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Metric monitors are useful for a continuous stream of data. Any metric sent to Datadog can be alerted upon if they cross a threshold over a given period of time.
To create a metric monitor in Datadog, use the main navigation: Monitors –> New Monitor –> Metric.
A threshold alert compares metric values to a static threshold.
On each alert evaluation, Datadog calculates the average, minimum, maximum, or sum over the selected period and checks if it is above or below the threshold. This is for standard alert cases where you know the expected values. The distribution metric type offers the additional threshold option of calculating percentiles over the selected period.
A change alert compares the absolute or relative (%) change in value between N minutes ago and now against a given threshold. The compared data points aren’t single points but are computed using the parameters in the define the metric section.
On each alert evaluation, Datadog calculates the raw difference (a positive or negative value) between the series now and N minutes ago, then computes the average/minimum/maximum/sum over the selected period. An alert is triggered when this computed series crosses the threshold.
This type of alert is useful to track spikes, drops, or slow changes in a metric when there is not an unexpected threshold.
An anomaly detection alert uses past behavior to detect when a metric is behaving abnormally.
Anomaly alerts calculate an expected range of values for a series based on the past. Some of the anomaly algorithms use the time-of-day and day-of-week to determine the expected range, thus capturing abnormalities that could not be detected by a simple threshold alert. For example, the series is unusually high for 5AM even though it would be considered normal at 10 AM.
On each alert evaluation, Datadog calculates the percentage of the series that falls above, below, and outside of the expected range. An alert is triggered when this percentage crosses the configured threshold.
For more detailed information, see the Anomaly Monitor page.
Outlier monitors detect when a member of a group (hosts, availability zones, partitions, etc.) is behaving unusually compared to the rest.
On each alert evaluation, Datadog checks whether or not all groups are clustered together and exhibiting the same behavior. An alert is triggered when one or more groups diverges from the rest of the groups.
For more detailed information, see the Outlier Monitor page.
A forecast alert predicts the future behavior of a metric and compares it to a static threshold. It is well-suited for metrics with strong trends or recurring patterns.
On each alert evaluation, a forecast alert predicts the future values of the metric along with the expected deviation bounds. An alert is triggered when any part of the bounds crosses the configured threshold.
For more detailed information, see the Forecast Monitor page.
Any metric reporting to Datadog is available for monitors. Use the editor and the steps below to define the metric. The query parameters vary slightly based on the chosen detection method.
| Step | Required | Default | Example |
|---|---|---|---|
| Select a metric | Yes | None | system.cpu.user |
Define the from | No | Everywhere | env:prod |
| Specify metric aggregation | Yes | avg by | sum by |
| Group by | No | Everything | host |
| Set the alert grouping | No | Simple Alert | Multi Alert |
| Specify monitor query aggregation | No | average | sum |
| Evaluation window | No | 5 minutes | 1 day |
Definitions
| Option | Description |
|---|---|
| average | The series is averaged to produce a single value that is checked against the threshold. It adds the avg() function to your monitor query. |
| max | If any single value in the generated series crosses the threshold, then an alert is triggered. It adds the max() function to your monitor query. |
| min | If all points in the evaluation window for your query cross the threshold, then an alert is triggered. It adds the min() function to your monitor query. |
| sum | If the summation of every point in the series crosses the threshold, an alert is triggered. It adds the sum() function to your monitor query. |
| percentile(pXX) | If pXX percentage of points in the evaluation window for your query cross the threshold, then an alert is triggered. This option adds a percentile function to your monitor query. Only available for the distribution metric type. |
| Alert grouping | If using a Simple Alert, the monitor aggregates over all reporting sources. If using a Multi Alert, the monitor applies the alert to each source, according to your group parameters. See Alert grouping for more details. |
| Evaluation window | The time period the monitor evaluates. Use preset time windows like 5 minutes, 15 minutes, 1 hour, or custom to set a value between 1 minute and 730 hours (1 month). |
| Step | Required | Default | Example |
|---|---|---|---|
| Select a metric | Yes | None | system.cpu.user |
Define the from | No | Everywhere | env:prod |
