---
title: "Application Metrics"
description: "Send counters, gauges, and distributions from your code to track application health and drill down into related traces, logs, and errors."
url: https://docs.sentry.io/product/explore/metrics/
---

# Application Metrics

## [Overview](https://docs.sentry.io/product/explore/metrics.md#overview)

With Sentry's Application Metrics, you can send [counters](https://docs.sentry.io/product/explore/metrics.md#counters), [gauges](https://docs.sentry.io/product/explore/metrics.md#gauges), and [distributions](https://docs.sentry.io/product/explore/metrics.md#distributions) from your code to track application health signals like `email.sent`, `checkout.failed`, or `queue.depth`. What makes Sentry's Application Metrics unique is that every metric event is **trace-connected**, meaning you can click directly into the related traces, logs, and errors when something looks off.

Unlike traditional metrics tools that only show *if* something's changed, Sentry's trace-connected metrics let you understand *why* it changed. When a `checkout.failed` counter spikes, you can click into a sample and see the exact trace, spans, logs, and errors that produced that metric event.

Not everything in your application generates an error or requires full tracing. Application Metrics are perfect for tracking:

* **Business events**: `checkout.started`, `checkout.failed`, `payment.declined`, `refund.issued`
* **Application health**: `email.sent`, `email.failed`, `job.processed`, `job.retried`
* **Resource utilization**: `queue.depth`, `pool.in_use`, `cache.hit_rate`
* **User behavior**: `search.zero_results`, `feature.enabled`, `configuration.loaded`

## [Set Up Application Metrics](https://docs.sentry.io/product/explore/metrics.md#set-up-application-metrics)

To get started, navigate to the [Getting Started](https://docs.sentry.io/product/explore/metrics/getting-started.md) page and select your SDK from the list.

## [Metric Types](https://docs.sentry.io/product/explore/metrics.md#metric-types)

Sentry supports three types of metrics:

### [Counters](https://docs.sentry.io/product/explore/metrics.md#counters)

Counters track how many times something happened. Each increment adds to a cumulative total.

**Aggregation methods**: `sum`, `per_second`, and `per_minute`.

**Use cases**: events that occur over time

* `email.sent` - Track total emails sent
* `checkout.failed` - Track failed checkout attempts
* `api.request` - Track API calls

### [Gauges](https://docs.sentry.io/product/explore/metrics.md#gauges)

Gauges set a specific value at a point in time, like a snapshot. The latest value replaces the previous one.

**Aggregation methods**: `min`, `max`, `avg`, `per_second`, and `per_minute`.

**Use cases**: current state or level

* `queue.depth` - Current number of items in queue
* `pool.in_use` - Active connections in a pool
* `memory.usage` - Current memory consumption

### [Distributions](https://docs.sentry.io/product/explore/metrics.md#distributions)

Distributions record numeric values to compute statistical aggregates.

**Aggregation methods**: `p50`, `p75`, `p90`, `p95`, `p99`, `avg`, `sum`, `min`, `max`, `count`, `per_second`, and `per_minute`.

**Use cases**: values that vary and need statistical analysis

* `cart.amount_usd` - Purchase amounts for revenue tracking
* `query.duration_ms` - Query latency for performance monitoring
* `file.size_bytes` - File sizes for storage analysis

## [Viewing and Exploring Application Metrics](https://docs.sentry.io/product/explore/metrics.md#viewing-and-exploring-application-metrics)

The Metrics Explorer provides two main views:

### [Aggregates View](https://docs.sentry.io/product/explore/metrics.md#aggregates-view)

The Aggregates tab shows trends and totals across any attributes you've added to your metrics. You can:

* View time-series charts showing metric trends
* Group by custom attributes (e.g., `sum(metrics_value)` grouped by `email_type`)
* Apply filters to drill down into specific segments
* Compare multiple time periods

Use this view to spot trends, identify anomalies, and understand aggregate behavior across your application.

### [Samples View](https://docs.sentry.io/product/explore/metrics.md#samples-view)

The Samples tab shows individual metric events with **direct links to their traces**. This is where trace-connected metrics shine:

* See each individual metric event as it occurred
* Click any sample to open the full trace waterfall
* View related spans, logs, and errors from the same moment
* Understand the exact context that produced each metric

When you notice a spike or dip in the Aggregates view, switch to Samples to drill into specific occurrences and find the root cause.

### [Multiple Metrics and Equations](https://docs.sentry.io/product/explore/metrics.md#multiple-metrics-and-equations)

You can compare several metrics side-by-side in a single Explorer view and derive new values from them without leaving the page:

* Click **Add Metric** to add another metric query to the page. Each query gets its own panel and a short label (`A`, `B`, `C`, …) so you can reference it elsewhere. You can reorder queries by dragging their panels, and add up to 26 queries at once.
* Click **Add Equation** to create a calculated series that references existing metric labels — for example, `A / B` to compute a ratio between two counters, or `A - B` to subtract a baseline from a current value. Equations appear alongside your metric queries and can be added to dashboards and monitors alongside the underlying metrics.

## [Turning Metrics Into Monitors](https://docs.sentry.io/product/explore/metrics.md#turning-metrics-into-monitors)

Any metric query you build in the Explorer can be turned into a [Monitor](https://docs.sentry.io/product/monitors-and-alerts/monitors.md) so you get notified when its behavior changes.

