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Microsoft Azure Monitor Opentelemetry Distro Client Library for Python

Project description

Azure Monitor Opentelemetry Distro client library for Python

The Azure Monitor Distro of Opentelemetry Python provides multiple installable components available for an Opentelemetry Azure Monitor monitoring solution. It allows you to instrument your Python applications to capture and report telemetry to Azure Monitor via the Azure monitor exporters.

This distro automatically installs the following libraries:

Officially supported instrumentations

OpenTelemetry instrumentations allow automatic collection of requests sent from underlying instrumented libraries. The following is a list of OpenTelemetry instrumentations that come bundled in with the Azure monitor distro. If you would like to add support for another OpenTelemetry instrumentation, please submit a feature request. In the meantime, you can use the OpenTelemetry instrumentation manually via it's own APIs (i.e. instrument()) in your code. See this for an example.

Instrumentation Supported library Supported versions
OpenTelemetry Django Instrumentation django link
OpenTelemetry FastApi Instrumentation fastapi link
OpenTelemetry Flask Instrumentation flask link
OpenTelemetry Psycopg2 Instrumentation psycopg2 link
OpenTelemetry Requests Instrumentation requests link
OpenTelemetry UrlLib Instrumentation urllib All
OpenTelemetry UrlLib3 Instrumentation urllib3 link

Azure Core Distributed Tracing

Using the Azure Core Tracing OpenTelemetry library, you can automatically capture the distributed tracing from Azure Core libraries. See the associated sample for more information. This feature is enabled automatically.

Key concepts

This package bundles a series of OpenTelemetry and Azure Monitor components to enable the collection and sending of telemetry to Azure Monitor. For MANUAL instrumentation, use the configure_azure_monitor function. AUTOMATIC instrumentation is not yet supported.

The Azure Monitor OpenTelemetry exporters are the main components in accomplishing this. You will be able to use the exporters and their APIs directly through this package. Please go the exporter documentation to understand how OpenTelemetry and Azure Monitor components work in enabling telemetry collection and exporting.

Currently, all instrumentations available in OpenTelemetry are in a beta state, meaning they are not stable and may have breaking changes in the future. Efforts are being made in pushing these to a more stable state.

Getting started

Prerequisites

To use this package, you must have:

Install the package

Install the Azure Monitor Opentelemetry Distro with pip:

pip install azure-monitor-opentelemetry

Usage

You can use configure_azure_monitor to set up instrumentation for your app to Azure Monitor. configure_azure_monitor supports the following optional arguments:

Parameter Description Environment Variable
connection_string The connection string for your Application Insights resource. The connection string will be automatically populated from the APPLICATIONINSIGHTS_CONNECTION_STRING environment variable if not explicitly passed in. APPLICATIONINSIGHTS_CONNECTION_STRING

You can configure further with OpenTelemetry environment variables such as:

Environment Variable Description
OTEL_SERVICE_NAME, OTEL_RESOURCE_ATTRIBUTES Specifies the OpenTelemetry resource associated with your application.
OTEL_LOGS_EXPORTER If set to None, disables collection and export of logging telemetry.
OTEL_METRICS_EXPORTER If set to None, disables collection and export of metric telemetry.
OTEL_TRACES_EXPORTER If set to None, disables collection and export of distributed tracing telemetry.
OTEL_BLRP_SCHEDULE_DELAY Specifies the logging export interval in milliseconds. Defaults to 5000.
OTEL_BSP_SCHEDULE_DELAY Specifies the distributed tracing export interval in milliseconds. Defaults to 5000.
OTEL_TRACES_SAMPLER_ARG Specifies the ratio of distributed tracing telemetry to be sampled. Accepted values are in the range [0,1]. Defaults to 1.0, meaning no telemetry is sampled out.
OTEL_PYTHON_DISABLED_INSTRUMENTATIONS Specifies which of the supported instrumentations to disable. Disabled instrumentations will not be instrumented as part of configure_azure_monitor. However, they can still be manually instrumented by users after the fact. Accepts a comma-separated list of lowercase entry point names for instrumentations. For example, set to "psycopg2,fastapi" to disable the Psycopg2 and FastAPI instrumentations. Defaults to an empty list, enabling all supported instrumentations.

Azure monitor OpenTelemetry Exporter configurations

You can pass Azure monitor OpenTelemetry exporter configuration parameters directly into configure_azure_monitor. See additional configuration related to exporting here.

...
configure_azure_monitor(
   connection_string="<your-connection-string>",
   disable_offline_storage=True, 
)
...

Examples

Samples are available here to demonstrate how to utilize the above configuration options.

Troubleshooting

The exporter raises exceptions defined in Azure Core.

Next steps

Check out the documentation for more.

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. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Additional documentation

Project details


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