| Specify metric aggregation | No | avg by | sum by |
| Group by | No | Everything | host |
| Specify monitor query aggregation | No | average | sum |
| Select a change type | No | change | % change |
| Evaluation window | No | 5 minutes | 1 day |
| Comparison window | No | 5 minutes | 1 month |
Definitions
| Option | Description |
|---|---|
| change | The absolute change of the value. |
| % change | The percentage change of the value compared to its previous value. For example, the percentage change for a previous value of 2 with a current value of 4 is 100%. |
| average | The series is averaged to produce a single value that is checked against the threshold. It adds the avg() function to your monitor query. |
| max | If any single value in the generated series crosses the threshold, then an alert is triggered. It adds the max() function to your monitor query. |
| min | If all points in the evaluation window for your query cross the threshold, then an alert is triggered. It adds the min() function to your monitor query. |
| sum | If the summation of every point in the series crosses the threshold, an alert is triggered. It adds the sum() function to your monitor query. |
| percentile(pXX) | If pXX percentage of points in the evaluation window for your query cross the threshold, then an alert is triggered. This option adds a percentile function to your monitor query. Only available for the distribution metric type. |
| Alert grouping | If using a Simple Alert, the monitor aggregates over all reporting sources. If using a Multi Alert, the monitor applies the alert to each source, according to your group parameters. See Alert grouping for more details. |
| Evaluation window | The time period the monitor evaluates. Use preset time windows like 5 minutes, 15 minutes, 1 hour, or custom to set a value between 1 minute and 730 hours (1 month). |
Notes:
Advanced... option, see Advanced graphing.as_count(). See as_count() in Monitor Evaluations for details.Trigger when the metric is above, above or equal to, below, or below or equal to. If the value is between zero and one, a leading zero is required. For example, 0.3.
Require or Do not require a full window of data for evaluation.
This setting allows you to change when the alerting engine considers a monitor as a candidate for evaluation.
Do not require (Default): A monitor is evaluated as soon as it is recognized. Consider using this value if your data points might be sparse. With this configuration, the monitor evaluates even if there is a single data point in the evaluation timeframe.
Require: A monitor is not evaluated until the evaluation window is considered to be filled with data. To be notified if there is data over the entire evaluation timeframe, use this option.
To define if the evaluation timeframe is filled with data, the timeframe is split into smaller buckets.
The following logic determines the bucket size:
In order to be considered as a “full window”, the monitor requires:
If the conditions are met, the monitor is evaluated. Otherwise, the evaluation is canceled and the monitor state is unchanged.
For example, a monitor that evaluates over the last 2h is split in 12 buckets of 10 minutes. The monitor is considered full if the first bucket has data and at most three buckets in total are empty.
| data | B0 | B1 | B2 | B3 | B4 | B5 | B6 | B7 | B8 | B9 | B10 | B11 | Full window? |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| case 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | Yes |
| case 2 | x | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | No |
| case 3 | 1 | 1 | x | x | x | 1 | 1 | 1 | 1 | 1 | 1 | 1 | Yes |
| case 4 | 1 | x | x | x | 1 | 1 | 1 | 1 | x | x | 1 | 1 | No |
For more information on the Evaluation Window, see the Monitor configuration page.
For detailed instructions on the advanced alert options (no data, auto resolve, etc.), see the Monitor configuration page.
For detailed instructions on the Say what’s happening and Notify your team sections, see the Notifications and Monitor configuration pages.
Alerts are grouped automatically based on your selection of the group by step when defining your metric. If no group is specified, grouping defaults to Simple Alert. If groups are selected, grouping defaults to Multi Alert.
Simple alerts aggregate over all reporting sources. You receive one alert when the aggregated value meets the set conditions. This works best to monitor a metric from a single host or the sum of a metric across many hosts.
Multi alerts apply the alert to each source according to your group parameters. You receive an alert for each group that meets the set conditions. For example, you could group system.disk.in_use by host and device to receive a separate alert for each host device that is running out of space.
Note that if your metric is only reporting by host with no device tag, it would not be detected by a monitor group by both host and device. Tag Variables are available for every group evaluated in the multi alert to dynamically fill in notifications with useful context.
