---
title: "Metrics pricing | Grafana Cloud documentation"
description: "Learn how Grafana Cloud Metrics bills for active series and data points per minute, and how 95th percentile billing works."
---

> For a curated documentation index, see [llms.txt](/llms.txt). For the complete documentation index, see [llms-full.txt](/llms-full.txt).

# Metrics pricing

Grafana Cloud Metrics bills on two components: *active series* and *data points per minute* (DPM). Understanding both makes it much easier to predict and control what you spend.

For current rates, refer to the [pricing page](/pricing/#metrics).

Your metrics usage is determined by the number of active series you send and how frequently you send data points for them. Both are measured at the [95th percentile](#95th-percentile-billing) over the billing period.

If your average DPM per active series is greater than the included DPM, your usage is based on total DPM instead of active series. In other words, you’re billed on whichever is higher.

This applies to both hosted Prometheus and hosted Graphite.

## Definitions

### Active series

An active series is a time series that has received new data points within the previous 20 minutes. Shortly after you stop writing new data points to a series, it’s no longer active.

> Note
> 
> The definition of active series is different for Prometheus native histograms. Refer to [Prometheus native histograms](#prometheus-native-histograms).

To view active series data, query the `grafanacloud_instance_active_series` metric in the **grafanacloud-usage** data source.

### Data points per minute (DPM)

A data point is a single measured occurrence, or **sample**, of a metric within a time series, consisting of a unique value and timestamp. DPM is the number of data points sent to Grafana Cloud Metrics per minute per series, calculated per stack.

Grafana Cloud measures DPM directly from the data sent to its servers. You can also calculate it by multiplying the number of active series by the number of data points per series per minute.

To calculate data points per series per minute, divide the number of seconds in a minute by your scrape interval:

- A scrape interval of 15 seconds produces 4 data points per series per minute. This is the Prometheus default.
- A scrape interval of 60 seconds produces 1 data point per series per minute. This is the default for Grafana Cloud integrations.

To view DPM, query the `grafanacloud_instance_samples_per_second` metric in the **grafanacloud-usage** data source, then multiply by 60 to convert to minutes (`* 60`).

### Included DPM per series

Grafana Cloud Pro accounts include a default resolution of 1 DPM per active series. You can shorten your scrape interval to ship data points more frequently and increase your DPM, for an additional charge. [Contracted plans](/pricing/) let you choose between the default 1 DPM resolution and a 4 DPM resolution for higher resolution use cases.

To view included DPM per series, query the `grafanacloud_org_metrics_included_dpm_per_series` metric in the **grafanacloud-usage** data source.

### Prometheus time series

A Prometheus time series is a list of timestamp and value pairs, or samples, identified by a metric name and zero or more pairs of label names and label values.

For example, consider the following output from a Prometheus metrics exporter:

Bash ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy

```bash
node_cpu_seconds_total{host="host1",cpu="0",mode="user"}
node_cpu_seconds_total{host="host1",cpu="1",mode="user"}
```

This output contains two time series:

- The **metric name** is `node_cpu_seconds_total`.
- The **label names** are `host`, `cpu`, and `mode`.
- The **label values** are `host1`, `0` or `1`, and `user`.

There are two time series because the `cpu` label value differs, even though `host` and `mode` are the same. When you scrape a target and it generates a sample, the sample has a specific timestamp and measured value. Scraping the same target again, for example one minute later, creates a second data point in the same series with a new timestamp and value.

Metrics usage increases quickly when a metric has many different combinations of labels. This is called *high cardinality*, and it’s best to [avoid spikes in cardinality](/blog/2022/02/15/what-are-cardinality-spikes-and-why-do-they-matter/). For example, with 6 CPU modes, 10 hosts, and 4 CPUs, `node_cpu_seconds_total` counts as `6*10*4`, or 240 active series. At a 15 second scrape interval, this produces a DPM per series of 4, or a total DPM of `4*240=960` data points.

For a detailed explanation, refer to the [Prometheus data model](https://prometheus.io/docs/concepts/data_model/) in the Prometheus documentation.

### Graphite time series

For Graphite, unique time series are equivalent to metric paths. For example, the following Graphite output contains eight unique time series:

![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy

```none
collect.host1.cpu-0.cpu-idle
collect.host1.cpu-0.cpu-user
collect.host1.cpu-0.cpu-wait
collect.host1.cpu-0.cpu-system
collect.host2.cpu-3.cpu-idle
collect.host2.cpu-3.cpu-user
collect.host2.cpu-3.cpu-wait
collect.host2.cpu-3.cpu-system
```

If you use Graphite tags, the following output also contains eight unique time series:

Bash ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy

```bash
collect.cpu;host=host1;cpu=0;mode=idle
collect.cpu;host=host1;cpu=0;mode=user
collect.cpu;host=host1;cpu=0;mode=wait
collect.cpu;host=host1;cpu=0;mode=system
collect.cpu;host=host2;cpu=3;mode=idle
collect.cpu;host=host2;cpu=3;mode=user
collect.cpu;host=host2;cpu=3;mode=wait
collect.cpu;host=host2;cpu=3;mode=system
```

For more information, refer to [Graphite tags](https://graphite.readthedocs.io/en/latest/tags.html).

