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.

Configure the Sample Rate

First, enable

• Setting a uniform sample rate for all transactions using the traces_sample_rate option in your SDK config to a number between 0 and 1. (For example, to send 20% of transactions, set traces_sample_rate to 0.2.)
• 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.

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.

Next Steps: