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.
Python versions 2.7 and 3.4 and up are supported.
Install the Python Auto-Installer, using pip.
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pip install ls-trace
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.
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from ddtrace import tracer
from ddtrace.propagation.b3 import B3HTTPPropagator
tracer.configure(http_propagator=B3HTTPPropagator)
To send data from your system to Cloud Observability, you need to configure the Auto-Installer to:
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
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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
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export DD_TRACE_AGENT_URL=https://ingest.lightstep.com:443
export DD_TRACE_GLOBAL_TAGS=lightstep.service_name:<service_name>,lightstep.access_token:<access_token>
Developer Mode
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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
:access_token
: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 app.py
then:$ ls-trace-run python app.py
Following are issues you may have after instrumentation, and how to resolve them.
Symptom
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:
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receivers:
datadog:
operation_name_extractors:
- 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.
Following are the supported frameworks, data stores, and libraries that are auto-instrumented when you run your app.
Framework | Supported 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 |
Datastore | Supported 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 |
SQLite3 | Fully Supported |
Vertica | >= 0.6 |
Library | Supported Version |
---|---|
asyncio | Fully Supported |
gevent | >= 1.0 |
aiobotocore | >= 0.2.3 |
Boto2 | >= 2.29.0 |
Botocore | >= 1.4.51 |
Celery | >= 4.0.2 |
Futures | Fully Supported |
Grpc | >= 1.8.0 |
httplib | Fully Supported |
Jinja2 | >= 2.7 |
Kombu | >= 4.0 |
Mako | >= 0.1.0 |
Requests | >= 2.08 |
If you’re using a mix of Datadog and Cloud Observability you must use B3 header propagation.
Python Manual Instrumentation with OpenTracing
Measure your instrumentation quality
Updated Mar 3, 2020