Setting Up Cloud Logging for Python

You can write logs to Logging from Python applications by using the Python logging handler included with the Logging client library, or by using Cloud Logging API Cloud client library for Python directly.

Before you begin

  1. Sign in to your Google Account.

    If you don't already have one, sign up for a new account.

  2. In the Cloud Console, on the project selector page, select or create a Cloud project.

    Go to the project selector page

  3. Make sure that billing is enabled for your Google Cloud project. Learn how to confirm billing is enabled for your project.

  4. Enable the Cloud Logging API.

    Enable the API

  5. Prepare your environment for Python development.

    Go to the Python setup guide

Installing the library

To install the Cloud Logging library for Python, see Installing the client library.

Once installed, this library includes logging handlers to connect Python's standard logging module to Logging, as well as an API client library to access Cloud Logging manually.

Connecting the library to Python logging

To send all log entries to Cloud Logging by attaching the Cloud Logging handler to the Python root logger, use the setup_logging helper method:

logging/cloud-client/handler.py 
# Imports the Cloud Logging client library
import google.cloud.logging

# Instantiates a client
client = google.cloud.logging.Client()

# Retrieves a Cloud Logging handler based on the environment
# you're running in and integrates the handler with the
# Python logging module. By default this captures all logs
# at INFO level and higher
client.get_default_handler()
client.setup_logging()

Using the Python root logger

Once the handler is attached, any logs at, by default, INFO level or higher which are emitted in your application will be sent to Logging:

logging/cloud-client/handler.py 
# Imports Python standard library logging
import logging

# The data to log
text = 'Hello, world!'

# Emits the data using the standard logging module
logging.warning(text)

If messages are logged to Logging from App Engine or Google Kubernetes Engine, the handler will send them to those environments' respective resource types; otherwise, logs will by default appear under the python log in the Global resource type.

Configuring the logging handler

To attach the Cloud Logging logging handler to only select Python loggers, or to otherwise configure the logging handler, go to the API library documentation.

For more information on installation, see the documentation for the Cloud Logging library for Python. You can also report issues using the issue tracker.

Using the Cloud Client Library directly

For information on using the Cloud Logging Cloud client library for Python directly, see Cloud Logging Client Libraries.

Running on Google Cloud

Using Cloud Logging library for Python requires the Cloud IAM Logs Writer role on Google Cloud. Most Google Cloud environments provide this role by default.

App Engine

App Engine grants the Logs Writer role by default.

The Cloud Logging library for Python can be used without needing to explicitly provide credentials.

Cloud Logging is automatically enabled for App Engine applications. No additional setup is required.

Google Kubernetes Engine

On Google Kubernetes Engine, you must add the logging.write access scope when creating the cluster:

gcloud container clusters create example-cluster-name --scopes https://www.googleapis.com/auth/logging.write

Compute Engine

When using Compute Engine VM instances, add the cloud-platform access scope to each instance. When creating a new instance through the Google Cloud Console, you can do this in the Identity and API access section of the Create Instance panel. Use the Compute Engine default service account or another service account of your choice, and select Allow full access to all Cloud APIs in the Identity and API access section. Whichever service account you select, ensure that it has been granted the Logs Writer role in the IAM & admin section of the Cloud Console.

Running locally and elsewhere

To use the Cloud Logging library for Python outside of Google Cloud, including running the library on your own workstation, on your data center's computers, or on the VM instances of another cloud provider, you must supply your Google Cloud project ID and appropriate service account credentials directly to the Cloud Logging library for Python.

You can create and obtain service account credentials manually. When specifying the Role field, use the Logs Writer role. For more information on Cloud Identity and Access Management roles, go to Access control guide.

Viewing the logs

After deployment, you can view the logs in the Cloud Console Logs Viewer.

Go to the Logs Viewer

In the Logs Viewer, you must specify one or more resources, but the resource selection might not be obvious. Here are some tips to help you get started:

  • If you are deploying your application to App Engine or using the App Engine-specific libraries, set your resource to GAE Application.

  • If you are deploying your application on Compute Engine, set the resource to GCE VM Instance.

  • If you are deploying your application on Google Kubernetes Engine, your cluster's logging configuration determines the resource type of the log entries. For a detailed discussion on the Legacy Google Cloud's operations suite and the Google Cloud's operations suite Kubernetes Monitoring solutions, and how those options affect the resource type, see Migrating to Google Cloud's operations suite Kubernetes Monitoring.

  • If your application is using the Cloud Logging API directly, the resource is dependent on the API and your configuration. For example, in your application, you can specify a resource or use a default resource.

  • If you don't see any logs in the Logs Viewer, to see all log entries, switch to the advanced query mode and use an empty query.

    1. To switch to the advanced query mode, click menu (▾) at the top of the Logs Viewer and then select Convert to advanced filter.
    2. Clear the content that appears in the filter box.
    3. Click Submit Filter.

    You can examine the individual entries to identify your resources.

For additional information, see Viewing Logs and Advanced logs queries.