Metadata-Version: 2.1
Name: azure-monitor-opentelemetry-exporter
Version: 1.0.0b9
Summary: Microsoft Azure Monitor Opentelemetry Exporter Client Library for Python
Home-page: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/monitor/azure-monitor-opentelemetry-exporter
Author: Microsoft Corporation
Author-email: ascl@microsoft.com
License: MIT License
Description: # Microsoft OpenTelemetry exporter for Azure Monitor
        
        The exporter for Azure Monitor allows you to export data utilizing the OpenTelemetry SDK and send telemetry data to Azure Monitor for applications written in Python.
        
        [Source code](https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/monitor/azure-monitor-opentelemetry-exporter) | [Package (PyPi)][pypi] | [API reference documentation][api_docs] | [Product documentation][product_docs] | [Samples](https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/monitor/azure-monitor-opentelemetry-exporter/samples) | [Changelog](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/monitor/azure-monitor-opentelemetry-exporter/CHANGELOG.md)
        
        ## Getting started
        
        ### Install the package
        
        Install the Microsoft OpenTelemetry exporter for Azure Monitor with [pip][pip]:
        
        ```Bash
        pip install azure-monitor-opentelemetry-exporter --pre
        ```
        
        ### Prerequisites
        
        To use this package, you must have:
        
        * Azure subscription - [Create a free account][azure_sub]
        * Azure Monitor - [How to use application insights][application_insights_namespace]
        * OpenTelemetry SDK - [OpenTelemetry SDK for Python][ot_sdk_python]
        * Python 3.7 or later - [Install Python][python]
        
        ### Instantiate the client
        
        Interaction with Azure monitor exporter starts with an instance of the `AzureMonitorTraceExporter` class for distributed tracing, `AzureMonitorLogExporter` for logging and `AzureMonitorMetricExporter` for metrics. You will need a **connection_string** to instantiate the object.
        Please find the samples linked below for demonstration as to how to construct the exporter using a connection string.
        
        #### Logging (experimental)
        
        NOTE: The logging signal for the `AzureMonitorLogExporter` is currently in an EXPERIMENTAL state. Possible breaking changes may ensue in the future.
        
        ```Python
        from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
        exporter = AzureMonitorLogExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        ```
        
        #### Metrics
        
        ```Python
        from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter
        exporter = AzureMonitorMetricExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        ```
        
        #### Tracing
        
        ```Python
        from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
        exporter = AzureMonitorTraceExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        ```
        
        You can also instantiate the exporter directly via the constructor. In this case, the connection string will be automatically populated from the `APPLICATIONINSIGHTS_CONNECTION_STRING` environment variable.
        
        ```python
        from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
        exporter = AzureMonitorLogExporter()
        ```
        
        ```python
        from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter
        exporter = AzureMonitorMetricExporter()
        ```
        
        ```python
        from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
        exporter = AzureMonitorTraceExporter()
        ```
        
        ## Key concepts
        
        Some of the key concepts for the Azure monitor exporter include:
        
        * [OpenTelemetry][opentelemetry_spec]: OpenTelemetry is a set of libraries used to collect and export telemetry data (metrics, logs, and traces) for analysis in order to understand your software's performance and behavior.
        
        * [Instrumentation][instrumentation_library]: The ability to call the OpenTelemetry API directly by any application is facilitated by instrumentation. A library that enables OpenTelemetry observability for another library is called an instrumentation Library.
        
        * [Log][log_concept]: Log refers to capturing of logging, exception and events.
        
        * [LogRecord][log_record]: Represents a log record emitted from a supported logging library.
        
        * [LogEmitter][log_emitter]: Converts a `LogRecord` into a readable `LogData`, and will be pushed through the SDK to be exported.
        
        * [LogEmitter Provider][log_emitter_provider]: Provides a `LogEmitter` for the given instrumentation library.
        
