Coralogix's introduction of Dataspaces and Datasets through its DataPrime engine marks a significant advancement in managing observability data at scale by providing a structured approach to organizing, governing, and analyzing telemetry and platform-usage events. The new architecture allows for logical data segmentation, enabling teams to isolate data based on specific boundaries like team, environment, or compliance domain, which enhances data clarity, control, and analytics predictability. This innovation addresses the challenges posed by traditional observability data management, such as schema collisions, governance issues, and performance degradation, by allowing data to be stored in smaller, purpose-built Datasets within Dataspaces, each governed by consistent policies. This structure not only simplifies governance and compliance but also accelerates analytics and provides granular cost visibility, ultimately offering a unified, scalable solution for managing observability data across organizations.