---
name: monitoring-about-timeseries
title: Time-series
description: You can collect metrics from a number of platforms, orchestrators, and a wide range of applications such as Prometheus, JMX, StatsD, Kubernetes, and other application stacks, that are available in the IBM Cloud®, outside the IBM Cloud, or on-prem. You can also add more metrics by creating custom metrics and adding integrations.
last-updated: 2023-03-27
---

> ## Documentation Index
> The table of contents for this documentation set is at https://cloud.ibm.com/docs/monitoring?format=markdown
> The index for all IBM Cloud docs is at: https://cloud.ibm.com/docs/llms.txt
> Use these files to discover more information as needed.

---

# Time-series
{: #about-timeseries}

You can collect metrics from a number of platforms, orchestrators, and a wide range of applications such as Prometheus, JMX, StatsD, Kubernetes, and other application stacks, that are available in the IBM Cloud®, outside the IBM Cloud, or on-prem. You can also add more metrics by creating custom metrics and adding integrations.
{: shortdesc}


A *time-series* is a series of data-points ordered by time.  It is a unique combination of a metric name and label key-value pairs.  For example: `website_failedRequest |region='Asia', customer_ID='abc'`.

The same metric name can produce multiple *time-series* when the metric and label values differ.

For example, the following are 4 unique time series:

```text
metric_name{datacenter=”dc-1”, zone=”zone1”} 23
metric_name{datacenter=”dc-2”, zone=”zone1”} 34
metric_name{datacenter=”dc-3”, zone=”zone2”} 43
metric_name{datacenter=”dc-4”, zone=”zone2”} 23
```
{: screen}

A *data-point* is the value generated for a *time-series* at a given point in time.  For example: `[timestamp]|website_failedRequests:20|region='Asia', customer_ID='abc'`.

For example, 3K unique time-series in 10 seconds is 18K data-points per minute.  Or, 3K unique time-series in a minute would be 3K data-points per minute.

You are billed based on the number of time series hours collected during a billing cycle.
{: note}

## Sources of time-series
{: #about-collect-timeseries-1}

For `TIME_SERIES_HOURS`, there are 4 sources of custom metrics:

* Custom metrics created by agents such as Prometheus, StatsD, JMX, and AppChecks.

   * Prometheus metrics are collected from Prometheus endpoints. By default any pod with `prometheus.io/scrape: true` is included.

   * StatsD metrics are collected automatically without setting up a collector.

   * JMX metrics can be collected by configuring the target and the JMX `MBeans` names.

   * AppChecks are small scripts run by the agent to collect metrics.

* IBM Cloud platform metrics. These are metrics generated by IBM Cloud services for your service instances. This also includes usage of the default IBM Cloud Monitoring dashboards available in the IBM Cloud Monitoring console under **Dashboard** > **Dashboard Templates** > **IBM**.

* Metrics sent using Prometheus remote write to IBM Cloud Monitoring through Prometheus servers.

* Metrics forwarded to external systems using Kafka or an Event Streams topic. The `sysdig_datastream_ts_usage` metric returns the number of time series exported using metric streaming.