Python Auto-Instrumentation

Want to use OpenTelemetry instead? Read these docs to get started!

If your app is written in Python, you can get started quickly with Cloud Observability. Download the Auto-Installer, then configure it to communicate with your Cloud Observability Microsatellites. When you deploy your app, all supported frameworks, data stores, and libraries will begin sending trace data to Cloud Observability.

To ensure you can access all Cloud Observability functionality, including infrastructure metrics reporting, update your tracer to the latest release. To update, simply follow the instructions for installing the tracer. No code changes are needed.

These Auto-Installers are forked from Datadog’s contribution of their tracers to the OpenTelemetry project. You can find the original Datadog docs here.

For Python Django applications, note that tracing is disabled when your application is launched in DEBUG mode.

Supported Python Versions

Python versions 2.7 and 3.4 and up are supported.

Install the Auto-Installer

Install the Python Auto-Installer, using pip.

pip install ls-trace

Import Tracer and Set B3 Headers for Trace Propagation

Cloud Observability recommends using B3 headers for trace propagation as the default, especially on hybrid deployments, as it is the most widely supported header at this time.

from ddtrace import tracer
from ddtrace.propagation.b3 import B3HTTPPropagator

Configure the Auto-Installer to Send Data to Cloud Observability

To send data from your system to Cloud Observability, you need to configure the Auto-Installer to:

  • Point to your Microsatellites
  • Send global tags required by Cloud Observability to ingest and display the data to you.

To configure the Auto-Installer:

Configure the Auto-Installer to point to the Cloud Observability Microsatellites by setting these environment variables. Use the right values, depending on if you are using on-premise, Cloud Observability public, or Developer Mode Satellites.

Start tabs

On-Premise Microsatellites

export DD_TRACE_AGENT_URL=https://<Satellite host>:<Satellite port>
export DD_TRACE_GLOBAL_TAGS=lightstep.service_name:<service_name>,lightstep.access_token:<access_token>

Public Microsatellites

export DD_TRACE_GLOBAL_TAGS=lightstep.service_name:<service_name>,lightstep.access_token:<access_token>

Developer Mode

export DD_TRACE_AGENT_URL=http://localhost:8360
export DD_TRACE_GLOBAL_TAGS=lightstep.service_name:<service_name>,lightstep.access_token:developer

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The host and port values for on-premise Microsatellites is your pool address, found in your configuration file.

When setting the environment variable DD_TRACE_GLOBAL_TAGS, the following variables must be included:

  • service_name:
    The name of the service from which spans originate. This tag allows Cloud Observability to accurately report on your services, with features such as the Service diagram and the Service Directory
  • access_token:
    The access token for the project the tracers report to. Cloud Observability Microsatellites need this token to accept and store span data from the tracer. Reports from clients with invalid or deactivated access tokens will be rejected on ingress.

Run Your App

To include the Auto-Installer’s auto-instrumentation, prefix your Python entry-point command with ls-trace-run.
For example, if your application is started with python then:
$ ls-trace-run python


Following are issues you may have after instrumentation, and how to resolve them.

Operation Names Aren’t Human Readable

Operation names in Cloud Observability are not clear or are very long and unhelpful.

This feature requires a Satellite upgrade to the June 2020 release.

This can happen because the auto-installer is getting the name from a parameter in Datadog that might not be appropriate for your language. You can set that parameter to different values to see if that results in better operation names.

You can use either the resource or the name parameter, or both.

Which to use (or if using the both, the order to use) depends on the language of the installer. Refer to the Datadog docs for more info.

To configure how the operation name is set, add the following parameter to your Microsatellite configuration:

  	  - resource
  	  - name

If you set both, the order of the values matters. Cloud Observability tries to extract a name from the first variable value. If one isn’t found, it looks for the second value and uses that.

What’s Auto-Instrumented

Following are the supported frameworks, data stores, and libraries that are auto-instrumented when you run your app.


FrameworkSupported Version
aiohttp>= 1.2
Bottle>= 0.11
Django>= 1.8
djangorestframework>= 3.4
Falcon>= 1.0
Flask>= 0.10
Molten>= 0.7.0
Pylons>= 0.9.6
Pyramid>= 1.7
Tornado>= 4.0

Data Stores

DatastoreSupported Version
Cassandra>= 3.5
Elasticsearch>= 1.6
Flask Cache>= 0.12
Memcached pylibmc>= 1.4
Memcached pymemcache>= 1.3
MongoDB Mongoengine>= 0.11
MongoDB Pymongo>= 3.0
MySQL MySQL-python>= 1.2.3
MySQL mysqlclient>= 1.3
MySQL mysql-connector>= 2.1
Postgres aiopg>= 0.12.0
Postgres psycopg>= 2.4
Redis>= 2.6
Redis redis-py-cluster>= 1.3.5
SQLAlchemy>= 1.0
SQLite3Fully Supported
Vertica>= 0.6


LibrarySupported Version
asyncioFully Supported
gevent>= 1.0
aiobotocore>= 0.2.3
Boto2>= 2.29.0
Botocore>= 1.4.51
Celery>= 4.0.2
FuturesFully Supported
Grpc>= 1.8.0
httplibFully Supported
Jinja2>= 2.7
Kombu>= 4.0
Mako>= 0.1.0
Requests>= 2.08

Use Datadog Tracers with Cloud Observability Tracers

If you’re using a mix of Datadog and Cloud Observability you must use B3 header propagation.

See also

Python Manual Instrumentation with OpenTracing

Measure your instrumentation quality

Updated Mar 3, 2020