        * [LogProcessor][log_processor]: Interface to hook the log record emitting action.
        
        * [LoggingHandler][logging_handler]: A handler class which writes logging records in OpenTelemetry format from the standard Python `logging` library.
        
        * [AzureMonitorLogExporter][log_reference]: This is the class that is initialized to send logging related telemetry to Azure Monitor.
        
        * [Metric][metric_concept]: `Metric` refers to recording raw measurements with predefined aggregation and sets of attributes for a period in time.
        
        * [Measurement][measurement]: Represents a data point recorded at a point in time.
        
        * [Instrument][instrument]: Instruments are used to report `Measurement`s.
        
        * [Meter][meter]: The `Meter` is responsible for creating `Instruments`.
        
        * [Meter Provider][meter_provider]: Provides a `Meter` for the given instrumentation library.
        
        * [Metric Reader][metric_reader]: An SDK implementation object that provides the common configurable aspects of the OpenTelemetry Metrics SDK such as collection, flushing and shutdown.
        
        * [AzureMonitorMetricExporter][metric_reference]: This is the class that is initialized to send metric related telemetry to Azure Monitor.
        
        * [Trace][trace_concept]: Trace refers to distributed tracing. A distributed trace is a set of events, triggered as a result of a single logical operation, consolidated across various components of an application. In particular, a Trace can be thought of as a directed acyclic graph (DAG) of Spans, where the edges between Spans are defined as parent/child relationship.
        
        * [Span][span]: Represents a single operation within a `Trace`. Can be nested to form a trace tree. Each trace contains a root span, which typically describes the entire operation and, optionally, one ore more sub-spans for its sub-operations.
        
        * [Tracer][tracer]: Responsible for creating `Span`s.
        
        * [Tracer Provider][tracer_provider]: Provides a `Tracer` for use by the given instrumentation library.
        
        * [Span Processor][span_processor]: A span processor allows hooks for SDK's `Span` start and end method invocations. Follow the link for more information.
        
        * [AzureMonitorTraceExporter][trace_reference]: This is the class that is initialized to send tracing related telemetry to Azure Monitor.
        
        * [Sampling][sampler_ref]: Sampling is a mechanism to control the noise and overhead introduced by OpenTelemetry by reducing the number of samples of traces collected and sent to the backend.
        
        * ApplicationInsightsSampler: Application Insights specific sampler used for consistent sampling across Application Insights SDKs and OpenTelemetry-based SDKs sending data to Application Insights. This sampler MUST be used whenever `AzureMonitorTraceExporter` is used.
        
        For more information about these resources, see [What is Azure Monitor?][product_docs].
        
        ## Configuration
        
        All configuration options can be passed through the constructors of exporters through `kwargs`. Below is a list of configurable options.
        
        `connection_string`: The connection string used for your Application Insights resource.
        `disable_offline_storage`: Boolean value to determine whether to disable storing failed telemetry records for retry. Defaults to `False`.
        `storage_directory`: Storage directory in which to store retry files. Defaults to `<tempfile.gettempdir()>/Microsoft/AzureMonitor/opentelemetry-python-<your-instrumentation-key>`.
        
        ## Examples
        
        ### Logging (experimental)
        
        NOTE: The logging signal for the `AzureMonitorLogExporter` is currently in an EXPERIMENTAL state. Possible breaking changes may ensue in the future.
        
        The following sections provide several code snippets covering some of the most common tasks, including:
        
        * [Exporting a log record](#export-hello-world-log)
        * [Exporting correlated log record](#export-correlated-log)
        * [Exporting log record with custom properties](#export-custom-properties-log)
        * [Exporting an exceptions log record](#export-exceptions-log)
        
        Review the [OpenTelemetry Logging SDK][ot_logging_sdk] to learn how to use OpenTelemetry components to collect logs.
        
