Getting started with tags
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Getting started with tags


Tags are a way of adding dimensions to metrics, so they can be filtered, aggregated, and compared in Datadog visualizations. Using tags enables you to observe aggregate performance across a number of hosts and (optionally) narrow the set further based on specific elements. In summary, tagging is a method to observe aggregate data points.

Tagging binds different data types in Datadog, allowing for correlation and call to action between metrics, traces, and logs. This is accomplished with reserved tag keys. Here are some examples:

Tag KeyAllows for
hostCorrelation between metrics, traces, processes, and logs
deviceSegregation of metrics, traces, processes, and logs by device or disk
sourceSpan filtering and automated pipeline creation for log management
serviceCorrelation between metrics, traces, and logs

Why It Matters

Typically, it’s helpful to look at containers, VMs, and cloud infrastructure at the “service” level in aggregate. For example, it’s more helpful to look at CPU usage across a collection of hosts that represents a service, rather than CPU usage for server A or server B separately.

Containers and cloud environments regularly churn through hosts, so it is critical to tag these to allow for aggregation of the metrics you’re getting.

Defining Tags

Below are Datadog’s tagging restrictions, requirements, and suggestions:

  1. Tags must start with a letter and after that may contain the characters listed below:

    • Alphanumerics
    • Underscores
    • Minuses
    • Colons
    • Periods
    • Slashes

    Other special characters are converted to underscores.

    Note: A tag cannot end with a colon, for example tag:

  2. Tags can be up to 200 characters long and support Unicode.

  3. Tags are converted to lowercase. Therefore, CamelCase tags are not recommended. Authentication (crawler) based integrations convert camel case tags to underscores, for example TestTag –> test_tag.

  4. A tag can be in the format value or <KEY>:<VALUE>. For optimal functionality, we recommend constructing tags in the <KEY>:<VALUE> format. Commonly used tag keys are env, instance, and name. The key always precedes the first colon of the global tag definition, for example:

  5. Reserved tag keys host, device, source, and service cannot be used in the standard way.

  6. Tags shouldn’t originate from unbounded sources, such as EPOCH timestamps, user IDs, or request IDs. Doing so may infinitely increase the number of metrics for your organization and impact your billing.

Assigning Tags

Tags may be assigned using any (or all) of the following methods. Refer to the dedicated Assigning Tags documentation to learn more:

MethodAssign tags
Configuration FilesManually in your main Agent configuration files, or in your integrations configuration file.
Environment VariablesUsing environment variables for the containerized Agent
UIIn your Datadog platform
APIUsing Datadog’s API
DogStatsDWhen submitting metrics via DogStatsD
Integration InheritanceAutomatically with supported integrations after setup

Using Tags

After you have assigned tags at the host and integration level, start using them to filter and group your metrics, traces, and logs. Tags are used in the following areas of your Datadog platform. Refer to the dedicated Using Tags documentation to learn more:

AreaUse Tags to
EventsFilter the event stream
DashboardsFilter and group metrics on graphs
InfrastructureFilter and group on the host map, infrastructure list, live containers, and live processes views
MonitorsManage monitors, create monitors, or manage downtime
MetricsFilter and group with the metric explorer
IntegrationsOptionally limit metrics for AWS, Google Cloud, and Azure
APMFilter App Analytics or jump to other areas with the service map
NotebooksFilter and group metrics on graphs
LogsFilter logs search, analytics, patterns, live tail, and pipelines
DevelopersPull information or setup different areas in the UI with the API

Further Reading