from behave import given
from behave import when
from behave import then
+from copy import deepcopy
from requests import RequestException
from retry import retry
import json
from nfvbench.summarizer import Formatter
from nfvbench.traffic_gen.traffic_utils import parse_rate_str
+from behave_tests.features.steps.testapi import TestapiClient, nfvbench_input_to_str
+
+
STATUS_ERROR = "ERROR"
STATUS_OK = "OK"
context.logger.info(f"add_percentage_rate: {percentage_rate} => rate={rate}")
+@given('packet rate equal to {percentage} of max throughput of last characterization')
+def add_packet_rate(context, percentage: str):
+ """Update nfvbench run config with packet rate based on reference value.
+
+ For the already configured frame size and flow count, retrieve the max
+ throughput obtained during the latest successful characterization run. Then
+ retain `percentage` of this value for the packet rate and update `context`.
+
+ Args:
+ context: The context data of the current scenario run. It includes the
+ testapi endpoints to retrieve the reference values.
+
+ percentage: String representation of the percentage of the reference max
+ throughput. Example: "70%"
+
+ Updates context:
+ context.percentage_rate: percentage of reference max throughput
+ using a string representation. Example: "70%"
+
+ context.json['rate']: packet rate in packets per second using a string
+ representation. Example: "2000pps"
+
+ Raises:
+ ValueError: invalid percentage string
+
+ AssertionError: cannot find reference throughput value
+
+ """
+ # Validate percentage
+ if not percentage.endswith('%'):
+ raise ValueError('Invalid percentage string: "{0}"'.format(percentage))
+ percentage_float = convert_percentage_str_to_float(percentage)
+
+ # Retrieve nfvbench results report from testapi for:
+ # - the latest throughput scenario inside a characterization feature that passed
+ # - the test duration, frame size and flow count given in context.json
+ # - (optionally) the user_label and flavor_type given in context.json
+ # - the 'ndr' rate
+ testapi_params = {"project_name": context.data['PROJECT_NAME'],
+ "case_name": "characterization"}
+ nfvbench_test_conditions = deepcopy(context.json)
+ nfvbench_test_conditions['rate'] = 'ndr'
+ testapi_client = TestapiClient(testapi_url=context.data['TEST_DB_URL'])
+ last_result = testapi_client.find_last_result(testapi_params,
+ scenario_tag="throughput",
+ nfvbench_test_input=nfvbench_test_conditions)
+ if last_result is None:
+ error_msg = "No characterization result found for scenario_tag=throughput"
+ error_msg += " and nfvbench test conditions "
+ error_msg += nfvbench_input_to_str(nfvbench_test_conditions)
+ context.logger.error(error_msg)
+ raise AssertionError(error_msg)
+
+ # From the results report, extract the max throughput in packets per second
+ total_tx_rate = extract_value(last_result["output"], "total_tx_rate")
+ context.logger.info("add_packet_rate: max throughput of last characterization (pps): "
+ f"{total_tx_rate:,}")
+
+ # Compute the desired packet rate
+ rate = round(total_tx_rate * percentage_float)
+ context.logger.info(f"add_packet_rate: percentage={percentage} rate(pps)={rate:,}")
+
+ # Build rate string using a representation understood by nfvbench
+ rate_str = str(rate) + "pps"
+
+ # Update context
+ context.percentage_rate = percentage
+ context.json['rate'] = rate_str
+
+
"""When steps."""
f"rate={context.json['rate']} repeat={repeat}")
if 'json' not in context.json:
+ # Build filename for nfvbench results in JSON format
context.json['json'] = '/var/lib/xtesting/results/' + context.CASE_NAME + \
- '/nfvbench-' + context.tag + '-fs_' + \
- context.json['frame_sizes'][0] + '-fc_' + \
- context.json['flow_count'] + '-rate_' + \
- context.json['rate'] + '.json'
+ '/nfvbench-' + context.tag + \
+ '-fs_' + context.json['frame_sizes'][0] + \
+ '-fc_' + context.json['flow_count']
+ if context.percentage_rate is not None:
+ # Add rate as a percentage, eg '-rate_70%'
+ context.json['json'] += '-rate_' + context.percentage_rate
+ else:
+ # Add rate in bits or packets per second, eg '-rate_15Gbps' or '-rate_10kpps'
+ context.json['json'] += '-rate_' + context.json['rate']
+ context.json['json'] += '.json'
+
json_base_name = context.json['json']
max_total_tx_rate = None
max_reference_value=Formatter.standard(reference_values[1])))
-def get_result_from_input_values(input, result):
- # Select required keys (other keys can be not set or unconsistent between scenarios)
- required_keys = ['duration_sec', 'frame_sizes', 'flow_count', 'rate']
- if 'user_label' in result:
- required_keys.append('user_label')
- if 'flavor_type' in result:
- required_keys.append('flavor_type')
- subset_input = dict((k, input[k]) for k in required_keys if k in input)
- subset_result = dict((k, result[k]) for k in required_keys if k in result)
- return subset_input == subset_result
-
-
def extract_value(obj, key):
"""Pull all values of specified key from nested JSON."""
