When theory meets scale: Operating Mimir and Tempo in production

Operating distributed databases at scale can be challenging. It is not just about algorithms, but also about surviving failure, unpredictable load, and human mistakes.

In this session, Grafana Mimir maintainer Marco Pracucci and Grafana Tempo maintainer Marty Disibio share hard-earned lessons from growing these two databases to massive scale in Grafana Cloud. Although Mimir and Tempo serve different telemetry signals, they share the same core architecture and design principles.

Marty and Marco start by presenting the architecture and the key decisions that allow Mimir and Tempo to scale reliably and cost-effectively. Then they move to practice, showing how those principles hold up in production – and where they don’t – by contrasting the real bottlenecks, breaking points, and operational failure modes they see in metrics versus traces.