Per-request `_force_flush_otel()` in ADK template blocks streaming responses

Start in vertexai/agent_engines/templates/adk.py, inspecting streaming_agent_run_with_events, async_stream_query, and _force_flush_otel, then reproduce a streaming query with telemetry enabled and disabled. Done means response delivery no longer waits on a per-request telemetry flush while telemetry continues to export asynchronously and shutdown data-loss handling remains addressed.

Environment

• google-cloud-aiplatform (vertexai SDK)
• vertexai/agent_engines/templates/adk.py
• Agent Runtime with identity_type=AGENT_IDENTITY
• ADK >= 1.17.0

Description

Problem

The ADK template's streaming_agent_run_with_events and async_stream_query methods call _force_flush_otel() in their finally blocks on every request. This triggers a synchronous BatchSpanProcessor.force_flush() that blocks the response stream until all queued spans are exported to telemetry.googleapis.com.

In Agent Identity environments where the export uses certificate-bound tokens (mTLS via SPIFFE/WIF), the authentication overhead is significantly higher than standard OAuth, and the blocking duration becomes noticeable to end users. Setting GOOGLE_CLOUD_AGENT_ENGINE_ENABLE_TELEMETRY=false eliminates the overhead, confirming the flush is the sole cause.

Root Cause

_force_flush_otel() in adk.py calls tracer_provider.force_flush() via asyncio.to_thread(), which invokes BatchSpanProcessor._export(BatchExportStrategy.EXPORT_ALL) — a blocking synchronous export. The default OTEL_BSP_EXPORT_TIMEOUT is 30,000ms, so the flush can block for up to 30 seconds depending on the mTLS authentication latency.

The comment on the call site reads:

# Avoid telemetry data loss having to do with CPU throttling on instance turndown

This concern is valid, but per-request flush is the wrong mechanism for it. BatchSpanProcessor already exports asynchronously at a configurable interval (default 5s). Telemetry data loss on shutdown should be handled by a shutdown hook, not by blocking every request.

Reproduction

1. Deploy an ADK agent to Agent Runtime with identity_type=AGENT_IDENTITY
2. Ensure telemetry is enabled (GOOGLE_CLOUD_AGENT_ENGINE_ENABLE_TELEMETRY=true, or leave at default for ADK >= 1.17)
3. Send a streaming query
4. Observe a significant gap between agent execution completion and response delivery
5. Set GOOGLE_CLOUD_AGENT_ENGINE_ENABLE_TELEMETRY=false and repeat — the gap disappears

Expected Behavior

The OTel flush should not block the request path. BatchSpanProcessor is designed to export spans asynchronously in background threads. Per-request force_flush() negates this design and introduces user-facing latency proportional to the telemetry export duration.

When running the same agent on Cloud Run with ADK Runner.run_async() directly (bypassing the ADK template wrapper), no such overhead exists — the agent execution time is the same, but the framework-level gap is negligible.

Code References

Call sites (per-request flush in finally blocks):

• streaming_agent_run_with_events
• async_stream_query

Flush implementation:

• _force_flush_otel

Workaround

Set GOOGLE_CLOUD_AGENT_ENGINE_ENABLE_TELEMETRY=false in the Agent Runtime deployment's env_vars. This disables Cloud Trace export but does not affect BigQuery Agent Analytics Plugin (which uses its own data path).