_settings, gcp_project_id, docker_image_name,
# Server takes a while to start.
# TODO(sree) Use Kubernetes API to query the status of the server instead of
# sleeping
print 'Waiting for %s seconds for the server to start...' % image_warmp_secs
time.sleep(image_warmp_secs)
print 'Waiting for %s seconds for the server to start...' % _GKE_IMAGE_WARMUP_WAIT_SECS
time.sleep(_GKE_IMAGE_WARMUP_WAIT_SECS)
# Launch client
server_address = '%s.default.svc.cluster.local:%d' % (server_pod_name,
server_port)
client_pod_name_prefix = 'stress-client'
is_success = _launch_client(gcp_project_id, docker_image_name, bq_settings,
kubernetes_proxy, num_client_instances,
client_pod_name_prefix, server_pod_name,
server_port)
is_success = _launch_client(gke_settings, stress_server_settings,
stress_client_settings, bq_settings,
kubernetes_proxy)
if not is_success:
print 'Error in launching client(s)'
return False
print 'Waiting for %s seconds for the client images to start...' % image_warmp_secs
time.sleep(image_warmp_secs)
print 'Waiting for %s seconds for the client images to start...' % _GKE_IMAGE_WARMUP_WAIT_SECS
time.sleep(_GKE_IMAGE_WARMUP_WAIT_SECS)
return True
def _delete_server_and_client(num_client_instances):
kubernetes_api_port = 9001
kubernetes_proxy = KubernetesProxy(kubernetes_api_port)
def _delete_server_and_client(stress_server_settings, stress_client_settings,
kubernetes_proxy_port):
kubernetes_proxy = KubernetesProxy(kubernetes_proxy_port)
kubernetes_proxy.start()
# Delete clients first
client_pod_names = ['stress-client-%d' % i
for i in range(1, num_client_instances + 1)]
is_success = _delete_image_on_gke(kubernetes_proxy, client_pod_names)
is_success = True
for pod_name in stress_client_settings.client_pod_names_list:
is_success = kubernetes_api.delete_pod_and_service(
'localhost', kubernetes_proxy_port, 'default', pod_name)
if not is_success:
return False
# Delete server
server_pod_name = 'stress-server'
return _delete_image_on_gke(kubernetes_proxy, [server_pod_name])
is_success = kubernetes_api.delete_pod_and_service(
'localhost', kubernetes_proxy_port, 'default',
stress_server_settings.server_pod_name)
return is_success
def _build_and_push_docker_image(gcp_project_id, docker_image_name, tag_name):
is_success = _build_docker_image(docker_image_name, tag_name)
if not is_success:
return False
return _push_docker_image_to_gke_registry(tag_name)
def run_test_main(test_settings, gke_settings, stress_server_settings,
stress_client_clients):
is_success = True
# TODO(sree): This is just to test the above APIs. Rewrite this to make
# everything configurable (like image names / number of instances etc)
def run_test(skip_building_image, gcp_project_id, image_name, tag_name,
num_client_instances, poll_interval_secs, total_duration_secs):
if not skip_building_image:
is_success = _build_docker_image(image_name, tag_name)
if test_settings.build_docker_image:
is_success = _build_docker_image(gke_settings.docker_image_name,
gke_settings.tag_name)
if not is_success:
return False
is_success = _push_docker_image_to_gke_registry(tag_name)
is_success = _push_docker_image_to_gke_registry(gke_settings.tag_name)
if not is_success:
return False
# == Big Query tables related settings (Common for both server and client) ==
# Create a unique id for this run (Note: Using timestamp instead of UUID to
# make it easier to deduce the date/time of the run just by looking at the run
# run id. This is useful in debugging when looking at records in Biq query)
run_id = datetime.datetime.now().strftime('%Y_%m_%d_%H_%M_%S')
dataset_id = 'stress_test_%s' % run_id
summary_table_id = 'summary'
qps_table_id = 'qps'
bq_settings = BigQuerySettings(run_id, dataset_id, summary_table_id,
qps_table_id)
bq_helper = BigQueryHelper(run_id, '', '', gcp_project_id, dataset_id,
summary_table_id, qps_table_id)
dataset_id = '%s_%s' % (_DATASET_ID_PREFIX, run_id)
# Big Query settings (common for both Stress Server and Client)
bq_settings = BigQuerySettings(run_id, dataset_id, _SUMMARY_TABLE_ID,
_QPS_TABLE_ID)
bq_helper = BigQueryHelper(run_id, '', '', args.project_id, dataset_id,
_SUMMARY_TABLE_ID, _QPS_TABLE_ID)
bq_helper.initialize()
is_success = _launch_server_and_client(bq_settings, gcp_project_id, tag_name,
num_client_instances)
try:
is_success = _launch_server_and_client(gke_settings, stress_server_settings,
stress_client_settings, bq_settings,
test_settings.kubernetes_proxy_port)
if not is_success:
return False
start_time = datetime.datetime.now()
end_time = start_time + datetime.timedelta(seconds=total_duration_secs)
end_time = start_time + datetime.timedelta(
seconds=test_settings.test_duration_secs)
print 'Running the test until %s' % end_time.isoformat()
while True:
if datetime.datetime.now() > end_time:
print 'Test was run for %d seconds' % total_duration_secs
print 'Test was run for %d seconds' % test_settings.test_duration_secs
break
# Check if either stress server or clients have failed
@ -401,25 +438,129 @@ def run_test(skip_building_image, gcp_project_id, image_name, tag_name,
is_success = False
print 'Some tests failed.'