        #### Export Hello World Log
        
        ```Python
        """
        An example to show an application using Opentelemetry logging sdk. Logging calls to the standard Python
        logging library are tracked and telemetry is exported to application insights with the AzureMonitorLogExporter.
        """
        import os
        import logging
        
        from opentelemetry.sdk._logs import (
            LogEmitterProvider,
            LoggingHandler,
            set_log_emitter_provider,
        )
        from opentelemetry.sdk._logs.export import BatchLogProcessor
        
        from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
        
        log_emitter_provider = LogEmitterProvider()
        set_log_emitter_provider(log_emitter_provider)
        
        exporter = AzureMonitorLogExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        
        log_emitter_provider.add_log_processor(BatchLogProcessor(exporter))
        handler = LoggingHandler()
        
        # Attach LoggingHandler to root logger
        logging.getLogger().addHandler(handler)
        logging.getLogger().setLevel(logging.NOTSET)
        
        logger = logging.getLogger(__name__)
        
        logger.warning("Hello World!")
        ```
        
        #### Export Correlated Log
        
        ```Python
        """
        An example showing how to include context correlation information in logging telemetry.
        """
        import os
        import logging
        
        from opentelemetry import trace
        from opentelemetry.sdk._logs import (
            LogEmitterProvider,
            LoggingHandler,
            set_log_emitter_provider,
        )
        from opentelemetry.sdk._logs.export import BatchLogProcessor
        from opentelemetry.sdk.trace import TracerProvider
        
        from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
        
        trace.set_tracer_provider(TracerProvider())
        tracer = trace.get_tracer(__name__)
        log_emitter_provider = LogEmitterProvider()
        set_log_emitter_provider(log_emitter_provider)
        
        exporter = AzureMonitorLogExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        
        log_emitter_provider.add_log_processor(BatchLogProcessor(exporter))
        handler = LoggingHandler()
        
        # Attach LoggingHandler to root logger
        logging.getLogger().addHandler(handler)
        logging.getLogger().setLevel(logging.NOTSET)
        
        logger = logging.getLogger(__name__)
        
        logger.info("INFO: Outside of span")
        with tracer.start_as_current_span("foo"):
            logger.warning("WARNING: Inside of span")
        logger.error("ERROR: After span")
        ```
        
        #### Export Custom Properties Log
        
        ```Python
        """
        An example showing how to add custom properties to logging telemetry.
        """
        import os
        import logging
        
        from opentelemetry.sdk._logs import (
            LogEmitterProvider,
            LoggingHandler,
            set_log_emitter_provider,
        )
        from opentelemetry.sdk._logs.export import BatchLogProcessor
        
        from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
        
        log_emitter_provider = LogEmitterProvider()
        set_log_emitter_provider(log_emitter_provider)
        
        exporter = AzureMonitorLogExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        
        log_emitter_provider.add_log_processor(BatchLogProcessor(exporter))
        handler = LoggingHandler()
        
        # Attach LoggingHandler to root logger
        logging.getLogger().addHandler(handler)
        logging.getLogger().setLevel(logging.NOTSET)
        
        logger = logging.getLogger(__name__)
        
        # Custom properties
        logger.debug("DEBUG: Debug with properties", extra={"debug": "true"})
        ```
        
        #### Export Exceptions Log
        
        ```Python
        """
        An example showing how to export exception telemetry using the AzureMonitorLogExporter.
        """
        import os
        import logging
        
        from opentelemetry.sdk._logs import (
            LogEmitterProvider,
            LoggingHandler,
            get_log_emitter_provider,
            set_log_emitter_provider,
        )
        from opentelemetry.sdk._logs.export import BatchLogProcessor
        
        from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
        
        set_log_emitter_provider(LogEmitterProvider())
        exporter = AzureMonitorLogExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        get_log_emitter_provider().add_log_processor(BatchLogProcessor(exporter))
        
        # Attach LoggingHandler to namespaced logger
        handler = LoggingHandler()
        logger = logging.getLogger(__name__)
        logger.addHandler(handler)
        logger.setLevel(logging.NOTSET)
        
