def test_metrics_auth():
credential = _credential()
client = MetricsQueryClient(credential)
response = client.query(os.environ['METRICS_RESOURCE_URI'],
metric_names=["MatchedEventCount"],
timespan=timedelta(days=1),
aggregations=[MetricAggregationType.COUNT])
assert response
assert response.metrics
class MetricsPerfTest(PerfStressTest):
def __init__(self, arguments):
super().__init__(arguments)
# auth configuration
self.metrics_uri = self.get_from_env('METRICS_RESOURCE_URI')
self.names = ["MatchedEventCount"]
self.aggregations = [MetricAggregationType.COUNT]
# Create clients
self.metrics_client = SyncMetricsQueryClient(
credential=SyncDefaultAzureCredential())
self.async_metrics_client = AsyncMetricsQueryClient(
credential=AsyncDefaultAzureCredential())
async def close(self):
"""This is run after cleanup.
Use this to close any open handles or clients.
"""
await self.async_metrics_client.close()
await super().close()
def run_sync(self):
"""The synchronous perf test.
Try to keep this minimal and focused. Using only a single client API.
Avoid putting any ancilliary logic (e.g. generating UUIDs), and put this in the setup/init instead
so that we're only measuring the client API call.
"""
self.metrics_client.query(self.metrics_uri,
self.names,
aggregations=self.aggregations)
async def run_async(self):
"""The asynchronous perf test.
Try to keep this minimal and focused. Using only a single client API.
Avoid putting any ancilliary logic (e.g. generating UUIDs), and put this in the setup/init instead
so that we're only measuring the client API call.
"""
await self.async_metrics_client.query(self.metrics_uri,
self.names,
aggregations=self.aggregations)
def test_metrics_auth():
credential = _credential()
client = MetricsQueryClient(credential)
# returns LogsQueryResults
response = client.query(os.environ['METRICS_RESOURCE_URI'],
metric_names=["PublishSuccessCount"],
timespan='P2D')
assert response is not None
assert response.metrics is not None
import os
from datetime import datetime
import urllib3
from azure.monitor.query import MetricsQueryClient
from azure.identity import ClientSecretCredential
urllib3.disable_warnings()
# [START metrics_client_auth_with_token_cred]
credential = ClientSecretCredential(
client_id=os.environ['AZURE_CLIENT_ID'],
client_secret=os.environ['AZURE_CLIENT_SECRET'],
tenant_id=os.environ['AZURE_TENANT_ID'])
client = MetricsQueryClient(credential)
# [END metrics_client_auth_with_token_cred]
# [START send_metrics_query]
metrics_uri = os.environ['METRICS_RESOURCE_URI']
response = client.query(metrics_uri,
metric_names=["PublishSuccessCount"],
start_time=datetime(2021, 5, 25),
duration='P1D')
for metric in response.metrics:
print(metric.name)
for time_series_element in metric.timeseries:
for metric_value in time_series_element.data:
print(metric_value.time_stamp)
# [END send_metrics_query]
from azure.monitor.query import MetricsQueryClient, MetricAggregationType
from azure.identity import DefaultAzureCredential
# urllib3.disable_warnings()
# [START metrics_client_auth_with_token_cred]
credential = DefaultAzureCredential()
client = MetricsQueryClient(credential)
# [END metrics_client_auth_with_token_cred]
# [START send_metrics_query]
metrics_uri = os.environ['METRICS_RESOURCE_URI']
response = client.query(
metrics_uri,
metric_names=["Ingress"],
timespan=timedelta(hours=2),
granularity=timedelta(minutes=5),
aggregations=[MetricAggregationType.AVERAGE],
)
for metric in response.metrics:
print(metric.name + ' -- ' + metric.display_description)
for time_series_element in metric.timeseries:
for metric_value in time_series_element.data:
print('The ingress at {} is {}'.format(
metric_value.timestamp,
metric_value.average
))
# [END send_metrics_query]