def test_new_metrics_exporter(self, exporter_mock):
iKey = '12345678-1234-5678-abcd-12345678abcd'
exporter = metrics_exporter.new_metrics_exporter(
instrumentation_key=iKey)
self.assertEqual(exporter.options.instrumentation_key, iKey)
self.assertEqual(len(exporter_mock.call_args_list), 1)
self.assertEqual(len(exporter_mock.call_args[0][0]), 2)
producer_class = standard_metrics.AzureStandardMetricsProducer
self.assertFalse(isinstance(exporter_mock.call_args[0][0][0],
producer_class))
self.assertTrue(isinstance(exporter_mock.call_args[0][0][1],
producer_class))
def __init__(self, test_name, test_description=None):
# oc will automatically search for the ENV VAR 'APPLICATIONINSIGHTS_CONNECTION_STRING'
self.exporter = metrics_exporter.new_metrics_exporter()
self.stats = stats_module.stats
self.view_manager = self.stats.view_manager
self.stats_recorder = self.stats.stats_recorder
self.azure_logger = get_azure_logger(test_name)
self.name = test_name
self.desc = test_description
events_measure_name = "The number of events handled by " + self.name
events_measure_desc = "The number of events handled by " + self.desc if self.desc else None
memory_measure_name = "memory usage percentage for " + self.name
memory_measure_desc = "memory usage percentage for " + self.desc if self.desc else None
cpu_measure_name = "cpu usage percentage for " + self.name
cpu_measure_desc = "cpu usage percentage for " + self.desc if self.desc else None
error_measure_name = "error count for " + self.name
error_measure_desc = "The number of errors happened while running the test for " + self.desc if self.desc else None
self.events_measure = measure_module.MeasureInt(
events_measure_name, events_measure_desc, "events")
self.memory_measure = measure_module.MeasureFloat(
memory_measure_name, memory_measure_desc)
self.cpu_measure = measure_module.MeasureFloat(cpu_measure_name,
cpu_measure_desc)
self.error_measure = measure_module.MeasureInt(error_measure_name,
error_measure_desc)
self.events_measure_view = view_module.View(
events_measure_name, events_measure_desc, [], self.events_measure,
aggregation_module.SumAggregation())
self.memory_measure_view = view_module.View(
memory_measure_name, memory_measure_desc, [], self.memory_measure,
aggregation_module.LastValueAggregation())
self.cpu_measure_view = view_module.View(
cpu_measure_name, cpu_measure_desc, [], self.cpu_measure,
aggregation_module.LastValueAggregation())
self.error_measure_view = view_module.View(
error_measure_name, error_measure_desc, [], self.error_measure,
aggregation_module.CountAggregation())
self.view_manager.register_view(self.events_measure_view)
self.view_manager.register_view(self.memory_measure_view)
self.view_manager.register_view(self.cpu_measure_view)
self.view_manager.register_view(self.error_measure_view)
self.mmap = self.stats_recorder.new_measurement_map()
def test_new_metrics_exporter_no_standard_metrics(self, exporter_mock):
with mock.patch('opencensus.ext.azure.metrics_exporter'
'.heartbeat_metrics.enable_heartbeat_metrics') as hb:
hb.return_value = None
iKey = '12345678-1234-5678-abcd-12345678abcd'
exporter = metrics_exporter.new_metrics_exporter(
instrumentation_key=iKey, enable_standard_metrics=False)
self.assertEqual(exporter.options.instrumentation_key, iKey)
self.assertEqual(len(exporter_mock.call_args_list), 1)
self.assertEqual(len(exporter_mock.call_args[0][0]), 1)
producer_class = standard_metrics.AzureStandardMetricsProducer
self.assertFalse(
isinstance(exporter_mock.call_args[0][0][0], producer_class))
