Data stream naming schemeedit
APM data follows the
<type>-<dataset>-<namespace> naming scheme.
dataset are predefined by the APM integration,
namespace is your opportunity to customize how different types of data are stored in Elasticsearch.
There is no recommendation for what to use as your namespace—it is intentionally flexible.
For example, you might create namespaces for each of your environments,
Or, you might create namespaces that correspond to strategic business units within your organization.
APM data streamsedit
By type, the APM data streams are:
Traces are comprised of spans and transactions. Traces are stored in the following data streams:
RUM and iOS agent application traces:
- Application traces:
Metrics include application-based metrics and basic system metrics. Metrics are stored in the following data streams:
APM internal metrics:
APM profiling metrics:
Application metrics include the instrumented service’s name—defined in each APM agent’s configuration—in the data stream name. Service names therefore must follow certain index naming rules.
Service name rules
Service names are case-insensitive and must be unique.
For example, you cannot have a service named
Fooand another named
Special characters will be removed from service names and replaced with underscores (
_). Special characters include:
'\\', '/', '*', '?', '"', '<', '>', '|', ' ', ',', '#', ':', '-'
- Service names are case-insensitive and must be unique. For example, you cannot have a service named
- APM internal metrics:
Logs include application error events and application logs. Logs are stored in the following data streams:
APM error/exception logging:
- APM error/exception logging:
- Data streams define not only how data is stored in Elasticsearch, but also how data is retained over time. See Index lifecycle management to learn how to create your own data retention policies.
- See Manage storage for information on APM storage and processing costs, processing and performance, and other index management features.