Output

What an output does

An output is the delivery target for telemetry streams. It tells a system where logs or other event data should go, what connection details to use, and how to transport the data. In practice, outputs separate destination choice from stream selection, so operators can predefine sinks while tenants choose which streams use them.

That separation matters because it turns delivery into a reusable control point rather than a one-off integration. The same telemetry platform can route different streams to different backends, support multiple transport patterns, and preserve operator control over destinations without forcing every tenant to hard-code endpoints.

Where outputs fit in telemetry pipelines

Outputs sit at the downstream edge of a telemetry pipeline, after data has been produced and often after it has been filtered, transformed, or enriched. The output is not the data source itself, it is the configured path to the sink that receives the data.

This makes outputs a practical abstraction for multi-tenant or multi-environment observability. A platform can expose a small set of approved destinations, while teams attach their own streams to the output that matches their retention, analytics, or operational needs.

What an output typically defines

An output usually includes the endpoint or backend address, transport settings, authentication or connection parameters where needed, and any delivery-specific options such as batching, retry behaviour, or protocol selection. The exact fields vary by product, but the underlying purpose is consistent: define how telemetry leaves the pipeline and where it lands.

Because outputs are configuration objects rather than policy by themselves, their security value depends on the surrounding controls. A carefully defined output can reduce drift, but it can also become a concentration point for misrouting, exposure, or unintended cross-environment delivery if it is too broadly shared.

Why outputs matter operationally

Outputs make telemetry architecture easier to govern at scale. They reduce duplication, support standardised destinations, and allow operators to manage sink configuration centrally instead of letting every producer point somewhere different. That improves consistency and makes it easier to change backends without rewriting every stream configuration.

They also introduce an important control boundary. A destination that is convenient for one stream may be inappropriate for another if it changes retention, access scope, residency, or downstream processing. Good output design therefore helps organisations balance flexibility with control over where telemetry is allowed to flow.

Related resources from NHI Mgmt Group

• When should organisations treat agent output integrations as part of access governance?
• What is the difference between AI access control and AI output control?
• What is the difference between retrieval authorization and output authorization?
• Who is accountable when AI output is influenced by tampered grounding data?