def main():
# Enable metrics
# Set the interval in seconds in which you want to send metrics
exporter = metrics_exporter.new_metrics_exporter(export_interval=2)
view_manager.register_exporter(exporter)
view_manager.register_view(CARROTS_VIEW)
mmap = stats_recorder.new_measurement_map()
tmap = tag_map_module.TagMap()
mmap.measure_int_put(CARROTS_MEASURE, 1000)
mmap.record(tmap)
time.sleep(10)
print("Done recording metrics")
def __init__(self, export_metrics=False):
self.nb_check_requests = measure_module.MeasureInt(
"nb_check_requests",
"number of dates check requests for all weeks", "nb")
self.nb_check_requests_view = view_module.View(
"nb_check_requests view",
"number of dates check requests for all weeks", [],
self.nb_check_requests, aggregation_module.CountAggregation())
view_manager.register_view(self.nb_check_requests_view)
self.mmap = stats_recorder.new_measurement_map()
self.tmap = tag_map_module.TagMap()
if export_metrics:
exporter = metrics_exporter.new_metrics_exporter(
connection_string=azure_insights.connection_string)
view_manager.register_exporter(exporter)
def main():
# TODO: you need to specify the instrumentation key in a connection string
# and place it in the APPLICATIONINSIGHTS_CONNECTION_STRING
# environment variable.
# All you need is the next line. You can disable standard metrics by
# passing in enable_standard_metrics=False into the constructor of
# new_metrics_exporter()
_exporter = metrics_exporter.new_metrics_exporter()
print(_exporter.max_batch_size)
for _ in range(100):
print(psutil.virtual_memory())
time.sleep(5)
print("Done recording metrics")
def __init__(self):
"""Initializes Condensed_Binocular using the Run object of azureml.core, and adding a
metric exporter for ApplicationInsights using the opencensus library.
"""
env = Env()
env.read_env()
self.run = Run.get_context(allow_offline=True)
self.run_id = self.get_run_id(self.run)
self.offline_run = self.run.id.startswith(constants.OFFLINE_RUN_PREFIX)
self.exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=False,
export_interval=0,
connection_string=env("APP_INSIGHTS_CONNECTION_KEY"))
self.exporter.add_telemetry_processor(self.callback_function)
stats_module.stats.view_manager.register_exporter(self.exporter)
def main():
# Enable metrics
# Set the interval in seconds in which you want to send metrics
# TODO: you need to specify the instrumentation key in a connection string
# and place it in the APPLICATIONINSIGHTS_CONNECTION_STRING
# environment variable.
exporter = metrics_exporter.new_metrics_exporter()
view_manager.register_exporter(exporter)
view_manager.register_view(CARROTS_VIEW)
mmap = stats_recorder.new_measurement_map()
tmap = tag_map_module.TagMap()
mmap.measure_int_put(CARROTS_MEASURE, 1000)
mmap.record(tmap)
print("Done recording metrics")
def main():
# Enable metrics
# Set the interval in seconds in which you want to send metrics
exporter = metrics_exporter.new_metrics_exporter()
view_manager.register_exporter(exporter)
view_manager.register_view(NUM_REQUESTS_VIEW)
mmap = stats_recorder.new_measurement_map()
tmap = tag_map_module.TagMap()
tmap.insert("url", "http://example.com")
for i in range(100):
print(i)
mmap.measure_int_put(REQUEST_MEASURE, i)
mmap.record(tmap)
time.sleep(1)
print("Done recording metrics")
def main(port):
tornado.options.parse_command_line()
loop = tornado.ioloop.IOLoop.current()
if os.environ.get("APPLICATIONINSIGHTS_CONNECTION_STRING"):
_exporter = metrics_exporter.new_metrics_exporter()
app_log.info("Metric exporter started.")
