How Data Lakehouse Architecture Is Reshaping Observability

Modern Observability Needs a New Architecture

Enterprise telemetry is growing at an unprecedented rate. Logs, metrics, and traces are expanding faster than traditional observability platforms were ever designed to handle.

Our new white paper explores how legacy observability architectures rely heavily on index-based storage, driving up ingestion and storage costs while forcing engineering teams into painful compromises:

• Sampling telemetry data to control costs
• Dropping high-cardinality fields to shrink index size
• Limiting retention to only days of data

These tradeoffs reduce visibility when teams need it most.

A new model is emerging.

Discover how engineering and platform teams are modernizing their observability architecture with the data lakehouse model.