For Platform Engineers

Your agents fail in ways
your logs will never show you.

Retries, silent tool errors, latency stacked across steps. ObserveAgents takes the OpenTelemetry traces you already emit and turns every agent session into an execution waterfall — no proprietary SDK, no re-instrumentation.

Try our Demo → Watch the product tour
OTel-native · GenAI semantic conventions · Prompts & responses never stored
The platform problem

Agent behavior is a distributed trace.
You're debugging it with print statements.

An agent request fans out across models, tools, MCP servers, and databases. When it's slow or wrong, the story is spread over five systems and none of them agree. Reproducing it locally is a fantasy.

You have three bad options:
01

Log-diving

Grep five services and stitch timestamps by hand — for every flaky agent run, again and again.

02

A dashboard per team

Every squad builds its own partial view in its own tool. Nobody sees a whole session end-to-end.

03

Build it yourself

A custom trace pipeline plus a UI plus alerting — a quarter of platform work before the first insight.

What ObserveAgents gives platform

Your OTel stack is the only integration.

Point an OTLP exporter at ObserveAgents. Sessions, waterfalls, inventory, and alerts appear — no manual registration, no tagging.

Ingest

OTel-native, SDK-free

Works with the OpenTelemetry SDKs and collectors you already run, speaking the GenAI semantic conventions.

Runtime

Execution waterfalls

Traces grouped one row per agent session, expandable into per-step timing — where every request actually spent its time.

Quality

Telemetry quality scoring

See which services classify fully, which signals are missing, and which custom attributes deserve a mapping.

Dependencies

Runtime dependency map

Every MCP server, tool, API, and database your agents touch at runtime — discovered, not declared.

Alerts

Threshold rules, delivered

Built-in detection rules over runtime behavior — repeated tool errors, MCP thresholds — delivered to your webhook.

How it works

Three jobs it does for platform

Ingest. Correlate. Alert. On the pipeline you already own.

otel
01 · Ingest

Point your exporter, done

POST /otel/v1/traces from your existing stack. Agents and their sessions appear without registration.

02 · Correlate

Sessions become waterfalls

One row per agent session, expandable to per-step timing, tool calls, token usage, and errors.

repeated_tool_errors → webhook delivered
03 · Alert

Rules over behavior

Threshold rules evaluate during intelligence runs — never inside ingestion — and reach you by webhook.

Debug your first agent session in minutes.

Open the live demo: runtime timelines, execution waterfalls, telemetry quality, and the dependency map — on realistic synthetic data.

Try our Demo →
The ObserveAgents console