Subscribers

This page explains how subscribers consume lifecycle events without changing runtime execution.

What Subscribers Are

Subscribers are consumers of the NeMo Relay event stream. They receive emitted lifecycle events and use them for observation, forwarding, export, or analysis. In the native Rust, Python, Node.js, and FFI bindings, event-producing calls enqueue subscriber delivery on a process-wide background dispatcher and return without waiting for subscriber callbacks or exporter work.

How Subscribers Relate to Events

Events describe what happened. Subscribers are the components that watch those events.

In this documentation, an event is emitted when the runtime submits it for subscriber dispatch. An event is delivered to a subscriber when its callback runs. An event is exported when an exporter completes the downstream work defined by its API. On native targets, these are separate milestones.

That separation matters:

The runtime can emit one ATOF event stream.
Native event calls stay non-blocking for subscriber work.
Many subscribers can consume the same stream.
Observability behavior stays separate from call execution.

Registration Levels

Middleware and subscribers can be registered at different levels depending on their lifetime and visibility.

Global Subscribers

Global subscribers remain active process-wide until they are removed.

Scope-Local Subscribers

Scope-local subscribers are owned by one active scope and disappear when that scope closes.

Deregistering a subscriber affects future emissions. Events that were already emitted carry a subscriber snapshot, so queued callbacks from that snapshot can still run after deregistration.

Plugin-Installed Subscribers

Plugins can install subscribers as reusable, configuration-driven runtime components.

What Subscribers Consume

Subscribers consume the ATOF event stream. They do not define the event model. They react to it.

This lets plain subscribers, exporters, and tracing adapters share one runtime source of truth.

ATOF Events and ATIF Trajectories

ATOF and ATIF describe different stages of the observability path:

Format	What It Represents	What Subscribers or Exporters Do With It
ATOF	The canonical raw scope, tool, LLM, middleware, and mark event stream	Subscribers receive these events directly. The ATOF JSONL exporter writes one raw event per line.
ATIF	A trajectory projection assembled from related ATOF events	The ATIF exporter maps model and tool activity into trajectory steps for analysis, replay, or evaluation.

Marks are point-in-time ATOF events, not ATIF trajectory steps, so ATIF steps are not a lossless event log. ATIF is designed primarily for evaluation and visualization. Its steps do not represent the complete parent-child graph needed for perfect session replay. This limitation comes from the ATIF data model, not from converting ATOF events. Plugin-managed ATIF files preserve nested scope lineage and the raw events associated with the trajectory under extra.observed_events, including observed marks, for analysis and debugging. Those fields do not change the ATIF step model or make steps a complete replay log. Refer to Agent Trajectory Interchange Format (ATIF) for the complete projection and file contract.

Common Subscriber Roles

Subscribers are commonly used for in-process observation, counters, debugging, and exporter handoff.

In-Process Observation

Some subscribers stay inside the process and power custom logging, analytics, or debugging logic.

Host Integration Event JSON

For host integrations that need a serialized event payload, use the event object’s JSON serialization helpers instead of reconstructing payloads from native attributes. Python subscribers can call event.to_dict() or event.to_json() from the callback, while continuing to use the normal subscriber registration API.

This pattern is useful when an agent runtime, framework adapter, or plugin host already has its own lifecycle hooks but wants NeMo Relay to be the shared ATOF event representation. The host integration maps those hooks into NeMo Relay scopes, LLM calls, tool calls, or marks. NeMo Relay emits the ATOF event stream, and each subscriber chooses whether to consume the native event object, serialized event JSON, or an exporter-specific translation.

Subscribers do not define the event schema. They receive the runtime event and can serialize it through a binding helper when they need JSON. Exporter subscribers, such as the ATOF JSONL exporter, consume the same event stream and serialize it for their target backend.

Native subscribers are invoked by one process-wide worker thread in FIFO event order and subscriber snapshot order.

Subscriber callbacks are not re-entrant. Do not invoke a NeMo Relay API that runs middleware, flushes subscriber delivery, waits on an exporter, or clears plugins from a subscriber callback. Scope APIs remain supported: callbacks may create, push, or pop scopes at any nesting level and may replace the active scope stack with an arbitrary stack. Emitting a new event is the only supported operation that can enqueue additional callback work; Relay queues that event behind the active publication instead of recursively delivering it.