        # The following code will generate two pieces of exception telemetry
        # that are identical in nature
        try:
            val = 1 / 0
            print(val)
        except ZeroDivisionError:
            logger.exception("Error: Division by zero")
        
        try:
            val = 1 / 0
            print(val)
        except ZeroDivisionError:
            logger.error("Error: Division by zero", stack_info=True, exc_info=True)
        ```
        
        ### Metrics
        
        The following sections provide several code snippets covering some of the most common tasks, including:
        
        * [Using different metric instruments](#metric-instrument-usage)
        * [Customizing outputted metrics with views](#metric-custom-views)
        * [Recording instruments with attributes](#metric-record-attributes)
        
        Review the [OpenTelemetry Metrics SDK][ot_metrics_sdk] to learn how to use OpenTelemetry components to collect metrics.
        
        #### Metric instrument usage
        
        ```python
        """
        An example to show an application using all instruments in the OpenTelemetry SDK. Metrics created
        and recorded using the sdk are tracked and telemetry is exported to application insights with the
        AzureMonitorMetricsExporter.
        """
        import os
        from typing import Iterable
        
        from opentelemetry import metrics
        from opentelemetry.metrics import CallbackOptions, Observation
        from opentelemetry.sdk.metrics import MeterProvider
        from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
        
        from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter
        
        exporter = AzureMonitorMetricExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        reader = PeriodicExportingMetricReader(exporter, export_interval_millis=5000)
        metrics.set_meter_provider(MeterProvider(metric_readers=[reader]))
        
        # Create a namespaced meter
        meter = metrics.get_meter_provider().get_meter("sample")
        
        # Callback functions for observable instruments
        def observable_counter_func(options: CallbackOptions) -> Iterable[Observation]:
            yield Observation(1, {})
        
        
        def observable_up_down_counter_func(
            options: CallbackOptions,
        ) -> Iterable[Observation]:
            yield Observation(-10, {})
        
        
        def observable_gauge_func(options: CallbackOptions) -> Iterable[Observation]:
            yield Observation(9, {})
        
        # Counter
        counter = meter.create_counter("counter")
        counter.add(1)
        
        # Async Counter
        observable_counter = meter.create_observable_counter(
            "observable_counter", [observable_counter_func]
        )
        
        # UpDownCounter
        up_down_counter = meter.create_up_down_counter("up_down_counter")
        up_down_counter.add(1)
        up_down_counter.add(-5)
        
        # Async UpDownCounter
        observable_up_down_counter = meter.create_observable_up_down_counter(
            "observable_up_down_counter", [observable_up_down_counter_func]
        )
        
        # Histogram
        histogram = meter.create_histogram("histogram")
        histogram.record(99.9)
        
        # Async Gauge
        gauge = meter.create_observable_gauge("gauge", [observable_gauge_func])
        
        ```
        
        #### Metric custom views
        
        ```python
        """
        This example shows how to customize the metrics that are output by the SDK using Views. Metrics created
        and recorded using the sdk are tracked and telemetry is exported to application insights with the
        AzureMonitorMetricsExporter.
        """
        import os
        
        from opentelemetry import metrics
        from opentelemetry.sdk.metrics import Counter, MeterProvider
        from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
        from opentelemetry.sdk.metrics.view import View
        
        from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter
        
        exporter = AzureMonitorMetricExporter.from_connection_string(
            os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        # Create a view matching the counter instrument `my.counter`
        # and configure the new name `my.counter.total` for the result metrics stream
        change_metric_name_view = View(
            instrument_type=Counter,
            instrument_name="my.counter",
            name="my.counter.total",
        )
        
        reader = PeriodicExportingMetricReader(exporter, export_interval_millis=5000)
        provider = MeterProvider(
            metric_readers=[
                reader,
            ],
            views=[
                change_metric_name_view,
            ],
        )
        metrics.set_meter_provider(provider)
        
        meter = metrics.get_meter_provider().get_meter("view-name-change")
        my_counter = meter.create_counter("my.counter")
        my_counter.add(100)
        
        ```
        
        More examples with the metrics `Views` SDK can be found [here](https://github.com/open-telemetry/opentelemetry-python/tree/main/docs/examples/metrics/views).
        
