Starlette Error & Performance Monitoring
Actionable insights to solve Starlette errors.
Getting Started is Simple
Grab the Sentry Python SDK:
pip install --upgrade sentry-sdk
Configure your DSN:
from starlette.applications import Starlette import sentry_sdk sentry_sdk.init( dsn="https://<key>@sentry.io/<project>", # Set traces_sample_rate to 1.0 to capture 100% # of transactions for Tracing. # We recommend adjusting this value in production, traces_sample_rate=1.0, # If you wish to associate users to errors (assuming you are using # django.contrib.auth) you may enable sending PII data. send_default_pii=True, ) app = Starlette(routes=[...])
Check our documentation for the latest instructions.
See all platformsMore than 150K Organizations Trust Sentry with Their Application Monitoring
Starlette Error Monitoring with Complete Stack Traces
See Starlette stack trace details like the class and method names so you never have to guess. Filter and group Starlette exceptions intuitively to eliminate noise. Monitor errors at scale without impacting throughput in production.
Starlette Performance Monitoring
Quickly identify Starlette performance issues before they become downtime with performance monitoring. View the entire end-to-end distributed trace to see the exact, poor-performing API call and surface any related errors.
Fill In The Blanks About Starlette Errors
Expose the important events that led to each Starlette exception: app lifecycle, user actions, debug logs, network requests, past errors.
See the Full Picture of Any Starlette Exception
With Sentry's exceptional exception handling in Starlette, you can triage quickly based on specific parameters like platform, device type, or page name, for each issue. Set custom tags to recreate the error environment relevant to your app, business concerns, and users.
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