# initialize AD extension attributes
loop.run_sync(graph.ensure_custom_attrs_exist)
graph.keep_jwt_keys_updated()
handlers.start_app(
endpoints(),
port,
consecutive_failures=0,
consecutive_failure_limit=int(os.environ.get("CONSECUTIVE_FAILURE_LIMIT", "3")),
xheaders=True,
)
def __init__(self):
self.metrics = {}
self.logger = logging.getLogger(__name__)
self.appinsights_key = None
raw_key = getenv(APPINSIGHTS_INSTRUMENTATIONKEY, None)
if raw_key and len(raw_key.strip()) > 0:
self.appinsights_key = raw_key.strip()
if self.appinsights_key:
handler = AzureLogHandler(
connection_string="InstrumentationKey=" +
str(getenv("APPINSIGHTS_INSTRUMENTATIONKEY")))
self.logger.addHandler(handler)
exporter = metrics_exporter.new_metrics_exporter(
connection_string="InstrumentationKey=" +
str(getenv("APPINSIGHTS_INSTRUMENTATIONKEY")))
view_manager.register_exporter(exporter)
def main():
# Enable metrics
# Set the interval in seconds in which you want to send metrics
exporter = metrics_exporter.new_metrics_exporter(export_interval=5)
view_manager.register_exporter(exporter)
view_manager.register_view(latency_view)
mmap = stats_recorder.new_measurement_map()
tmap = tag_map_module.TagMap()
for i in range(100):
ms = random.random() * 5 * 1000
print("Latency {0}:{1}".format(i, ms))
mmap.measure_float_put(m_latency_ms, ms)
mmap.record(tmap)
time.sleep(1)
print("Done recording metrics")
def main():
# Enable metrics
# Set the interval in seconds in which you want to send metrics
exporter = metrics_exporter.new_metrics_exporter(
connection_string='InstrumentationKey=<Your Key>')
view_manager.register_exporter(exporter)
view_manager.register_view(CARROTS_VIEW)
mmap = stats_recorder.new_measurement_map()
tmap = tag_map_module.TagMap()
mmap.measure_int_put(CARROTS_MEASURE, 1000)
mmap.record(tmap)
# Default export interval is every 15.0s
# Your application should run for at least this amount
# of time so the exporter will meet this interval
# Sleep can fulfill this
time.sleep(60)
print("Done recording metrics")
def main():
# Enable metrics
# Set the interval in seconds in which you want to send metrics
# TODO: you need to specify the instrumentation key in a connection string
# and place it in the APPLICATIONINSIGHTS_CONNECTION_STRING
# environment variable.
exporter = metrics_exporter.new_metrics_exporter()
view_manager.register_exporter(exporter)
view_manager.register_view(NUM_REQUESTS_VIEW)
mmap = stats_recorder.new_measurement_map()
tmap = tag_map_module.TagMap()
tmap.insert("url", "http://example.com")
for i in range(100):
print(i)
mmap.measure_int_put(REQUEST_MEASURE, i)
mmap.record(tmap)
time.sleep(1)
print("Done recording metrics")
def setupOpenCensusAndPrometheusExporter():
# __name__ contains the full name of the current module
logger = logging.getLogger(__name__)
logger.addHandler(AzureLogHandler(
connection_string='InstrumentationKey=<Your Key>'
))
stats = stats_module.stats
view_manager = stats.view_manager
exporter = metrics_exporter.new_metrics_exporter(
connection_string='InstrumentationKey=<Your Key>')
view_manager.register_exporter(exporter)
registerAllViews(view_manager)
view_manager.register_view(latency_view)
time.sleep(5)
from opencensus.tags import tag_map as tag_map_module
stats = stats_module.stats
view_manager = stats.view_manager
stats_recorder = stats.stats_recorder
prompt_measure = measure_module.MeasureInt("prompts", "number of prompts",
"prompts")
prompt_view = view_module.View("prompt view", "number of prompts", [],
prompt_measure,
aggregation_module.CountAggregation())
view_manager.register_view(prompt_view)
mmap = stats_recorder.new_measurement_map()
tmap = tag_map_module.TagMap()
exporter = metrics_exporter.new_metrics_exporter(
connection_string=connection_string)
view_manager.register_exporter(exporter)
def prompt():
input("Press enter.")
