Rethinking Cardinality & Secrets to Reliable Software

We open 2027 with two talks that look at modern engineering from very different angles. Joel Verezhak from Grafana Labs revisits cardinality in observability and asks whether years of warning developers away from it has cost us valuable insight. Dorota Parad shares the often overlooked foundations of reliable software, the parts that have nothing to do with your tech stack. A solid mix to start the year, plus the usual networking apero. Here's what's planned for the evening: 17:30 - 18:00 - Arrival and first drinks 18:00 - 18:45 - What's So Bad About Cardinality Anyway? Rethinking Metrics in the Modern Observability Ecosystem by Joel Verezhak 18:45 - 19:30 - Slow and Boring? Secrets to Building Reliable Software by Dorota Parad 19:30 - 20:30 - Networking, Open Space & More drinks\ What's So Bad About Cardinality Anyway? Rethinking Metrics in the Modern Observability Ecosystem For years, observability teams have warned developers to avoid high-cardinality metrics. We treat cardinality like a natural disaster rather than something we can design for. But what if the fear comes not from inherent limits, but from historical constraints baked into early metrics systems? This talk reexamines cardinality through a historical and architectural perspective. We'll explore how the original Prometheus design created cultural habits that persist, and how modern systems change the equation. With remote-write storage, Parquet-based engines, OTLP-native pipelines, exemplars, and alternative backends like ClickHouse, high-cardinality data is no longer something we must avoid, it's something we can use intentionally. Rather than asking how to stop cardinality, we'll ask what insights we've been missing by fearing it, and how to design observability platforms that support flexible dimensionality without compromising reliability or cost. Key takeaways: why cardinality fear is cultural and historical, not fundamental; how early metrics architectures shaped today's constraints; modern t