We’ve been feasting at the Open Source table without paying the maintainers for too long. The Open Source Pledge is looking to change that. Will you join us?
Dismiss banner

Django Error Monitoring

Actionable insights to resolve Django performance bottlenecks and errors. Improve your monitoring workflow with a full view of releases so you can mark Django errors as resolved and prioritize live issues.

Getting Started is Simple

Install our Python SDK using pip:

Bash
pip install --upgrade sentry-sdk

Initialize the Python SDK with the Django integration in your settings.py file.

Python
import sentry_sdk
from sentry_sdk.integrations.django import DjangoIntegration

sentry_sdk.init(
    dsn="https://<key>@sentry.io/<project>",
    integrations=[DjangoIntegration()],

    # 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
)

Check our documentation for the latest instructions.

See All Platforms

More than 150K Organizations Trust Sentry with Their Application Monitoring

Django Performance Monitoring

Within minutes after installing Sentry, software teams are able to trace Django performance issues back to a poor performing API call as well as surface all related code errors. Engineering Managers and Developers now have a single tool to optimize performance of their code and deliver fast customer experiences with Performance Monitoring.
See a Sample Transaction

Complete Stack Traces, With Local Variables

See local variables in the stack for prod errors, just like in your dev environment. Introspect more deeply into the runtime and jump into the frame to get additional data for any local variable. Filter and group Django exceptions intuitively to eliminate noise.
See a Sample Stack Trace

Fill In the Blanks

Expose the important events that led to each Django exception: SQL queries, debug logs, network requests, past errors. Learn in which version a bug first appeared, merge duplicates, and know if things regress in a future release.
Check out Breadcrumbs
Sentry Logs showing structured log output alongside errors and traces

Your Logs, Next to the Request

Send your Django logging output to Sentry and query it alongside the request trace and the exception. The log lines that surrounded a failed view are attached to it, so you can see the retry, the failed upstream call, or the unexpected state that caused it.

Learn more about Logs in Sentry.

Explore Logs

"Sentry helps our team fix the most important issues in each release."

Jaylum Chen
Staff Software Engineer
Eventbrite

See the Full Picture of Any Exception

Aggregate errors by details like HTTP request, hostname, and app version to see what's new, a priority, or a trend.

Assign custom tags to reproduce the error environment specific to your application, business, and users.

Find answers to key questions: How actionable is this error? In which app release did the Django bug occur?

FAQs

Install the Sentry Python SDK and enable tracing. Sentry then instruments your Django app automatically: the middleware stack, synchronous signal receivers, database queries, cache read operations, and Redis commands all become spans on a distributed trace, so you can see which layer made a request slow.

Add Profiling to get function-level detail on the slowest requests, and Logs to keep your Django logs beside the trace that produced them. Sentry supports Django 1.8 and above.

Yes. The Django integration instruments your database queries automatically and records each one as a span, so slow and repeated queries show up directly on the trace for a request. Cache reads and Redis commands are instrumented the same way.

Because queries are attached to the trace rather than sitting in a separate tool, you can see the request, the query that slowed it down, and any related error together. Learn more about Tracing.

Yes. Sentry Logs lets you send, view, and query structured logs from your application alongside your errors and traces. Because logs sit next to the error and the trace that produced them, you get the granular context — retries, API failures, internal state — that spans and stack traces alone can miss, without switching tools.

Learn more about Logs in Sentry.

Seer is Sentry's AI debugging agent. It reads the full context Sentry already has — the error, its stack trace, the surrounding trace, logs, and profiles — to find the root cause of an issue and propose a fix. Seer can open a pull request with that fix, hand the work to an external coding agent, or review your PRs before they ship.

Learn more about Seer and Autofix.

You can get started for free. Pricing depends on the number of monthly events, transactions, and attachments that you send Sentry. For more details, visit our pricing page.

Sentry doesn't impact a web site's performance.

If you look at the configuration options for when you initialize Sentry in your code, you'll see there's nothing regarding minimizing its impact on your app's performance. This is because our team of SDK engineers already developed Sentry with this in mind.

Sentry is a listener/handler for errors that asynchronously sends out the error/event to Sentry.io. This is non-blocking. The error/event only goes out if this is an error.

Global handlers have almost no impact as well, as they are native APIs provided by the browsers.

Supporting Resources

How Slow Is Slow

Eventbrite Customer Story

Resolve Django errors with max efficiency, not max effort