# RQ Error Monitoring

> Trace RQ performance issues back to poor performing API calls & performance errors with RQ error monitoring by Sentry. Request a demo today.

**URL:** https://sentry.io/for/rq/

---

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

**Documentation:** [https://docs.sentry.io/platforms/python/integrations/rq/](https://docs.sentry.io/platforms/python/integrations/rq/)

## Install

Install the [Sentry Python SDK](https://github.com/getsentry/sentry-python) from PyPI:

```bash
pip install --upgrade sentry-sdk
```

Create a file called `mysettings.py` with the following content. The RQ integration is enabled automatically.

```python
import sentry_sdk

sentry_sdk.init(
    dsn="https://<key>@sentry.io/<project>",
    # Add data like request headers and IP for users, if applicable;
    # see https://docs.sentry.io/platforms/python/data-management/data-collected/ for more info
    send_default_pii=True,
    # 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,
)
```

Start your worker with:

```bash
rq worker -c mysettings
```

See the [RQ docs](https://docs.sentry.io/platforms/python/integrations/rq/) for full setup options.

## Features

### RQ Performance Monitoring

Within minutes after installing Sentry, software teams are able to trace RQ [performance](/product/tracing/) 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 [Tracing](/product/tracing/).

### RQ Error Monitoring with Complete Stack Traces

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 RQ exceptions intuitively to eliminate noise.

### Fill In the Blanks About RQ Errors

Expose the important events that led to each RQ 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.

---

*Source: [sentry.io/for/rq/](https://sentry.io/for/rq/)*