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Release for v0.7.7 (#853)
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8 changes: 8 additions & 0 deletions CHANGELOG.md
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## Unreleased

## 0.7.7
Released 2020-02-03
- Update `azure` module
([#837](https://github.com/census-instrumentation/opencensus-python/pull/837),
[#845](https://github.com/census-instrumentation/opencensus-python/pull/845),
[#848](https://github.com/census-instrumentation/opencensus-python/pull/848),
[#851](https://github.com/census-instrumentation/opencensus-python/pull/851))

## 0.7.6
Released 2019-11-26

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10 changes: 10 additions & 0 deletions contrib/opencensus-ext-azure/CHANGELOG.md
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## Unreleased

## 1.0.2
Released 2020-02-03

- Add local storage and retry logic for Azure Metrics Exporter
([#845](https://github.com/census-instrumentation/opencensus-python/pull/845))
- Add Fixed-rate sampling logic for Azure Log Exporter
([#848](https://github.com/census-instrumentation/opencensus-python/pull/848))
- Implement TelemetryProcessors for Azure exporters
([#851](https://github.com/census-instrumentation/opencensus-python/pull/851))

## 1.0.1
Released 2019-11-26

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151 changes: 143 additions & 8 deletions contrib/opencensus-ext-azure/README.rst
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Expand Up @@ -37,6 +37,8 @@ This example shows how to send a warning level log to Azure Monitor.
logger.addHandler(AzureLogHandler(connection_string='InstrumentationKey=<your-instrumentation_key-here>'))
logger.warning('Hello, World!')
Correlation
###########

You can enrich the logs with trace IDs and span IDs by using the `logging integration <../opencensus-ext-logging>`_.

Expand Down Expand Up @@ -73,9 +75,12 @@ You can enrich the logs with trace IDs and span IDs by using the `logging integr
logger.warning('In the span')
logger.warning('After the span')
You can also add custom properties to your log messages in the form of key-values.
Custom Properties
#################

WARNING: For this feature to work, you need to pass a dictionary as the argument. If you pass arguments of any other type, the logger will ignore them. The solution is to convert these arguments into a dictionary.
You can also add custom properties to your log messages in the *extra* keyword argument using the custom_dimensions field.

WARNING: For this feature to work, you need to pass a dictionary to the custom_dimensions field. If you pass arguments of any other type, the logger will ignore them.

.. code:: python
Expand All @@ -85,7 +90,37 @@ WARNING: For this feature to work, you need to pass a dictionary as the argument
logger = logging.getLogger(__name__)
logger.addHandler(AzureLogHandler(connection_string='InstrumentationKey=<your-instrumentation_key-here>'))
logger.warning('action', {'key-1': 'value-1', 'key-2': 'value2'})
properties = {'custom_dimensions': {'key_1': 'value_1', 'key_2': 'value_2'}}
logger.warning('action', extra=properties)
Modifying Logs
##############

* You can pass a callback function to the exporter to process telemetry before it is exported.
* Your callback function can return `False` if you do not want this envelope exported.
* Your callback function must accept an [envelope](https://github.com/census-instrumentation/opencensus-python/blob/master/contrib/opencensus-ext-azure/opencensus/ext/azure/common/protocol.py#L86) data type as its parameter.
* You can see the schema for Azure Monitor data types in the envelopes [here](https://github.com/census-instrumentation/opencensus-python/blob/master/contrib/opencensus-ext-azure/opencensus/ext/azure/common/protocol.py).
* The `AzureLogHandler` handles `ExceptionData` and `MessageData` data types.