        #### Metric record attributes
        
        ```python
        """
        An example to show an application using different attributes with instruments in the OpenTelemetry SDK.
        Metrics created and recorded using the sdk are tracked and telemetry is exported to application insights
        with the AzureMonitorMetricsExporter.
        """
        import os
        
        from opentelemetry import metrics
        from opentelemetry.sdk.metrics import MeterProvider
        from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
        
        from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter
        
        exporter = AzureMonitorMetricExporter.from_connection_string(
            os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        reader = PeriodicExportingMetricReader(exporter, export_interval_millis=5000)
        metrics.set_meter_provider(MeterProvider(metric_readers=[reader]))
        
        attribute_set1 = {
            "key1": "val1"
        }
        attribute_set2 = {
            "key2": "val2"
        }
        large_attribute_set = {}
        for i in range(20):
            key = "key{}".format(i)
            val = "val{}".format(i)
            large_attribute_set[key] = val
        
        meter = metrics.get_meter_provider().get_meter("sample")
        
        # Counter
        counter = meter.create_counter("attr1_counter")
        counter.add(1, attribute_set1)
        
        # Counter2
        counter2 = meter.create_counter("attr2_counter")
        counter2.add(10, attribute_set1)
        counter2.add(30, attribute_set2)
        
        # Counter3
        counter3 = meter.create_counter("large_attr_counter")
        counter3.add(100, attribute_set1)
        counter3.add(200, large_attribute_set)
        
        ```
        
        ### Tracing
        
        The following sections provide several code snippets covering some of the most common tasks, including:
        
        * [Exporting a custom span](#export-hello-world-trace)
        * [Using an instrumentation to track a library](#instrumentation-with-requests-library)
        * [Enabling sampling to limit the amount of telemetry sent](#enabling-sampling)
        
        Review the [OpenTelemetry Tracing SDK][ot_tracing_sdk] to learn how to use OpenTelemetry components to collect logs.
        
        #### Export Hello World Trace
        
        ```Python
        """
        An example to show an application using Opentelemetry tracing api and sdk. Custom dependencies are
        tracked via spans and telemetry is exported to application insights with the AzureMonitorTraceExporter.
        """
        import os
        from opentelemetry import trace
        from opentelemetry.sdk.trace import TracerProvider
        from opentelemetry.sdk.trace.export import BatchSpanProcessor
        from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
        
        trace.set_tracer_provider(TracerProvider())
        tracer = trace.get_tracer(__name__)
        # This is the exporter that sends data to Application Insights
        exporter = AzureMonitorTraceExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        span_processor = BatchSpanProcessor(exporter)
        trace.get_tracer_provider().add_span_processor(span_processor)
        
        with tracer.start_as_current_span("hello"):
            print("Hello, World!")
        ```
        
        #### Instrumentation with requests library
        
        OpenTelemetry also supports several instrumentations which allows to instrument with third party libraries.
        
        For a list of instrumentations available in OpenTelemetry, visit the contrib [documentation](https://opentelemetry-python-contrib.readthedocs.io/en/latest/).
        
        This example shows how to instrument with the [requests](https://pypi.org/project/requests/) library.
        
        * Install the requests instrumentation package using pip install opentelemetry-instrumentation-requests.
        
