Apache Iceberg is a mature open desk format that’s been battle-tested within the broader analytics world for years. Now it’s time to use the advantages of an open and scalable commonplace to an observability area that badly wants to interrupt out of its siloed heritage.
It isn’t that observability has totally resisted requirements. OpenTelemetry is a well-adopted mannequin for amassing metrics, logs, and traces. However as soon as that knowledge lands, most stacks nonetheless fragment it into silos. Becoming a member of observability with enterprise knowledge sometimes means exporting, duplicating, or downsampling. It’s a expensive and error-prone course of that makes easy questions, reminiscent of “Which clients had been affected by an outage?” or “What was the income impression?” right into a bespoke knowledge challenge.
Iceberg standardizes how giant analytical knowledge units are saved and advanced on object storage, with ACID transactions, snapshot isolation, time journey, and schema evolution. It’s a impartial desk layer that any suitable compute engine can use, together with Spark, Flink, Trino/Presto, Dremio, and the main cloud knowledge platforms. That turns telemetry into first-class knowledge that lives alongside buyer, finance, and product tables with out limitless copy pipelines.