break
# Things seem to be running fine. Wait until next poll time to check the
# status
print 'Sleeping for %d seconds..' % poll_interval_secs
time.sleep(poll_interval_secs)
print 'Sleeping for %d seconds..' % test_settings.test_poll_interval_secs
time.sleep(test_settings.test_poll_interval_secs)
# Print BiqQuery tables
bq_helper.print_summary_records()
bq_helper.print_qps_records()
_delete_server_and_client(num_client_instances)
finally:
# If is_success is False at this point, it means that the stress tests were
# started successfully but failed while running the tests. In this case we
# do should not delete the pods (since they contain all the failure
# information)
if is_success:
_delete_server_and_client(stress_server_settings, stress_client_settings,
test_settings.kubernetes_proxy_port)
return is_success
argp = argparse.ArgumentParser(
description='Launch stress tests in GKE',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
argp.add_argument('--project_id',
required=True,
help='The Google Cloud Platform Project Id')
argp.add_argument('--num_clients',
default=1,
type=int,
help='Number of client instances to start')
argp.add_argument('--docker_image_name',
default=_DEFAULT_DOCKER_IMAGE_NAME,
help='The name of the docker image containing stress client '
'and stress servers')
argp.add_argument('--build_docker_image',
dest='build_docker_image',
action='store_true',
help='Build a docker image and push to Google Container '
'Registry')
argp.add_argument('--do_not_build_docker_image',
dest='build_docker_image',
action='store_false',
help='Do not build and push docker image to Google Container '
'Registry')
argp.set_defaults(build_docker_image=True)
argp.add_argument('--test_poll_interval_secs',
default=_DEFAULT_TEST_POLL_INTERVAL_SECS,
type=int,
help='How frequently should this script should monitor the '
'health of stress clients and servers running in the GKE '
'cluster')
argp.add_argument('--test_duration_secs',
default=_DEFAULT_TEST_DURATION_SECS,
type=int,
help='How long should this test be run')
argp.add_argument('--kubernetes_proxy_port',
default=_DEFAULT_KUBERNETES_PROXY_PORT,
type=int,
help='The port on which the kubernetes proxy (on localhost)'
' is started')
argp.add_argument('--stress_server_port',
default=_DEFAULT_STRESS_SERVER_PORT,
type=int,
help='The port on which the stress server (in GKE '
'containers) listens')
argp.add_argument('--stress_client_metrics_port',
default=_DEFAULT_METRICS_PORT,
type=int,
help='The port on which the stress clients (in GKE '
'containers) expose metrics')
argp.add_argument('--stress_client_poll_interval_secs',
default=_DEFAULT_STRESS_CLIENT_POLL_INTERVAL_SECS,
type=int,
help='How frequently should the stress client wrapper script'
' running inside GKE should monitor health of the actual '
' stress client process and upload the metrics to BigQuery')
argp.add_argument('--stress_client_metrics_collection_interval_secs',
default=_DEFAULT_METRICS_COLLECTION_INTERVAL_SECS,
type=int,
help='How frequently should metrics be collected in-memory on'
' the stress clients (running inside GKE containers). Note '
'that this is NOT the same as the upload-to-BigQuery '
'frequency. The metrics upload frequency is controlled by the'
' --stress_client_poll_interval_secs flag')
argp.add_argument('--stress_client_num_channels_per_server',
default=_DEFAULT_NUM_CHANNELS_PER_SERVER,
type=int,
help='The number of channels created to each server from a '
'stress client')
argp.add_argument('--stress_client_num_stubs_per_channel',
default=_DEFAULT_NUM_STUBS_PER_CHANNEL,
type=int,
help='The number of stubs created per channel. This number '
'indicates the max number of RPCs that can be made in '
'parallel on each channel at any given time')
argp.add_argument('--stress_client_test_cases',
default=_DEFAULT_TEST_CASES_STR,
help='List of test cases (with weights) to be executed by the'
' stress test client. The list is in the following format:\n'
' <testcase_1:w_1,<test_case2:w_2>..<testcase_n:w_n>\n'
' (Note: The weights do not have to add up to 100)')
if __name__ == '__main__':
image_name = 'grpc_stress_test'
gcp_project_id = 'sree-gce'
tag_name = 'gcr.io/%s/%s' % (gcp_project_id, image_name)
num_client_instances = 3
poll_interval_secs = 10
test_duration_secs = 150
run_test(True, gcp_project_id, image_name, tag_name, num_client_instances,
poll_interval_secs, test_duration_secs)
args = argp.parse_args()
test_settings = TestSettings(
args.build_docker_image, args.test_poll_interval_secs,
args.test_duration_secs, args.kubernetes_proxy_port)
gke_settings = GkeSettings(args.project_id, args.docker_image_name)
stress_server_settings = StressServerSettings(_SERVER_POD_NAME,
args.stress_server_port)
stress_client_settings = StressClientSettings(
args.num_clients, _CLIENT_POD_NAME_PREFIX, _SERVER_POD_NAME,
args.stress_server_port, args.stress_client_metrics_port,
args.stress_client_metrics_collection_interval_secs,
args.stress_client_poll_interval_secs,
args.stress_client_num_channels_per_server,
args.stress_client_num_stubs_per_channel, args.stress_client_test_cases)
run_test_main(test_settings, gke_settings, stress_server_settings,
stress_client_settings)

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