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Python OpenTelemetry Instrumentation

This document contains instructions on how to set up OpenTelemetry instrumentation in your Python applications. OpenTelemetry, also known as OTel for short, is an open source observability framework that can help you generate and collect telemetry data - traces, metrics, and logs from your Python application.

Once the telemetry data is collected, you can configure an exporter to send the data to SigNoz.

There are three major steps to using OpenTelemetry:

  • Instrumenting your Python application with OpenTelemetry
  • Configuring exporter to send data to SigNoz
  • Validating that configuration to ensure that data is being sent as expected.
OpenTelemetry helps to generate and collect telemetry data from your application which is then sent to an observability backend like SigNoz
OpenTelemetry helps generate and collect telemetry data from Python applications which can then be sent to SigNoz for storage, visualization, and analysis.

Let’s understand how to download, install, and run OpenTelemetry in Python.

Requirements​

  • Python 3.6 or newer

Send Traces Directly to SigNoz​

You can use OpenTelemetry Python to send your traces directly to SigNoz. OpenTelemetry provides a handy distro in Python that can help you get started with automatic instrumentation. We recommend using it to get started quickly.

Steps to auto-instrument Python app for traces​

info

If you are on K8s, you should checkout opentelemetry operators which enable auto instrumenting Python applications very easily.

  1. Create a virtual environment

    python3 -m venv instrumentation_env
    source instrumentation_env/bin/activate

  2. Install the OpenTelemetry dependencies

    pip install opentelemetry-distro
    pip install opentelemetry-exporter-otlp

    The dependencies included are briefly explained below:

    opentelemetry-distro - The distro provides a mechanism to automatically configure some of the more common options for users. It helps to get started with OpenTelemetry auto-instrumentation quickly.

    opentelemetry-exporter-otlp - This library provides a convenient way to install all supported OpenTelemetry Collector Exporters. You will need an exporter to send the data to SigNoz.

    note

    💡 The opentelemetry-exporter-otlp is a convenient way to install all supported OpenTelemetry exporters. Currently it installs:

    • opentelemetry-exporter-otlp-proto-http
    • opentelemetry-exporter-otlp-proto-grpc

    We recommend using the http exporter for sending data to SigNoz.

  3. Add automatic instrumentation
    The below command inspects the dependencies of your application and installs the instrumentation packages relevant for your Python application.

    opentelemetry-bootstrap --action=install

  1. Run your application
    In the final run command, you can configure environment variables and flags. Flags for exporters:
    HTTP: otlp_proto_http
    gRPC: otlp_proto_grpc

    We recommend using the otlp_proto_http exporter.

    note

    Don’t run app in reloader/hot-reload mode as it breaks instrumentation. For example, if you use export FLASK_ENV=development, it enables the reloader mode which breaks OpenTelemetry isntrumentation.

    To start sending data to SigNoz, use the following run command:

    OTEL_RESOURCE_ATTRIBUTES=service.name=<service_name> OTEL_EXPORTER_OTLP_ENDPOINT="http://<IP of SigNoz Backend>:4318"  opentelemetry-instrument --traces_exporter otlp_proto_http --metrics_exporter otlp_proto_http <your run command>

    <service_name> is the name of service you want

    <your_run_command> can be python3 app.py or flask run

    IP of SigNoz backend is the IP of the machine where you installed SigNoz. If you have installed SigNoz on localhost, the endpoint will be http://localhost:4318.

    Replacing these environment variables, a sample final run command will look like this:

    OTEL_RESOURCE_ATTRIBUTES=service.name=python_app OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4318"  opentelemetry-instrument --traces_exporter otlp_proto_http --metrics_exporter otlp_proto_http python3 app.py
    note

    The port numbers are 4317 and 4318 for the gRPC and HTTP exporters respectively. Remember to allow incoming requests to port 4317/4318 of machine where SigNoz backend is hosted.

Validating instrumentation by checking for traces​

With your application running, you can verify that you’ve instrumented your application with OpenTelemetry correctly by confirming that tracing data is being reported to SigNoz.

To do this, you need to ensure that your application generates some data. Applications will not produce traces unless they are being interacted with, and OpenTelemetry will often buffer data before sending. So you need to interact with your application and wait for some time to see your tracing data in SigNoz.

Validate your traces in SigNoz:

  1. Trigger an action in your app that generates a web request. Hit the endpoint a number of times to generate some data. Then, wait for some time.
  2. In SigNoz, open the Services tab. Hit the Refresh button on the top right corner, and your application should appear in the list of Applications.
  3. Go to the Traces tab, and apply relevant filters to see your application’s traces.

You might see other dummy applications if you’re using SigNoz for the first time. You can remove it by following the docs here.

