OpsCanary
observabilitygrafanaPractitioner

Building a Trust Platform for Your Agent with Grafana Observability

5 min read Grafana BlogReviewed for accuracy
Share
PractitionerHands-on experience recommended

In today's landscape, ensuring the reliability and effectiveness of your agents is critical. Grafana Agent Observability addresses the challenges of monitoring these agents, allowing you to build a trust platform that evaluates their performance effectively. This tool is now generally available to Grafana Cloud users, making it easier than ever to gain visibility into agent interactions.

Setting up Grafana Agent Observability is straightforward. You can write a configuration that integrates seamlessly with your agent frameworks using the Grafana Agent Observability SDK. This SDK comes equipped with coding skills specifically designed for instrumentation. Additionally, gcx, Grafana's new CLI, provides skills to assist in setting up these phases. To evaluate your agent's performance, you can utilize the agento11y SDK, which pulls the test suite, invokes the agent, records scores, and compiles a performance report. You can also leverage evaluator templates available out of the box, such as PII identification and Toxicity, to kickstart your evaluation process.

However, be cautious with LLM-judge evaluators like Helpfulness. While they offer more insights than traditional engineering metrics, they can be unreliable. It's essential to balance these qualitative evaluations with quantitative data to ensure a comprehensive understanding of your agent's performance.

Key takeaways

  • Utilize the agento11y SDK to pull test suites and record agent performance scores.
  • Leverage evaluator templates for quick starts in performance evaluation.
  • Implement gcx CLI for streamlined setup of agent observability phases.
  • Be cautious with LLM-judge evaluators due to potential unreliability.

Why it matters

In production, having a reliable trust platform for your agents can significantly enhance their effectiveness and user satisfaction. By leveraging Grafana Agent Observability, you can ensure that your agents not only perform well but also continuously improve based on real feedback.

Code examples

plaintext
gcx
plaintext
agento11y-instrument

When NOT to use this

The official docs don't call out specific anti-patterns here. Use your judgment based on your scale and requirements.

Want the complete reference?

Read official docs

Test what you just learned

Quiz questions written from this article

Take the quiz →
DigitalOcean Serverless InferenceSponsor

OpenAI & Anthropic-compatible inference API — no GPU provisioning needed. 55+ models, pay-per-token with no minimums. VPC + zero data retention by default.

Try Serverless Inference →

Get the daily digest

One email. 5 articles. Every morning.

No spam. Unsubscribe anytime.