.. code:: python
import logging
from opencensus.ext.azure.log_exporter import AzureLogHandler
logger = logging.getLogger(__name__)
# Callback function to append '_hello' to each log message telemetry
def callback_function(envelope):
envelope.data.baseData.message += '_hello'
return True
handler = AzureLogHandler(connection_string='InstrumentationKey=<your-instrumentation_key-here>')
handler.add_telemetry_processor(callback_function)
logger.addHandler(handler)
logger.warning('Hello, World!')
Metrics
~~~~~~~
Expand Down Expand Up @@ -143,6 +178,9 @@ The **Azure Monitor Metrics Exporter** allows you to export metrics to `Azure Mo
if __name__ == "__main__":
main()
Standard Metrics
################

The exporter also includes a set of standard metrics that are exported to Azure Monitor by default.

.. code:: python
Expand Down Expand Up @@ -177,6 +215,67 @@ Below is a list of standard metrics that are currently available:
- Process CPU Usage (percentage)
- Process Private Bytes (bytes)

Modifying Metrics
#################

* You can pass a callback function to the exporter to process telemetry before it is exported.
* Your callback function can return `False` if you do not want this envelope exported.
* Your callback function must accept an [envelope](https://github.com/census-instrumentation/opencensus-python/blob/master/contrib/opencensus-ext-azure/opencensus/ext/azure/common/protocol.py#L86) data type as its parameter.
* You can see the schema for Azure Monitor data types in the envelopes [here](https://github.com/census-instrumentation/opencensus-python/blob/master/contrib/opencensus-ext-azure/opencensus/ext/azure/common/protocol.py).
* The `MetricsExporter` handles `MetricData` data types.

.. code:: python
import time
from opencensus.ext.azure import metrics_exporter
from opencensus.stats import aggregation as aggregation_module
from opencensus.stats import measure as measure_module
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
stats = stats_module.stats
view_manager = stats.view_manager
stats_recorder = stats.stats_recorder
CARROTS_MEASURE = measure_module.MeasureInt("carrots",
"number of carrots",
"carrots")
CARROTS_VIEW = view_module.View("carrots_view",
"number of carrots",
[],
CARROTS_MEASURE,
aggregation_module.CountAggregation())
# Callback function to only export the metric if value is greater than 0
def callback_function(envelope):
return envelope.data.baseData.metrics[0].value > 0
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-instrumentation-key-here>')
exporter.add_telemetry_processor(callback_function)
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")
if __name__ == "__main__":
main()
Trace
~~~~~

Expand All @@ -195,16 +294,21 @@ This example shows how to send a span "hello" to Azure Monitor.
from opencensus.trace.tracer import Tracer
tracer = Tracer(
exporter=AzureExporter(connection_string='InstrumentationKey=<your-instrumentation-key-here>'),
exporter=AzureExporter(
connection_string='InstrumentationKey=<your-instrumentation-key-here>'
),
sampler=ProbabilitySampler(1.0)
)
with tracer.span(name='hello'):
print('Hello, World!')
OpenCensus also supports several [integrations](https://github.com/census-instrumentation/opencensus-python#integration) which allows OpenCensus to integrate with third party libraries.
Integrations
############

OpenCensus also supports several `integrations <https://github.com/census-instrumentation/opencensus-python#integration>`_ which allows OpenCensus to integrate with third party libraries.

This example shows how to integrate with the [requests](https://2.python-requests.org/en/master/) library.
This example shows how to integrate with the `requests <https://2.python-requests.org/en/master/>`_ library.

* Create an Azure Monitor resource and get the instrumentation key, more information can be found `here <https://docs.microsoft.com/azure/azure-monitor/app/create-new-resource>`_.
* Install the `requests integration package <../opencensus-ext-requests>`_ using ``pip install opencensus-ext-requests``.
Expand All @@ -223,14 +327,45 @@ This example shows how to integrate with the [requests](https://2.python-request
config_integration.trace_integrations(['requests'])
tracer = Tracer(
exporter=AzureExporter(
# TODO: replace this with your own instrumentation key.
instrumentation_key='00000000-0000-0000-0000-000000000000',
connection_string='InstrumentationKey=<your-instrumentation-key-here>',
),
sampler=ProbabilitySampler(1.0),
)
with tracer.span(name='parent'):
response = requests.get(url='https://www.wikipedia.org/wiki/Rabbit')
Modifying Traces
################

* You can pass a callback function to the exporter to process telemetry before it is exported.
* Your callback function can return `False` if you do not want this envelope exported.
* Your callback function must accept an [envelope](https://github.com/census-instrumentation/opencensus-python/blob/master/contrib/opencensus-ext-azure/opencensus/ext/azure/common/protocol.py#L86) data type as its parameter.
* You can see the schema for Azure Monitor data types in the envelopes [here](https://github.com/census-instrumentation/opencensus-python/blob/master/contrib/opencensus-ext-azure/opencensus/ext/azure/common/protocol.py).
* The `AzureExporter` handles `Data` data types.