mmap.measure_int_put(prompt_measure, 1)
mmap.record(tmap)
metrics = list(mmap.measure_to_view_map.get_metrics(datetime.utcnow()))
print(metrics[0].time_series[0].points[0])
def main():
while True:
prompt()
# Logging
logger = logging.getLogger(__name__)
logger.addHandler(AzureEventHandler(
connection_string='InstrumentationKey=ee6147a6-6162-463a-a119-bfeaff3147f6')
)
logger.addHandler(AzureLogHandler(
connection_string='InstrumentationKey=ee6147a6-6162-463a-a119-bfeaff3147f6')
)
logger.setLevel(logging.INFO)
# Metrics
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=True,
connection_string='InstrumentationKey=ee6147a6-6162-463a-a119-bfeaff3147f6')
# Tracing
tracer = Tracer(
exporter=AzureExporter(
connection_string='InstrumentationKey=ee6147a6-6162-463a-a119-bfeaff3147f6'),
sampler=ProbabilitySampler(1.0),
)
app = Flask(__name__)
# Requests
middleware = FlaskMiddleware(
app,
exporter=AzureExporter(connection_string="InstrumentationKey=ee6147a6-6162-463a-a119-bfeaff3147f6"),
# Logging
logger = logging.getLogger(__name__)
handler = AzureLogHandler(
connection_string='InstrumentationKey=3d3e7bec-d2e0-41b6-b690-7c9cb2020fc2'
)
logger.addHandler(handler)
logger.setLevel(logging.INFO)
logger.addHandler(
AzureEventHandler(
connection_string=
'InstrumentationKey=3d3e7bec-d2e0-41b6-b690-7c9cb2020fc2'))
# Metrics
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=True,
connection_string='InstrumentationKey=3d3e7bec-d2e0-41b6-b690-7c9cb2020fc2'
)
# Tracing
tracer = Tracer(
exporter=AzureExporter(
connection_string=
'InstrumentationKey=3d3e7bec-d2e0-41b6-b690-7c9cb2020fc2'),
sampler=ProbabilitySampler(1.0),
)
app = Flask(__name__)
# Requests
middleware = FlaskMiddleware(
app,
from opencensus.stats import stats as stats_module
from opencensus.stats import view as view_module
from opencensus.tags import tag_map as tag_map_module
from opencensus.ext.azure.trace_exporter import AzureExporter
from opencensus.trace.samplers import ProbabilitySampler
from opencensus.trace.tracer import Tracer
from opencensus.ext.flask.flask_middleware import FlaskMiddleware
# Logging
#logger = # TODO: Setup logger
logger = logging.getLogger(__name__)
logger.addHandler(AzureLogHandler(connection_string='InstrumentationKey=d2989c85-e9da-4470-97b3-2c4186d9785f'))
# Metrics
#exporter = # TODO: Setup exporter
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=True,
connection_string='InstrumentationKey=d2989c85-e9da-4470-97b3-2c4186d9785f')
# Tracing
#tracer = # TODO: Setup tracer
tracer = Tracer(
exporter=AzureExporter(
connection_string='InstrumentationKey=d2989c85-e9da-4470-97b3-2c4186d9785f'),
sampler=ProbabilitySampler(1.0),
)
app = Flask(__name__)
# Requests
#middleware = # TODO: Setup flask middleware
middleware = FlaskMiddleware(
# Trace integrations for requests library
config_integration.trace_integrations(['requests'])
# FlaskMiddleware will track requests for the Flask application and send
# request/dependency telemetry to Azure Monitor
middleware = FlaskMiddleware(app)
# Processor function for changing the role name of the app
def callback_function(envelope):
envelope.tags['ai.cloud.role'] = "To-Do App"
return True
# Adds the telemetry processor to the trace exporter
middleware.exporter.add_telemetry_processor(callback_function)
