What you'll learn
- Why Tempo?
- How Traces Drilldown and TraceQL help you explore trace data
- How Adaptive Traces and exemplars help you operate tracing at scale
- How Grafana Assistant and Tempo MCP fit into AI-assisted tracing workflows
Build AI-ready tracing in Grafana Cloud with Tempo, Adaptive Traces, and Grafana Assistant on the same correlated signals.
Along with metrics and logs, tracing is one of the three pillars of modern observability. Grafana Tempo is a high-volume distributed tracing backend whose only dependency is object storage. Unlike other tracing backends, Tempo can hit massive scale without a difficult-to-manage Elasticsearch or Cassandra cluster.
In this webinar, we will use an instrumented application to demonstrate how to use logs and Prometheus exemplars to find traces effectively in Tempo. The demo will cover the fundamentals of operating Tempo, showcase available features that help you optimize your use of Adaptive Traces, and highlight how Tempo enables massive scale with less operational cost and complexity than ever before.
Tracing data in Grafana Cloud connects to metrics and logs through exemplars and correlated views. With Grafana Assistant, teams can use natural-language questions and guided troubleshooting on top of the same signals—while TraceQL and Traces Drilldown remain how you prove what happened in the request path. For Tempo MCP and LLM-connected trace analysis, we’ll cover how external AI tools can query trace data via the Model Context Protocol. For a dedicated Assistant deep dive, see our Grafana Assistant webinar and documentation.
Your guide