* From the **Metrics Explorer**, open **Save As → Monitor for** and choose the metric/aggregate you want to monitor. Sentry will pre-fill the Monitor with the metric, aggregate, filters, group-by, and time interval from your current query.
* From **Discover**, use the **Create Monitor** button on an Application Metrics query to jump into the Monitor creation flow with the metric pre-selected.

When creating a [Monitor](https://docs.sentry.io/product/monitors-and-alerts/monitors.md), **Application Metrics** is available as a dataset alongside Errors, Spans, Logs, and Releases, and there's a dedicated **Application Metrics** template in the Monitor form to get you started quickly. The Monitor detects threshold breaches, percentage changes, or dynamic anomalies on the metric and creates an issue when conditions are met — which you can then route through [Alerts](https://docs.sentry.io/product/monitors-and-alerts/alerts.md) to Slack, PagerDuty, email, and more. See [Monitors](https://docs.sentry.io/product/monitors-and-alerts/monitors.md) for detailed configuration options.

## [Adding Metrics to Dashboards](https://docs.sentry.io/product/explore/metrics.md#adding-metrics-to-dashboards)

You can pin any metric query as a widget on a [Dashboard](https://docs.sentry.io/product/dashboards.md) for longer-term tracking:

* From the Metrics Explorer, open **Save As → Dashboard widget** and choose the metric query you want to visualize.
* If you have multiple metric queries on the page, you can add them individually or pick **All Metrics** to create a single widget containing all of them.

Equations can't currently be added as dashboard widgets — add the underlying metric queries instead.

## [Saving Queries](https://docs.sentry.io/product/explore/metrics.md#saving-queries)

Frequently-used metric queries can be saved and re-opened from the [Explorer](https://sentry.io/explore/metrics/):

* **Save As → New Query** stores your current metric queries, filters, group-bys, and time range under a name of your choosing.
* **Save As → Existing Query** updates a previously-saved query with your current configuration.

Saved queries show up in the Explorer's saved-query list and are accessible to everyone in your organization with Explorer access.

## [Trace-Connected Debugging Flow](https://docs.sentry.io/product/explore/metrics.md#trace-connected-debugging-flow)

Application Metrics debugging workflow:

1. **Spot the anomaly**: Notice a spike in your Aggregates view (e.g., `checkout.failed` increased 3x)
2. **Open samples**: Switch to the Samples tab to see individual metric events
3. **Pick a trace**: Click on a sample to open the full trace that produced it
4. **Find the cause**: Examine spans for slow queries, check logs for error messages, view related exceptions
5. **Fix the issue**: With full context in hand, identify and resolve the root cause

Instead of "metric alert → guesswork," debugging becomes a **single flow**: Metric spike → sample → trace → root cause.

## [Metric Attributes](https://docs.sentry.io/product/explore/metrics.md#metric-attributes)

Each metric event automatically includes:

| **Field**                             | **Description**                                                                                                       |
| ------------------------------------- | --------------------------------------------------------------------------------------------------------------------- |
| **name**                              | The metric identifier (e.g., `checkout.failed`)                                                                       |
| **kind**                              | The metric type (counter, gauge, or distribution)                                                                     |
| **value**                             | The numeric value                                                                                                     |
| **unit** *(optional)*                 | Unit of measurement (e.g., `usd`, `ms`, `bytes`). Rendered in the Samples table, trace view, and chart axes when set. |
| **timestamp**                         | When the metric was recorded                                                                                          |
| **project**                           | The project the metric belongs to                                                                                     |
| **trace\_id**                         | Links to the active trace when the metric was recorded                                                                |
| **span\_id**                          | Links to the specific span within the trace                                                                           |
| **client\_sample\_rate** *(optional)* | The client-side sample rate applied when the metric was captured                                                      |
| **custom attributes**                 | Any key-value pairs you add for grouping and filtering                                                                |

## [When to Use Application Metrics](https://docs.sentry.io/product/explore/metrics.md#when-to-use-application-metrics)

Application Metrics are best for **application and code-based health signals**, numeric indicators of whether your application logic is behaving as expected.

**Good candidates for Application Metrics:**

* Business KPIs tied to code execution
* Application health indicators
* Resource utilization tracking
* User action counts
* Success/failure rates

**Not ideal for Application Metrics:**

* Infrastructure metrics (CPU, memory, disk) - use APM tools
* Log aggregation - use [Logs](https://docs.sentry.io/product/explore/logs.md)
* Full request tracing - use [Traces](https://docs.sentry.io/product/explore/trace-explorer.md)

## [AI-Powered Metric Analysis](https://docs.sentry.io/product/explore/metrics.md#ai-powered-metric-analysis)

Your Sentry metrics can be leveraged with AI agents and tooling for debugging and automated analysis:

* **[Sentry MCP Server](https://docs.sentry.io/ai/mcp.md)**: Enables natural language queries and deep integration with AI tools like Claude, Cursor, and VS Code using the Model Context Protocol
* **[Seer](https://docs.sentry.io/product/ai-in-sentry/seer.md)**: Sentry's AI debugging agent can use metrics alongside traces, logs, and errors to provide intelligent issue analysis

## Pages in this section

- [Set Up](https://docs.sentry.io/product/explore/metrics/getting-started.md)