# Exporter for metrics, will send metrics data
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=False,
connection_string='InstrumentationKey=' + Config.INSTRUMENTATION_KEY)
# Exporter for logs, will send logging data
logger.addHandler(
AzureLogHandler(
connection_string='InstrumentationKey=' + Config.INSTRUMENTATION_KEY
)
)
if __name__ == '__main__':
app.run(host='localhost', port=5000, threaded=True, debug=True)
from opencensus.tags import tag_map as tag_map_module
from opencensus.ext.azure.trace_exporter import AzureExporter
from opencensus.trace.samplers import ProbabilitySampler
from opencensus.trace.tracer import Tracer
from opencensus.ext.flask.flask_middleware import FlaskMiddleware
from opencensus.ext.azure.log_exporter import AzureEventHandler
app_insught_intrumentation_key = '841b1abd-f5e6-499e-a744-d59a6ca8762a'
# Logging
logger = logging.getLogger(__name__)
logger.addHandler(AzureEventHandler(connection_string='InstrumentationKey='+app_insught_intrumentation_key))
logger.setLevel(logging.INFO)
# Metrics
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=True,
connection_string='InstrumentationKey='+app_insught_intrumentation_key)
# Tracing
tracer = Tracer(
exporter=AzureExporter(
connection_string='InstrumentationKey='+app_insught_intrumentation_key),
sampler=ProbabilitySampler(1.0),
)
app = Flask(__name__)
# Requests
middleware = FlaskMiddleware(
app,
exporter=AzureExporter(connection_string="InstrumentationKey="+app_insught_intrumentation_key),
from opencensus.tags import tag_map as tag_map_module
from opencensus.ext.azure.trace_exporter import AzureExporter
from opencensus.trace.samplers import ProbabilitySampler
from opencensus.trace.tracer import Tracer
from opencensus.ext.flask.flask_middleware import FlaskMiddleware
#logger = # TODO: Setup logger
logger = logging.getLogger(__name__)
logger.addHandler(
AzureLogHandler(connection_string=
'InstrumentationKey=d1c291be-3bd7-4d5c-9eaa-618310979e86'))
# Metrics
#exporter = # TODO: Setup exporter
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=True,
connection_string='InstrumentationKey=d1c291be-3bd7-4d5c-9eaa-618310979e86'
)
# Tracing
#tracer = # TODO: Setup tracer
tracer = Tracer(
exporter=AzureExporter(
connection_string=
'InstrumentationKey=d1c291be-3bd7-4d5c-9eaa-618310979e86'),
sampler=ProbabilitySampler(1.0),
)
app = Flask(__name__)
# Requests
#middleware = # TODO: Setup flask middleware
from opencensus.tags import tag_map as tag_map_module
from opencensus.ext.azure.trace_exporter import AzureExporter
from opencensus.trace.samplers import ProbabilitySampler
from opencensus.trace.tracer import Tracer
from opencensus.ext.flask.flask_middleware import FlaskMiddleware
from applicationinsights import TelemetryClient
# Logging
logger = logging.getLogger(__name__)
handler = AzureLogHandler(connection_string='InstrumentationKey=5e2837e6-5c38-4d77-9719-64e7f2d519a4')
logger.addHandler(handler)
logger.setLevel(logging.INFO)
# Metrics
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=True,
connection_string='InstrumentationKey=5e2837e6-5c38-4d77-9719-64e7f2d519a4')
# Tracing
tracer = Tracer(
exporter=AzureExporter(
connection_string='InstrumentationKey=5e2837e6-5c38-4d77-9719-64e7f2d519a4'),
sampler=ProbabilitySampler(1.0),
)
