OpenTelemetry Python Instrumentation

Get up and running with OpenTelemetry in just a few quick steps!

The setup process consists of two phases:

Getting OpenTelemetry installed and configured
Validating that configuration to ensure that data is being sent as expected.

This guide explains how to download, install, and run OpenTelemetry in Python.

Requirements#

Python 3.4 or newer
An app to add OpenTelemetry to

We follow OpenTelemetry python instrumentation library. We shall be exporting data in Jaeger Thrift protocol.

pip3 install opentelemetry-distro
pip3 install opentelemetry-instrumentation
pip3 install opentelemetry-exporter-otlp

If it hangs while installing grpcio during pip3 install opentelemetry-exporter-otlp then follow below steps as suggested in this stackoverflow link

pip3 install --upgrade pip
python3 -m pip install --upgrade setuptools
pip3 install --no-cache-dir --force-reinstall -Iv grpcio

Retry installing opentelemetry-exporter-otlp by doing

pip3 install opentelemetry-exporter-otlp

opentelemetry-bootstrap --action=install

The above command inspects the active Python site-packages and figures out which instrumentation packages the user might want to install and installs them for you.

note

If it says cannot find command opentelemetry-bootstrap then you need to specify the path of the file. In ubuntu, it is at /home/ubuntu/.local/bin/opentelemetry-bootstrap. So your command becomes, /home/ubuntu/.local/bin/opentelemetry-bootstrap --action=install

Run Command#

OTEL_METRICS_EXPORTER=none OTEL_RESOURCE_ATTRIBUTES=service.name=<service_name> OTEL_EXPORTER_OTLP_ENDPOINT="http://<IP of SigNoz Backend>:4317"  opentelemetry-instrument <your run command>

<service_name> is the name of service you want

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

note

If opentelemetry-instrument command is not found then use full path of executable. In ubuntu it is at /home/ubuntu/.local/bin/opentelemetry-instrument
Remember to allow incoming requests to port 4317 of machine where SigNoz backend is hosted

Instrumenting a sample Flask application#

We have included a sample flask application with README.md at https://github.com/SigNoz/sample-flask-app.

Feel free to use this repo to test out OpenTelemetry instrumentation and how to send telemetry data to SigNoz.

Instrumenting Django Applications#

For instrumenting Django applications, the instructions are same as for a Flask app as mentioned above.

Though for Django, you must define DJANGO_SETTINGS_MODULE correctly. If your project is called mysite, somwthing like following should work

export DJANGO_SETTINGS_MODULE=mysite.settings

Please refer the official Django docs for more details

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 om how to set it up.

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

Troubleshooting your installation#

If spans are not being reported to SigNoz, try running in debug mode by setting OTEL_LOG_LEVEL=debug:

The debug log level will print out the configuration information. It will also emit every span to the console, which should look something like:

Span {
  attributes: {},
  links: [],
  events: [],
  status: { code: 0 },
  endTime: [ 1597810686, 885498645 ],
  _ended: true,
  _duration: [ 0, 43333 ],
  name: 'bar',
  spanContext: {
    traceId: 'eca3cc297720bd705e734f4941bca45a',
    spanId: '891016e5f8c134ad',
    traceFlags: 1,
    traceState: undefined
  },
  parentSpanId: 'cff3a2c6bfd4bbef',
  kind: 0,
  startTime: [ 1597810686, 885455312 ],
  resource: Resource { labels: [Object] },
  instrumentationLibrary: { name: 'example', version: '*' },
  _logger: ConsoleLogger {
    debug: [Function],
    info: [Function],
    warn: [Function],
    error: [Function]
  },
  _traceParams: {
    numberOfAttributesPerSpan: 32,
    numberOfLinksPerSpan: 32,
    numberOfEventsPerSpan: 128
  },
  _spanProcessor: MultiSpanProcessor { _spanProcessors: [Array] }
},