You can enable Cloud Trace for Python applications by using OpenCensus. OpenCensus is a set of instrumentation libraries for collecting trace and metric data that work with multiple backends. For the latest details about OpenCensus for Python, along with additional documentation and examples, go to census-instrumentation/opencensus-python.
Installation and configuration
Install the OpenCensus packages using
pip install opencensus pip install opencensus-ext-stackdriver
Update your application to import the Stackdriver exporter and
the OpenCensus tracer packages. Your application must also instantiate
from opencensus.ext.stackdriver import trace_exporter as stackdriver_exporter import opencensus.trace.tracer def initialize_tracer(project_id): exporter = stackdriver_exporter.StackdriverExporter( project_id=project_id ) tracer = opencensus.trace.tracer.Tracer( exporter=exporter, sampler=opencensus.trace.tracer.samplers.AlwaysOnSampler() ) return tracer
For more information on the exporter, see OpenCensus Tracing.
If you are running on Google Cloud infrastructure, then
you don't need to set
project_id to your Google Cloud
project ID. If you don't set this field, the client library for Python
automatically gathers this data from a Google Cloud metadata server.
If you aren't running on Google Cloud infrastructure, then you must supply your Google Cloud project ID to your application.
Regardless of your infrastructure,
when you don't explicitly set the Google Cloud project ID,
google-cloud Python library, which is invoked by OpenCensus,
automatically determines if the environment variable
is set, and if so, the library uses the value of
as your Google Cloud project ID. For more information on authentication
when using client libraries, see Authentication.
For general information, see Getting started with authentication.
To set the environment variable, do the following:
Linux or macOS
To reduce the performance impact of reporting trace data, have this data
sent by a background process. To configure background reporting of trace data,
transport=AsyncTransport when initializing the
Configuring your platform
You can use Cloud Trace on Google Cloud and other platforms.
Running on Google Cloud
When your application is running on Google Cloud, you don't need to provide authentication credentials in the form of a service account to the client library. However, you do need to ensure that your Google Cloud platform has the Cloud Trace API access scope enabled.
For the following configurations, the default access-scope settings enable the Cloud Trace API:
- App Engine flexible environment
App Engine standard environment
Google Kubernetes Engine (GKE)
If you use custom access scopes, then you must ensure that
Cloud Trace API access scope
is enabled. For
gcloud users, specify access scopes using the
and include the
trace.append Cloud Trace API access scope.
For example, to create a GKE cluster with only
the Cloud Trace API enabled, do the following:
gcloud container clusters create example-cluster-name --scopes=https://www.googleapis.com/auth/trace.append
Running locally and elsewhere
If your application is running outside of Google Cloud, then you must provide authentication credentials in the form of a service account to the client library. The service account must contain the Cloud Trace agent role. For instructions, see Creating a service account.
Google Cloud client libraries use
Application Default Credentials (ADC) to find your
application's credentials. You provide these credentials
by setting the
GOOGLE_APPLICATION_CREDENTIALS environment variable:
For a sample Python application that utilizes Flask, see the Trace Quickstart.
For details on how the application was instrumentated to capture Trace data, see Instrumentation.
Viewing the traces
After deployment, you can view the traces in the Cloud Console Trace Viewer.
For information on troubleshooting issues with Cloud Trace, go to the Troubleshooting page.
- Source code
- GitHub issue tracker
- Stack Overflow