#
telemetry_client = TelemetryClient('5e2837e6-5c38-4d77-9719-64e7f2d519a4')
app = Flask(__name__)
# Requests
'InstrumentationKey=75bbbb31-b712-4e5d-abc7-8eb89689ce08;IngestionEndpoint=https://westus2-1.in.applicationinsights.azure.com/'
))
#Events
eventlogger = logging.getLogger('eventlogger')
eventlogger.addHandler(
AzureEventHandler(
connection_string=
'InstrumentationKey=75bbbb31-b712-4e5d-abc7-8eb89689ce08;IngestionEndpoint=https://westus2-1.in.applicationinsights.azure.com/'
))
eventlogger.setLevel(logging.INFO)
# Metrics
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=True,
connection_string=
'InstrumentationKey=75bbbb31-b712-4e5d-abc7-8eb89689ce08;IngestionEndpoint=https://westus2-1.in.applicationinsights.azure.com/'
)
# Tracing
tracer = Tracer(
exporter=AzureExporter(
connection_string=
'InstrumentationKey=75bbbb31-b712-4e5d-abc7-8eb89689ce08;IngestionEndpoint=https://westus2-1.in.applicationinsights.azure.com/'
),
sampler=ProbabilitySampler(1.0),
)
app = Flask(__name__)
# Requests
# middleware = # TODO: Setup flask middleware
exporter=AzureExporter(
connection_string=
'InstrumentationKey=a830027f-3b39-4371-8877-8ee0c3050e58'),
sampler=ProbabilitySampler(rate=1.0),
)
# TODO: Setup flask middleware
# Logging
logger = logging.getLogger(__name__)
logger.addHandler(
AzureLogHandler(connection_string=
'InstrumentationKey=a830027f-3b39-4371-8877-8ee0c3050e58'))
# Metrics TODO: Setup exporter
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=True,
connection_string='InstrumentationKey=a830027f-3b39-4371-8877-8ee0c3050e58'
)
# Tracing
tracer = Tracer(
exporter=AzureExporter(
connection_string=
'InstrumentationKey=a830027f-3b39-4371-8877-8ee0c3050e58'),
sampler=ProbabilitySampler(1.0),
)
# Load configurations from environment or config file
app.config.from_pyfile('config_file.cfg')
if ("VOTE1VALUE" in os.environ and os.environ['VOTE1VALUE']):
button1 = os.environ['VOTE1VALUE']
else:
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
# load configuration to get around hard coded tokens
config = configparser.ConfigParser()
with open('config.ini') as config_file:
config.read_file(config_file)
if config.has_option('Configuration', 'azure_log'):
logger.addHandler(
AzureLogHandler(
connection_string=config["Configuration"]["azure_log"]))
# the default metrics exporter will include
# stats like memory, CPU, etc
exporter = metrics_exporter.new_metrics_exporter(
connection_string=config["Configuration"]["azure_log"])
# startup stuff
print('discordpy')
print(discord.__version__)
client = commands.Bot(
command_prefix='>>',
description='https://github.com/Chris-Johnston/CssBot-Py',
case_insensitive=True)
# this is where extensions are added by default
default_extensions = [
'cogs.basic', 'cogs.courseInfo', 'cogs.number_utils',
'cogs.hardware_utils', 'cogs.analytics', 'cogs.gpa', 'cogs.manpage',
'cogs.markov', 'cogs.hyphen', 'cogs.crob', 'cogs.starboard', 'cogs.advent',
from opencensus.trace.tracer import Tracer
from opencensus.ext.flask.flask_middleware import FlaskMiddleware
from opencensus.ext.azure.log_exporter import AzureEventHandler
# Logging
logger = logging.getLogger(__name__)
logger.addHandler(
AzureEventHandler(
connection_string=
'InstrumentationKey=15d02af3-bb8b-48ab-937e-7f84588dfce0;IngestionEndpoint=https://westus-0.in.applicationinsights.azure.com/'