.. code:: python
import requests
from opencensus.ext.azure.trace_exporter import AzureExporter
from opencensus.trace import config_integration
from opencensus.trace.samplers import ProbabilitySampler
from opencensus.trace.tracer import Tracer
config_integration.trace_integrations(['requests'])
# Callback function to add os_type: linux to span properties
def callback_function(envelope):
envelope.data.baseData.properties['os_type'] = 'linux'
return True
exporter = AzureExporter(
connection_string='InstrumentationKey=<your-instrumentation-key-here>'
)
exporter.add_telemetry_processor(callback_function)
tracer = Tracer(exporter=exporter, sampler=ProbabilitySampler(1.0))
with tracer.span(name='parent'):
response = requests.get(url='https://www.wikipedia.org/wiki/Rabbit')
References
----------
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12 changes: 11 additions & 1 deletion contrib/opencensus-ext-azure/examples/logs/properties.py
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Expand Up @@ -21,4 +21,14 @@
# and place it in the APPLICATIONINSIGHTS_CONNECTION_STRING
# environment variable.
logger.addHandler(AzureLogHandler())
logger.warning('action', {'key-1': 'value-1', 'key-2': 'value2'})

properties = {'custom_dimensions': {'key_1': 'value_1', 'key_2': 'value_2'}}

# Use properties in logging statements
logger.warning('action', extra=properties)

# Use properties in exception logs
try:
result = 1 / 0 # generate a ZeroDivisionError
except Exception:
logger.exception('Captured an exception.', extra=properties)
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Expand Up @@ -92,6 +92,7 @@ def __init__(self, *args, **kwargs):
export_interval=15.0,
grace_period=5.0,
instrumentation_key=None,
logging_sampling_rate=1.0,
max_batch_size=100,
minimum_retry_interval=60, # minimum retry interval in seconds
proxy=None,
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@@ -0,0 +1,63 @@
# Copyright 2019, OpenCensus Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import logging

logger = logging.getLogger(__name__)


class ProcessorMixin(object):
"""ProcessorMixin adds the ability to process telemetry processors
Telemetry processors are functions that are called before exporting of
telemetry to possibly modify the envelope contents.
"""

def add_telemetry_processor(self, processor):
"""Adds telemetry processor to the collection. Telemetry processors
will be called one by one before telemetry item is pushed for sending
and in the order they were added.
:param processor: The processor to add.
"""
self._telemetry_processors.append(processor)

def clear_telemetry_processors(self):
"""Removes all telemetry processors"""
self._telemetry_processors = []

def apply_telemetry_processors(self, envelopes):
"""Applies all telemetry processors in the order they were added.
This function will return the list of envelopes to be exported after
each processor has been run sequentially. Individual processors can
throw exceptions and fail, but the applying of all telemetry processors
will proceed (not fast fail). Processors also return True if envelope
should be included for exporting, False otherwise.
:param envelopes: The envelopes to apply each processor to.
"""
filtered_envelopes = []
for envelope in envelopes:
accepted = True
for processor in self._telemetry_processors:
try:
if processor(envelope) is False:
accepted = False
break
except Exception as ex:
logger.warning('Telemetry processor failed with: %s.', ex)
if accepted:
filtered_envelopes.append(envelope)
return filtered_envelopes
10 changes: 0 additions & 10 deletions contrib/opencensus-ext-azure/opencensus/ext/azure/common/utils.py
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Expand Up @@ -23,12 +23,6 @@
from opencensus.common.version import __version__ as opencensus_version
from opencensus.ext.azure.common.version import __version__ as ext_version

try:
from urllib.parse import urlparse
except ImportError:
from urlparse import urlparse


azure_monitor_context = {
'ai.cloud.role': os.path.basename(sys.argv[0]) or 'Python Application',
'ai.cloud.roleInstance': platform.node(),
Expand Down Expand Up @@ -64,10 +58,6 @@ def timestamp_to_iso_str(timestamp):
return to_iso_str(datetime.datetime.utcfromtimestamp(timestamp))


def url_to_dependency_name(url):
return urlparse(url).netloc


# Validate UUID format
# Specs taken from https://tools.ietf.org/html/rfc4122
uuid_regex_pattern = re.compile('^[0-9a-f]{8}-'
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Expand Up @@ -12,4 +12,4 @@
# See the License for the specific language governing permissions and
# limitations under the License.

__version__ = '1.0.1'
__version__ = '1.0.2'
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