Include data in segments

• Latest Dynatrace
• Concept
• 5-min read
• Updated on Jun 23, 2025

Segments can logically structure and serve as convenient filters when analyzing data in different apps. Segments are constructed based on rules, called Includes. Learn how data of different types can be included in segments.

Key terms

Include

Single rule, referencing data to be included in segment. Querying for data not explicitly referenced by any include of the selected segment, will lead to empty results.

Signal

Observed data point, emmitted by a monitored entity. Available signal types in Dynatrace are logs, metrics, events, spans, and others.

Monitored entity

Logical component monitored by Dynatrace, persisted as Smartscape node and/or classic entity.

Smartscape node

Node topology objects, similar to entities on the Dynatrace cluster. Nodes are a collection of all kinds of entities, regardless of their type.

Classic entity

Application, service, process, host, or data center entity stored on the Dynatrace cluster (such as dt.entity.host, dt.entity.service, dt.entity.kubernetes_cluster). Classic entities are bound to a type.

Includes

Segments are constructed incrementally through includes, step by step, extending the scope of the segment. Includes reference a certain data type and are defined by a filter condition for data of that type.

In its initial state, logically speaking, a segment can be considered empty. To use a segment for filtering, data needs to be included.

In the following example, two include blocks were added to include logs and metrics by the given conditions. This illustrates how includes incrementally extend the scope of a segment.

Logical conditions within a single include can of course be more complex than simple equals-matches conditions as shown above.

Data types

Signals

Collecting observability signals is at the core of Dynatrace, so you need to understand their schema and build segments around how those signals are shaped.

Configurations like the one above can also be expressed more elegantly using the All data types option:

Since context matters, and Dynatrace's unique monitored entity model provides an alternative way to work with observability signals, there is a second option to include signals through entity-to-signal relationships.

Entity-to-entity relationships

A further benefit of segments in regards to monitored entities is being able to leverage relationships between them.

While working with entities stored as Smartscape nodes in Grail has multiple benefits, it's sometimes necessary to construct segments for classic entities. For instance, this enables having segments that include Kubernetes workloads or other monitored entities of higher cardinality, filtered by their related Kubernetes clusters.