))
# Metrics
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=True,
connection_string=
'InstrumentationKey=15d02af3-bb8b-48ab-937e-7f84588dfce0;IngestionEndpoint=https://westus-0.in.applicationinsights.azure.com/'
)
# Tracing
tracer = Tracer(
exporter=AzureExporter(
connection_string=
'InstrumentationKey=15d02af3-bb8b-48ab-937e-7f84588dfce0;IngestionEndpoint=https://westus-0.in.applicationinsights.azure.com/'
),
sampler=ProbabilitySampler(1.0),
)
app = Flask(__name__)
# Requests
prompt_measure = measure_module.MeasureInt("rcs_log_num", "number of rcs_logs",
"logs")
prompt_view = view_module.View("rcs_log_view_3", "number of logs", [],
prompt_measure,
aggregation_module.SumAggregation())
view_manager.register_view(prompt_view)
mmap = stats_recorder.new_measurement_map()
tmap = tag_map_module.TagMap()
# Register the metrics exporter
##customMetrics
## | where name =='prompt view'
from opencensus.ext.azure import metrics_exporter
exporter = metrics_exporter.new_metrics_exporter(
connection_string='InstrumentationKey=<Your Key>')
view_manager.register_exporter(exporter)
# metrics usage example
def test_metrics():
for _ in range(100):
value = random.randint(1, 10)
mmap.measure_int_put(prompt_measure, value)
mmap.record(tmap)
metrics = list(mmap.measure_to_view_map.get_metrics(datetime.utcnow()))
print(value, ' : ', metrics[0].time_series[0].points[0])
time.sleep(1)
time.sleep(100)
from opencensus.ext.flask.flask_middleware import FlaskMiddleware
from opencensus.trace.samplers import ProbabilitySampler
# Logging
logger = logging.getLogger(__name__)
logger.addHandler(
AzureLogHandler(
connection_string=
'InstrumentationKey=bdba70b7-8e6e-4adb-adb5-8fd02df32aea;IngestionEndpoint=https://westus2-1.in.applicationinsights.azure.com/'
))
logger.setLevel(logging.INFO)
# Metrics
exporter = metrics_exporter.new_metrics_exporter(
enable_standard_metrics=True,
connection_string=
'InstrumentationKey=bdba70b7-8e6e-4adb-adb5-8fd02df32aea;IngestionEndpoint=https://westus2-1.in.applicationinsights.azure.com/'
)
# Tracing
tracer = Tracer(
exporter=AzureExporter(
connection_string=
'InstrumentationKey=bdba70b7-8e6e-4adb-adb5-8fd02df32aea;IngestionEndpoint=https://westus2-1.in.applicationinsights.azure.com/'
),
sampler=ProbabilitySampler(1.0),
)
app = Flask(__name__)
# Requests
from opencensus.stats import view as view_module
from opencensus.tags import tag_map as tag_map_module
from opencensus.ext.azure.trace_exporter import AzureExporter
from opencensus.trace.samplers import ProbabilitySampler
from opencensus.trace.tracer import Tracer
from opencensus.ext.flask.flask_middleware import FlaskMiddleware
CONN_STR = 'InstrumentationKey=84fadb80-b028-4f05-90f7-300fa367c8fd'
# Logging
logger = logging.getLogger(__name__)
logger.addHandler(AzureLogHandler(connection_string=CONN_STR))
logger.setLevel(logging.INFO)
# Metrics
exporter = metrics_exporter.new_metrics_exporter(enable_standard_metrics=True,
connection_string=CONN_STR)
# Tracing
tracer = Tracer(
exporter=AzureExporter(connection_string=CONN_STR),
sampler=ProbabilitySampler(1.0),
)
app = Flask(__name__)
# Requests
middleware = FlaskMiddleware(
app,
exporter=AzureExporter(connection_string=CONN_STR),
sampler=ProbabilitySampler(rate=1.0),
)