Waiting for Delivery

An event-producing call returning is not a delivery barrier. These guarantees apply when you call a barrier outside a native subscriber callback. Use the following milestones to choose the barrier that matches the output you need to observe:

Milestone	What It Establishes	What It Does Not Establish
Event-producing call returns	The runtime call completed. On native targets, the runtime normally queues subscriber work for background dispatch.	Subscriber callbacks ran, exporter work completed, or output is visible or durable.
Subscriber flush returns	All native subscriber callbacks queued before the flush call have completed.	Exporter-owned workers drained or a remote backend accepted the data.
Exporter barrier returns	The runtime drained the shared subscriber queue, and the exporter completed its documented `force_flush()`, `export()`, or equivalent operation. For a worker-backed exporter, that operation can stop after its configured timeout.	Exactly-once delivery, machine-crash durability, confirmed completion by a worker that timed out, or success beyond the exporter’s documented error and timeout behavior.
Plugin clear or exporter shutdown returns	NeMo Relay completed the component’s documented graceful teardown steps, or reported an error.	Retention if the process terminates before teardown completes or completion by a worker that timed out during teardown.
Process terminates before a barrier	You can observe only callback side effects and exporter work that completed before termination.	Retention of queued subscriber callbacks or pending exporter work.

Use the subscriber flush API when application shutdown, tests, or examples must observe side effects from callbacks that were already queued before the barrier:

Rust: nemo_relay::api::subscriber::flush_subscribers()?
Python: nemo_relay.subscribers.flush() from synchronous code, or await nemo_relay.subscribers.flush_async() from an asyncio task
Node.js: await flushSubscribers(), then await an event-loop tick for JavaScript callback side effects
FFI: nemo_relay_flush_subscribers()

Events emitted concurrently after the flush barrier are not covered by that call. Exporters with their own workers or batch processors require the exporter-specific flush, export, or shutdown operation described in Observability.

Do not invoke a subscriber flush, an exporter barrier, or plugin clear from a subscriber, event-sanitizer, conditional-guardrail, request-intercept, or execution-intercept callback. These operations are not supported there and do not establish a valid delivery barrier; depending on the binding or exporter, they can also create a wait cycle. Run them after the callback returns.

Queued tool and LLM observability sanitizers are a narrow exception: Python and Node.js permit a subscriber flush call there, but it returns without waiting for the sanitizer’s own publication.

If the process terminates before subscriber delivery and exporter teardown complete, queued telemetry can be lost. Returning from the event-producing API does not make that telemetry crash-safe.

Forwarding and Export

Some subscribers translate the event stream into external formats or transport it to another system.

Analytics and Diagnostics

Some subscribers derive measurements, trajectories, or diagnostics from the event stream without affecting execution behavior.

Built-In Subscriber Examples

These examples show how built-in subscriber patterns relate to custom subscribers and exporters.

Custom Subscribers

A plain custom subscriber is the right choice when you want in-process handling of the canonical event stream.

Agent Trajectory Interchange Format (ATIF) Exporter

The Agent Trajectory Interchange Format (ATIF) exporter collects lifecycle events and emits trajectory artifacts for offline analysis, replay, or debugging.

Agent Trajectory Observability Format (ATOF) JSONL Exporter

The Agent Trajectory Observability Format (ATOF) JSONL exporter writes the canonical event stream to a native filesystem path as one raw ATOF event per line.

OpenTelemetry Subscriber

The OpenTelemetry subscriber maps runtime events into OTLP traces for tracing backends. Each subscriber uses one full, gen_ai, or openinference projection. Select openinference for model-centric OpenInference semantics; there is no separate OpenInference subscriber.

Detailed setup, configuration, and API behavior for this subscriber belongs in Observability. For configuration-driven setup, use the built-in observability plugin to install ATOF, ATIF, and typed OpenTelemetry exporters from one plugin component.

Practical Guidance

Use these practices when applying the concept in application or integration code.

Use a plain subscriber when you want in-process custom behavior.
Flush subscribers before inspecting printed output, captured lists, or other custom callback side effects.
Use the exporter’s documented barrier before inspecting exporter output.
Clear plugin-managed exporters during graceful shutdown.
Use event.to_dict() or event.to_json() when a host runtime or exporter needs the ATOF event as JSON in process.
Use a scope-local subscriber when the observation should disappear with the owning scope.
Use a plugin-installed subscriber when the behavior should be reusable and config-driven.
Use an exporter-oriented subscriber when the event stream should leave the process.