arr = []
return results[0]
-def get_last_result(context, reference=None, page=None):
+def get_last_result(context, reference: bool = False):
+ """Look for a previous result in TestAPI database.
+
+ Search TestAPI results from newest to oldest and return the first result
+ record matching the context constraints. Log an overview of the results
+ found (max rate pps, avg delay usec, test conditions, date of measurement).
+
+ The result record test case must match the current test case
+ ('characterization' or 'non-regression') unless `reference` is set to True.
+
+ The result record scenario tag must match the current scenario tag
+ ('throughput' or 'latency').
+
+ Args:
+ context: behave context including project name, test case name, traffic
+ configuration (frame size, flow count, test duration), type of the
+ compute node under test (via loop VM flavor_type) and platform (via
+ user_label).
+
+ reference: when True, look for results with the 'characterization' test
+ case name instead of the current test case name.
+
+ Returns:
+ a JSON dictionary with the results, ie a dict with the keys "input",
+ "output" and "synthesis" when the scenario tag is 'throughput' or
+ 'latency'
+ """
if reference:
case_name = 'characterization'
else:
case_name = context.CASE_NAME
- url = context.data['TEST_DB_URL'] + '?project={project_name}&case={case_name}'.format(
- project_name=context.data['PROJECT_NAME'], case_name=case_name)
- if context.data['INSTALLER_TYPE']:
- url += '&installer={installer_name}'.format(installer_name=context.data['INSTALLER_TYPE'])
- if context.data['NODE_NAME']:
- url += '&pod={pod_name}'.format(pod_name=context.data['NODE_NAME'])
- url += '&criteria=PASS'
- if page:
- url += '&page={page}'.format(page=page)
- last_results = requests.get(url)
- assert last_results.status_code == 200
- last_results = json.loads(last_results.text)
- for result in last_results["results"]:
- for tagged_result in result["details"]["results"][context.tag]:
- if get_result_from_input_values(tagged_result["input"], context.json):
- return tagged_result
- if last_results["pagination"]["current_page"] < last_results["pagination"]["total_pages"]:
- page = last_results["pagination"]["current_page"] + 1
- return get_last_result(context, page)
- return None
+ testapi_params = {"project_name": context.data['PROJECT_NAME'],
+ "case_name": case_name}
+ testapi_client = TestapiClient(testapi_url=context.data['TEST_DB_URL'])
+ last_result = testapi_client.find_last_result(testapi_params,
+ scenario_tag=context.tag,
+ nfvbench_test_input=context.json)
+ if last_result is None:
+ error_msg = "get_last_result: No result found in TestAPI database:"
+ error_msg += f" case_name={case_name} scenario_tag={context.tag} "
+ error_msg += nfvbench_input_to_str(context.json)
+ context.logger.error(error_msg)
+ raise AssertionError(error_msg)
+
+ # Log an overview of the last result (latency and max throughput)
+ measurement_date = last_result["output"]["result"]["date"]
+ total_tx_rate = extract_value(last_result["output"], "total_tx_rate")
+ avg_delay_usec = extract_value(extract_value(last_result["output"], "overall"),
+ "avg_delay_usec")
+ context.logger.info(f"get_last_result: case_name={case_name} scenario_tag={context.tag}"
+ f' measurement_date="{measurement_date}"'
+ f" total_tx_rate(pps)={total_tx_rate:,}"
+ f" avg_latency_usec={round(avg_delay_usec)}")
+
+ return last_result