From the Observability TAG: Designing a Common Query Language for Observability Data

Unifying query languages is key in reducing toil for app developers and end users to query and analyze observability data. A common query language that can leverage all observability data such as metrics, traces, profiles, events, logs to facilitate correlation, support trend analytics and provide end-to-end observability for AI applications. The Observability TAG QLS workgroup published a common query language spec in 2024. The workgroup recommended a SQL-like language. This talk will explore the design principles and challenges of creating a generic query language. It will delve into the core concepts, syntax, and semantics of such a language, drawing inspiration from SQL while addressing the unique requirements of observability data. It will also explore the trade-offs between simplicity, expressiveness, and performance. This query language convergence for end-to-end analytics could enhance reliability and operational efficiency for SREs and your app developers. A win-win for all.