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Scaling our observability platform by embracing wide events and replacing OTel

TLDR # Observability at scale: Our internal system grew from 19 PiB to 100 PB of uncompressed logs and from ~40 trillion to 500 trillion rows. Efficiency breakthrough: We absorbed a 20× surge in event volume using under 10% of the CPU previously needed. OTel pitfalls: The required parsing and marshalling of events in OpenTelemetry proved a bottleneck and didn’t scale - our custom pipeline addressed this. Introducing HyperDX: ClickHouse-native observability UI for seamless exploration, correlatio

ClickHouse scales beyond 100 petabytes of logs

TLDR # Observability at scale: Our internal system grew from 19 PiB to 100 PB of uncompressed logs and from ~40 trillion to 500 trillion rows. Efficiency breakthrough: We absorbed a 20× surge in event volume using under 10% of the CPU previously needed. OTel pitfalls: The required parsing and marshalling of events in OpenTelemetry proved a bottleneck and didn’t scale - our custom pipeline addressed this. Introducing HyperDX: ClickHouse-native observability UI for seamless exploration, correlatio