Abstract: The foregoing are among the objects attained by the invention which provides cloud native distributed, hierarchical methods and apparatus for the ingestion of data generated by a fully-instrumented manufacturing or industrial plants. The systems and methods employ an architecture that is capable of collecting and preliminarily processing data at the plant-level for self-learning detection of error (and other) conditions, and forwarding that data for more in depth processing in the cloud. The architecture takes into account the varied data throughput, storage and processing needs at each level of the hierarchy. The distributed and hierarchical system allows for the creation of a dynamic, real-time assessment of the behavior and health of assets and enables visibility and integrity into the design, manufacturing, operations and service of any asset. The use of that capability (referred to herein as PARCS™) allows for Systemic Asset Intelligence within an asset, plant, system and/or an ecosystem.