## How usage is calculated

The following examples show how usage scales with scrape interval for a Grafana Cloud Pro account:

- **Scenario A**: 50,000 active series at a 60-second scrape interval (1 DPM), resulting in 50,000 total DPM:
  
  Bash ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy
  
  ```bash
  usage = max(50000 active_series, 50000 total_dpm / 1 included_dpm) = 50000
  ```
- **Scenario B**: 50,000 active series at a 30-second scrape interval (2 DPM), resulting in 100,000 total DPM:
  
  Bash ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy
  
  ```bash
  usage = max(50000 active_series, 100000 total_dpm / 1 included_dpm) = 100000
  ```

Halving the scrape interval doubles the billable usage for the same number of series.

### Usage calculations

The following shows the calculations in pseudo-PromQL.

**Active series**:

promql ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy

```promql
active_series = quantile_over_time(0.95, sum by (id)(grafanacloud_instance_active_series < Inf)[30d:])
```

**DPM**:

promql ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy

```promql
total_dpm = quantile_over_time(0.95, sum by (id)(grafanacloud_instance_samples_per_second < Inf)[30d:]) * 60
```

**Total usage**:

promql ![Copy code to clipboard](/media/images/icons/icon-copy-small-2.svg) Copy

```promql
usage = max(active_series, total_dpm/included_dpm)
```

### 95th percentile billing

For each billing period, Grafana Cloud bills you on the 95th percentile of the active series and total DPM it tracks. This prevents you from being billed for unexpected or temporary spikes, such as when you first configure Prometheus or Grafana Alloy.

Grafana Cloud forgives the top five percent of usage time in each monthly billing period, roughly the top 36 hours in a 720 hour month (`0.05 * 720 = 36`).

For example, if you normally send around 6,000 active series but spike to 30,000 for a total of 24 hours in a month, you’re still billed at the rate of 6,000 active series.

> Note
> 
> Usage in the Cost Management and Billing dashboards is a cumulative month-to-date value refreshed hourly, not a per-day total. If you calculate daily usage from it, for example with `delta()` or `increase()`, some values can be negative. This is expected, as more data accumulates during the month, the 95th percentile recalculates and the prorated included usage changes, so the month-to-date value can drop. Use the gauge value directly and treat daily differences as approximations.

## Special considerations

### Prometheus native histograms

Prometheus native histograms are a data type that lets you produce, store, and query high resolution histograms.

Pricing for time series with native histograms depends on the number of buckets used to represent your data distribution. Unlike classic histograms, which use a predefined number of buckets, native histograms provision the number of buckets automatically. The number of active buckets counts toward a billable series at a ratio of 0.25 instead of counting the active series itself. For the same cost, you can use four times as many buckets for native histograms as for classic histograms.

To assess and limit the number of buckets, refer to [Analyze the cardinality of native histograms](/docs/grafana-cloud/platform/cost-management-and-billing/analyze-costs/metrics-costs/prometheus-metrics-costs/native-histograms-cardinality-api/).

### OpenTelemetry

Series ingested through the OpenTelemetry Protocol ([OTLP](https://opentelemetry.io/docs/specs/otel/protocol/)) cost no more than any other series. Standard active series pricing applies.

To track OTLP adoption, query the `grafanacloud_instance_active_otlp_series` metric in the **grafanacloud-usage** data source.

### Volume discounts

As your usage grows, your effective rate decreases automatically. Refer to [Volume discounts](/docs/grafana-cloud/platform/pricing-and-usage/volume-discounts/).

## View your usage

1. In your Grafana Cloud stack, go to **Cost Management and Billing &gt; Usage**.
2. Under **Product Breakdown**, select **Metrics**.

For a deeper breakdown, refer to [Understand Metrics usage and cost](/docs/grafana-cloud/platform/cost-management-and-billing/understand-usage-cost/metrics/).

## Related

- [Metrics pricing page](/pricing/#metrics)
- [Analyze Metrics costs](/docs/grafana-cloud/platform/cost-management-and-billing/analyze-costs/metrics-costs/)
- [Adjust your data points per minute](/docs/grafana-cloud/platform/cost-management-and-billing/analyze-costs/reduce-costs/metrics-costs/adjust-data-points-per-minute/)
- [Usage limits](/docs/grafana-cloud/platform/pricing-and-usage/usage-limits/)