        ```Python
        """
        An example to show an application instrumented with the OpenTelemetry requests instrumentation.
        Calls made with the requests library will be automatically tracked and telemetry is exported to 
        application insights with the AzureMonitorTraceExporter.
        See more info on the requests instrumentation here:
        https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-requests
        """
        import os
        import requests
        from opentelemetry import trace
        from opentelemetry.instrumentation.requests import RequestsInstrumentor
        from opentelemetry.sdk.trace import TracerProvider
        from opentelemetry.sdk.trace.export import BatchSpanProcessor
        from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
        
        # This line causes your calls made with the requests library to be tracked.
        RequestsInstrumentor().instrument()
        
        trace.set_tracer_provider(TracerProvider())
        tracer = trace.get_tracer(__name__)
        exporter = AzureMonitorTraceExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        span_processor = BatchSpanProcessor(exporter)
        trace.get_tracer_provider().add_span_processor(span_processor)
        
        # This request will be traced
        response = requests.get(url="https://azure.microsoft.com/")
        ```
        
        #### Enabling sampling
        
        You can enable sampling to limit the amount of telemetry records you receive. In order to enable correct sampling in Application Insights, use the `ApplicationInsightsSampler` as shown below.
        
        ```Python
        """
        An example to show an application using the ApplicationInsightsSampler to enable sampling for your telemetry.
        Specify a sampling rate for the sampler to limit the amount of telemetry records you receive. Custom dependencies
         are tracked via spans and telemetry is exported to application insights with the AzureMonitorTraceExporter.
        """
        import os
        from opentelemetry import trace
        from opentelemetry.sdk.trace import TracerProvider
        from opentelemetry.sdk.trace.export import BatchSpanProcessor
        from azure.monitor.opentelemetry.exporter import (
            ApplicationInsightsSampler,
            AzureMonitorTraceExporter,
        )
        
        # Sampler expects a sample rate of between 0 and 1 inclusive
        # A rate of 0.75 means approximately 75% of your telemetry will be sent
        sampler = ApplicationInsightsSampler(0.75)
        trace.set_tracer_provider(TracerProvider(sampler=sampler))
        tracer = trace.get_tracer(__name__)
        exporter = AzureMonitorTraceExporter(
            connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"]
        )
        span_processor = BatchSpanProcessor(exporter)
        trace.get_tracer_provider().add_span_processor(span_processor)
        
        for i in range(100):
            # Approximately 25% of these spans should be sampled out
            with tracer.start_as_current_span("hello"):
                print("Hello, World!")
        ```
        
        ## Troubleshooting
        
        The exporter raises exceptions defined in [Azure Core](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/core/azure-core/README.md#azure-core-library-exceptions).
        
        ## Next steps
        
        ### More sample code
        
        Please find further examples in the [samples](https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/monitor/azure-monitor-opentelemetry-exporter/samples) directory demonstrating common scenarios.
        
        ### Additional documentation
        
        For more extensive documentation on the Azure Monitor service, see the [Azure Monitor documentation][product_docs] on docs.microsoft.com.
        
        For detailed overview of OpenTelemetry, visit their [overview](https://github.com/open-telemetry/opentelemetry-specification/blob/master/specification/overview.md) page.
        
        For the official OpenTelemetry Python documentation and how to enable other telemetry scenarios, visit the official OpenTelemetry [website](https://opentelemetry.io/docs/instrumentation/python/).
        
        For more information on the Azure Monitor OpenTelemetry Distro, which is a bundle of useful, pre-assembled components (one of them being this current package) that enable telemetry scenarios with Azure Monitor, visit the [README](https://github.com/microsoft/ApplicationInsights-Python/tree/main/azure-monitor-opentelemetry-distro).
        
        ## Contributing
        
        This project welcomes contributions and suggestions.  Most contributions require you to agree to a
        Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us
        the rights to use your contribution. For details, visit https://cla.microsoft.com.
        
        When you submit a pull request, a CLA-bot will automatically determine whether you need to provide
        a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions
        provided by the bot. You will only need to do this once across all repos using our CLA.
        
