---
title: "Sending Span Metrics"
description: "Learn how to add attributes to spans in Sentry to monitor performance and debug applications "
url: https://docs.sentry.io/platforms/python/tracing/span-metrics/
---

# Sending Span Metrics | Sentry for Python

##### Looking for standalone counters, gauges, or distributions?

Span metrics are great for enriching your existing traces with custom data. If you need metrics that are independent of tracing — such as business event counters, success/failure rates, or aggregates that aren't affected by trace sampling — use [Application Metrics](https://docs.sentry.io/platforms/python/metrics.md) instead.

To use span metrics, you must first [configure tracing](https://docs.sentry.io/platforms/python/tracing.md) in your application.

Span metrics allow you to extend the default metrics that are collected by tracing and track custom performance data and debugging information within your application's traces. There are two main approaches to instrumenting metrics:

1. [Adding metrics to existing spans](https://docs.sentry.io/platforms/python/tracing/span-metrics.md#adding-metrics-to-existing-spans)
2. [Creating dedicated spans with custom metrics](https://docs.sentry.io/platforms/python/tracing/span-metrics.md#creating-dedicated-metric-spans)

This page covers both transaction mode (default) and stream mode. See [Streamed Spans](https://docs.sentry.io/platforms/python/tracing/streamed-spans.md) to learn more.

## [Adding Metrics to Existing Spans](https://docs.sentry.io/platforms/python/tracing/span-metrics.md#adding-metrics-to-existing-spans)

You can enhance existing spans with custom metrics by adding data. This is useful when you want to augment automatic instrumentation or add contextual data to spans you've already created.

```python
span = sentry_sdk.get_current_span()
if span:
    # Add individual metrics
    span.set_data("database.rows_affected", 42)
    span.set_data("cache.hit_rate", 0.85)
    span.set_data("memory.heap_used", 1024000)
    span.set_data("queue.length", 15)
    span.set_data("processing.duration_ms", 127)
```

*Other available variations of the above snippet: Stream Mode*

### [Best Practices for Span Data](https://docs.sentry.io/platforms/python/tracing/span-metrics.md#best-practices-for-span-data)

When adding metrics as span data:

* Use consistent naming conventions (for example, `category.metric_name`)
* Keep attribute names concise but descriptive
* Use appropriate data types (string, number, boolean, or an array containing only one of these types)

## [Creating Dedicated Metric Spans](https://docs.sentry.io/platforms/python/tracing/span-metrics.md#creating-dedicated-metric-spans)

For more detailed operations, tasks, or process tracking, you can create custom dedicated spans that focus on specific metrics or attributes that you want to track. This approach provides better discoverability and more precise span configurations, however it can also create more noise in your trace waterfall.

```python
with sentry_sdk.start_span(
    op="db.metrics",
    name="Database Query Metrics"
) as span:
    # Set metrics after creating the span
    span.set_data("db.query_type", "SELECT")
    span.set_data("db.table", "users")
    span.set_data("db.execution_time_ms", 45)
    span.set_data("db.rows_returned", 100)
    span.set_data("db.connection_pool_size", 5)
    # Your database operation here
    pass
```

*Other available variations of the above snippet: Stream Mode*

For detailed examples of how to implement span metrics in common scenarios, see our [Span Metrics Examples](https://docs.sentry.io/platforms/python/tracing/span-metrics/examples.md) guide.

## [Adding Metrics to All Spans](https://docs.sentry.io/platforms/python/tracing/span-metrics.md#adding-metrics-to-all-spans)

How you add data to every span depends on your tracing mode:

```python
import sentry_sdk
from sentry_sdk.types import Event, Hint

def before_send_transaction(event: Event, hint: Hint) -> Event | None:
    # Add attributes to the root span (transaction)
    if "trace" in event.get("contexts", {}):
        if "data" not in event["contexts"]["trace"]:
            event["contexts"]["trace"]["data"] = {}

        event["contexts"]["trace"]["data"].update({
            "app_version": "1.2.3",
            "environment_region": "us-west-2"
        })

    # Add attributes to all child spans
    for span in event.get("spans", []):
        if "data" not in span:
            span["data"] = {}

        span["data"].update({
            "component_version": "2.0.0",
            "deployment_stage": "production"
        })

    return event

sentry_sdk.init(
    # ...
    before_send_transaction=before_send_transaction
)
```

*Other available variations of the above snippet: Stream Mode*

For detailed examples of how to implement span metrics in common scenarios, see our [Span Metrics Examples](https://docs.sentry.io/platforms/python/tracing/span-metrics/examples.md) guide.

## Pages in this section

- [Example Instrumentation](https://docs.sentry.io/platforms/python/tracing/span-metrics/examples.md)
- [Sending Performance Metrics](https://docs.sentry.io/platforms/python/tracing/span-metrics/performance-metrics.md)