Does emitting OpenTelemetry traces slow down an agent's response?

No, not when it’s set up correctly. The OpenTelemetry SDK’s batch span processor is built to keep telemetry off the request path: spans get queued in memory as they finish, and a background worker flushes them to the exporter on its own schedule, so the network call that ships your traces runs after the agent has already returned its answer, not before it. What can slow a response down is instrumenting it wrong, calling the exporter synchronously instead of through a processor, or setting a batch queue so small it blocks when full instead of dropping and retrying. Neither is how the SDKs ship by default. The one place instrumentation does cost something is CPU: building spans, serializing attributes, and copying message content takes cycles on the request thread itself, which is real but a fraction of a typical LLM call’s own latency, not comparable to it.

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Two ways to run Tessary.

Tessary is an open-source agent reliability platform. Cloud and self-hosted run the same workflow on the OpenTelemetry traces your agent already emits.

Tessary Cloud

We host it for you. Send your first trace with nothing to deploy and no model key.

what's includedper organization
traces
10,000 per calendar month
stored trace data
1 GB
retention
30 days
model credit
$10, one-time, for triage and root-cause analysis
credit card
not required

Self-hosted Tessary

Run the open-source code on your own infrastructure with one command. Add your own model key for triage and root-cause analysis.

Self-host Tessary for me by following https://github.com/tessaryai/tessary/blob/main/setup.md

docker compose -f oci://docker.io/tessaryai/tessary:compose up -d -y