        This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
        For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or
        contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.
        
        <!-- LINKS -->
        [api_docs]: https://azuresdkdocs.blob.core.windows.net/$web/python/azure-opentelemetry-exporter-azuremonitor/1.0.0b2/index.html
        [product_docs]: https://docs.microsoft.com/azure/azure-monitor/overview
        [azure_sub]: https://azure.microsoft.com/free/
        [pip]: https://pypi.org/project/pip/
        [pypi]: https://pypi.org/project/azure-monitor-opentelemetry-exporter/
        [python]: https://www.python.org/downloads/
        [ot_sdk_python]: https://github.com/open-telemetry/opentelemetry-python
        [application_insights_namespace]: https://docs.microsoft.com/azure/azure-monitor/app/app-insights-overview#how-do-i-use-application-insights
        [opentelemetry_spec]: https://opentelemetry.io/
        [instrumentation_library]: https://github.com/open-telemetry/opentelemetry-specification/blob/master/specification/overview.md#instrumentation-libraries
        [log_concept]: https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/overview.md#log-signal
        [log_record]: https://opentelemetry-python.readthedocs.io/en/stable/sdk/logs.html#opentelemetry.sdk._logs.LogRecord
        [log_emitter]: https://opentelemetry-python.readthedocs.io/en/stable/sdk/logs.html#opentelemetry.sdk._logs.LogEmitter
        [log_emitter_provider]: https://opentelemetry-python.readthedocs.io/en/stable/sdk/logs.html#opentelemetry.sdk._logs.LogEmitterProvider
        [log_processor]: https://opentelemetry-python.readthedocs.io/en/stable/sdk/logs.html#opentelemetry.sdk._logs.LogProcessor
        [logging_handler]: https://opentelemetry-python.readthedocs.io/en/stable/sdk/logs.html#opentelemetry.sdk._logs.LoggingHandler
        [log_reference]: https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/monitor/azure-monitor-opentelemetry-exporter/azure/monitor/opentelemetry/exporter/export/logs/_exporter.py
        [ot_logging_sdk]: https://opentelemetry-python.readthedocs.io/en/stable/sdk/logs.html
        [metric_concept]: https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/overview.md#metric-signal
        [measurement]: https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/api.md#measurement
        [instrument]: https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/api.md#instrument
        [meter]: https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/api.md#meter
        [meter_provider]: https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/api.md#meterprovider
        [metric_reader]:https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/sdk.md#metricreader
        [metric_reference]: https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/monitor/azure-monitor-opentelemetry-exporter/azure/monitor/opentelemetry/exporter/export/metrics/_exporter.py
        [ot_metrics_sdk]: https://opentelemetry-python.readthedocs.io/en/stable/sdk/metrics.html
        [trace_concept]: https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/overview.md#tracing-signal
        [span]: https://opentelemetry-python.readthedocs.io/en/stable/api/trace.html?highlight=TracerProvider#opentelemetry.trace.Span
        [tracer]: https://opentelemetry-python.readthedocs.io/en/stable/api/trace.html?highlight=TracerProvider#opentelemetry.trace.Tracer
        [tracer_provider]: https://opentelemetry-python.readthedocs.io/en/stable/api/trace.html?highlight=TracerProvider#opentelemetry.trace.TracerProvider
        [span_processor]: https://opentelemetry-python.readthedocs.io/en/stable/_modules/opentelemetry/sdk/trace.html?highlight=SpanProcessor#
        [trace_reference]: https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/monitor/azure-monitor-opentelemetry-exporter/azure/monitor/opentelemetry/exporter/export/trace/_exporter.py
        [ot_tracing_sdk]: https://opentelemetry-python.readthedocs.io/en/stable/sdk/trace.html
        [sampler_ref]: https://github.com/open-telemetry/opentelemetry-specification/blob/master/specification/trace/sdk.md#sampling
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.7
Description-Content-Type: text/markdown
