Do you need to set up?
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.
Once you configure the sample rate, tracing will be enabled in your app. Set the sample rate for your transactions by either:
- Setting a uniform sample rate for all transactions using the
traces_sample_rateoption in your SDK config to a number between
1. (For example, to send 20% of transactions, set
- Controlling the sample rate based on the transaction itself and the context in which it's captured, by providing a function to the
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 traces_sample_rate=0.2, # Alternatively, to control sampling dynamically traces_sampler=traces_sampler )
Learn more about how the options work in Sampling Transactions.
Verify that performance monitoring is working correctly by setting
1.0 as that ensures that every transaction will be sent to Sentry.
Once testing is complete, we recommend lowering this value in production by either lowering your
traces_sample_rate value, or switching to using
traces_sampler to dynamically sample and filter your transactions.