From Logs to Insights: Observability with ClickHouse

• Open source
• Apache Kafka®
• ClickHouse®

As systems grow more distributed, the volume of logs, metrics, and traces generated in real time is exploding. Teams need the ability to ingest this firehose of data and query it instantly for troubleshooting, monitoring, and alerting. Traditional relational databases simply weren’t designed to handle high-velocity inserts and large-scale analytical queries at the same time.

That’s where ClickHouse comes in. Purpose-built for analytical workloads, it can ingest millions of log events per second while delivering sub-second query performance—even on terabytes of data. This makes it a natural fit for observability pipelines and log analytics platforms, where engineers need fast, reliable insights without compromising on scale or cost.

In this workshop, we’ll explore:

• How ClickHouse’s storage engine and query execution differ from traditional databases.
• Why these design choices make it so effective for observability use cases.
• Real-world patterns: powering log search, anomaly detection, and live dashboards at scale.
• Where ClickHouse is the right fit—and where it isn’t.