Set Up Performance
With performance monitoring, Sentry tracks your software performance, measuring metrics like throughput and latency, and displaying the impact of errors across multiple systems. Sentry captures distributed traces consisting of transactions and spans, which measure individual services and individual operations within those services. Learn more about our model in Distributed Tracing.
If you’re adopting Performance in a high-throughput environment, we recommend testing prior to deployment to ensure that your service’s performance characteristics maintain expectations.
Configure the Sample Rate
First, enable both
- Setting a uniform sample rate for all transactions using the
traces_sample_rate
option in your SDK config to a number between0
and1
. (For example, to send 20% of transactions, settraces_sample_rate
to0.2
.) - Controlling the sample rate based on the transaction itself and the context in which it's captured, by providing a function to the
traces_sampler
config option.
The two options are meant to be mutually exclusive. If you set both, traces_sampler
will take precedence.
Performance Monitoring is available for the Sentry Python SDK version ≥ 0.11.2.
import sentry_sdk
def traces_sampler(sampling_context):
# ...
# return a number between 0 and 1 or a boolean
sentry_sdk.init(
dsn="https://examplePublicKey@o0.ingest.sentry.io/0",
# To set a uniform sample rate
# Set traces_sample_rate to 1.0 to capture 100%
# of transactions for performance monitoring.
# We recommend adjusting this value in production,
traces_sample_rate=1.0,
# Alternatively, to control sampling dynamically
traces_sampler=traces_sampler
)
Learn more about how the options work in Sampling Transactions.
Verify
While you're testing, set traces_sample_rate
to 1.0
, as that ensures that every transaction will be sent to Sentry.
Once testing is complete, you may want to set a lower traces_sample_rate
value, or switch to using traces_sampler
to selectively sample and filter your transactions, based on contextual data.
Connecting Services
If you are also using Performance Monitoring for JavaScript, depending on where your request originates, you can connect traces:
- For requests that start in your backend, by adding a meta tag in your HTML template that contains tracingThe process of logging the events that took place during a request, often across multiple services.information.
- For requests that start in JavaScript, by the SDK setting a header on requests to your backend.
Otherwise, backend services with Performance Monitoring connect automatically.
Next Steps:
Our documentation is open source and available on GitHub. Your contributions are welcome, whether fixing a typo (drat!) to suggesting an update ("yeah, this would be better").
- Package:
- pypi:sentry-sdk
- Version:
- 1.25.0
- Repository:
- https://github.com/getsentry/sentry-python