Grok Build Observability with OpenTelemetry
Learn how to implement end to end observability and monitoring for Grok Build, xAI's terminal coding agent, using OpenTelemetry and SigNoz.
In this video, we walk through turning on Grok Build's native OpenTelemetry exporter, collecting metrics and structured session events, and visualizing everything in SigNoz to gain real time visibility into token usage, sessions and turns, tool calls and their outcomes, error categories, and startup latency. Grok Build ships its own exporter, so instrumenting it is a matter of configuration, with no library to install and no collector to run.
Whether you're rolling coding agents out across a team, tracking AI spend by model, debugging failing agent turns, or running Grok Build as part of your daily development workflow, observability is essential for understanding how your agent behaves in real world environments. You'll learn how to move beyond basic logging and adopt production grade observability practices that help you debug faster, optimize performance, reduce costs, and confidently operate Grok Build at scale.
We also cover the prebuilt Grok Build Dashboard in SigNoz, which provides out of the box visibility into token usage by type and by model, session and turn volume, tool effectiveness, error categories, startup latency by phase, and overall agent health.
What You'll Learn:
How to monitor Grok Build with OpenTelemetry
How to track input, output, cache read, and reasoning tokens by model
How to measure tool activity, turn outcomes, and error categories
How to visualize Grok Build telemetry in SigNoz
Useful Resources:
Grok Build Observability Documentation
https://signoz.io/docs/grok-build-observability/
Grok Build Dashboard Documentation
https://signoz.io/docs/dashboards/dashboard-templates/grok-build-dashboard/
SigNoz LLM Observability Documentation
https://signoz.io/docs/llm-observability/
More About SigNoz:
SigNoz is an open source observability platform built on OpenTelemetry. It helps developers monitor applications, troubleshoot production issues, and gain visibility across metrics, logs, and traces from a single platform.
SigNoz can be used to monitor AI applications, coding agents, AI assistants, LLM workloads, microservices, Kubernetes environments, and distributed systems.
SigNoz Website
https://signoz.io
GitHub Repository
https://github.com/SigNoz/signoz
Join our Slack Community
https://signoz.io/slack
If you have questions, feedback, or documentation requests, feel free to open a GitHub issue or join our Slack community.
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