Python Application in the list of services being monitored in SigNoz
Python Application in the list of services being monitored in SigNoz

Instrumenting different Python Frameworks​

The opentelemetry-distro package can initialize instrumentation for a lot of popular Python frameworks. You can find a complete list here. For popular Python frameworks too, the distro provides a quick way to get started with automatic instrumentation.

Django Instrumentation​

It is recommended to use the opentelemetry distro for instrumenting Django applications. Though for Django, you must define DJANGO_SETTINGS_MODULEcorrectly. If your project is called mysite, something like following should work:

export DJANGO_SETTINGS_MODULE=mysite.settings

Please refer the official Django docs for more details.

Flask Instrumentation​

It is recommended to use the opentelemetry distro for instrumenting Flask applications.

FastAPI Instrumentation​

It is recommended to use the opentelemetry distro for instrumenting FastAPI applications.

Falcon Instrumentation​

It is recommended to use the opentelemetry distro for instrumenting Falcon applications.

Database Instrumentation​

Make sure that the DB client library you are using has the corresponding instrumentation library, and the version of the DB client library is supported by OpenTelemetry.

MongoDB​

You can use opentelemetry-distro to initialize instrumentation for your MongoDB database calls. You need to ensure that the version of your DB client library is supported by OpenTelemetry. For MongoDB, the instrumentation library is opentelemetry-instrumentation-pymongo.

You can check the supported versions here.

Redis​

You can use opentelemetry-distro to initialize instrumentation for your Redis database calls. You need to ensure that the version of your DB client library is supported by OpenTelemetry. For Redis, the instrumentation library is opentelemetry-instrumentation-redis.

You can check the supported versions here.

MySQL​

You can use opentelemetry-distro to initialize instrumentation for your MySQL database calls. You need to ensure that the version of your DB client library is supported by OpenTelemetry. For MySQL, we have two isntrumentation libraries:

  • opentelemetry-instrumentation-mysql
  • opentelemetry-instrumentation-pymysql

You can check the supported versions here.

Postgres​

You can use opentelemetry-distro to initialize instrumentation for your PostgreSQL database calls. You need to ensure that the version of your DB client library is supported by OpenTelemetry. For Postgres, the instrumentation library is opentelemetry-instrumentation-psycopg2.

You can check the supported versions here.

note

psycopg2-binary is not supported by opentelemetry auto instrumentation libraries as it is not recommended for production use. Please use psycopg2 to see DB calls also in your trace data in SigNoz

Running applications with Gunicorn, uWSGI​

For application servers which are based on pre fork model like Gunicorn, uWSGI you have to add a post_fork hook or a @postfork decorator in your configuration.

Check this documentation from OpenTelemetry on how to set it up.

Here's a working example where we have configured a gunicorn server with post_fork hook.

 

Troubleshooting your SigNoz installation​

Spans are not being reported​

If spans are not being reported to SigNoz, try enabling debug exporter which writes the json formatted trace data to console.

opentelemetry-instrument --traces_exporter otlp_proto_http,console --metrics_exporter otlp_proto_http,console <your run command>:

{
    "name": "alice",
    "context": {
        "trace_id": "0xedb7caf0c8b082a9578460a201759193",
        "span_id": "0x57cf7eee198e1fed",
        "trace_state": "[]"
    },
    "kind": "SpanKind.INTERNAL",
    "parent_id": null,
    "start_time": "2022-03-27T14:55:18.804758Z",
    "end_time": "2022-03-27T14:55:18.804805Z",
    "status": {
        "status_code": "UNSET"
    },
    "attributes": {},
    "events": [],
    "links": [],
    "resource": {
        "telemetry.sdk.language": "python",
        "telemetry.sdk.name": "opentelemetry",
        "telemetry.sdk.version": "1.10.0",
        "service.name": "my-service"
    }
}

 

Sample Application​

  • Working example where we have configured a gunicorn server with post_fork hook.

Frequently Asked Questions​

  1. How to find what to use in IP of SigNoz if I have installed SigNoz in Kubernetes cluster?

    Based on where you have installed your application and where you have installed SigNoz, you need to find the right value for this. Please use this grid to find the value you should use for IP of SigNoz

  2. I am sending data from my application to SigNoz, but I don't see any events or graphs in the SigNoz dashboard. What should I do?

    This could be because of one of the following reasons:

    1. Your application is generating telemetry data, but not able to connect with SigNoz installation

      Please use this troubleshooting guide to find if your application is able to access SigNoz installation and send data to it.

    2. Your application is not actually generating telemetry data

      Please check if the application is generating telemetry data first. You can use Console Exporter to just print your telemetry data in console first. Join our Slack Community if you need help on how to export your telemetry data in console

    3. Your SigNoz installation is not running or behind a firewall

      Please double check if the pods in SigNoz installation are running fine. docker ps or kubectl get pods -n platform are your friends for this.