Fledge
Fledge is an open-source industrial Internet of Things (IoT) edge platform (edge computing / industrial data integration) under LF Edge designed for collecting, buffering, processing, and integrating data from industrial assets and Operational technology (OT) systems with enterprise and cloud environments.
- Industrial IoT edge platform for data collection, processing, and integration (edge computing / Industrial IoT (IIOT))
- Supports bi-directional data flows between industrial assets, on-premises (on-prem) systems, and cloud services (data integration)
- Plugin-based architecture for southbound device/OT connectivity and northbound enterprise/cloud connectors (extensible integration framework)
- Provides local buffering, filtering, and transformation of time-series and sensor data near the source (data pipeline / stream processing)
- Designed for deployment in operational environments such as manufacturing, energy, and other industrial sectors (industrial edge)
More About Fledge
Fledge is an open-source industrial IoT edge platform (edge computing / industrial data integration) hosted by LF Edge and focused on OT environments such as manufacturing, energy, and other industrial sectors. The project addresses the problem of connecting heterogeneous industrial equipment and sensors, normalizing and processing their data locally at the edge, and integrating that data with on-prem systems and cloud platforms for monitoring, analytics, and control.
The platform provides an edge data pipeline (data ingestion and processing) that runs close to industrial assets. It collects time-series and sensor data from OT systems and field devices, applies local buffering, filtering, and transformation, and delivers that data to upstream systems. This architecture reduces dependency on continuous network connectivity and allows industrial facilities to maintain local workloads while still feeding data into centralized applications, enterprise platforms, and public cloud services.
Fledge uses a plugin-based architecture (extensible integration framework) to support a range of southbound and northbound integrations. Southbound plugins handle device and protocol connectivity to industrial equipment and control systems, providing interfaces to various sensors, controllers, and OT protocols. Northbound plugins connect to databases, historians, analytics platforms, and cloud IoT services, enabling enterprises to route processed edge data into existing IT and data platforms without redesigning core systems.
The project is designed for deployment at the operational edge (industrial edge computing), typically on gateways, industrial Process Control System (PCS), or other on-site infrastructure located within plants, factories, or field installations. In such environments, Fledge supports local data handling, including buffering to manage intermittent connectivity, and configurable processing pipelines that can apply rules, transformations, or aggregations before data leaves the site. This supports use cases such as condition monitoring, performance tracking, and integration with asset management or analytics tools.
Within enterprise and institutional settings, Fledge operates as an intermediary layer between OT and IT (OT/IT integration). It enables organizations to connect legacy and modern industrial assets to cloud and enterprise applications in a controlled and modular way. Because it is part of LF Edge, Fledge is positioned within an ecosystem of edge computing projects focused on interoperability, common frameworks, and open standards for distributed systems at the network edge.
From a directory and taxonomy perspective, Fledge can be categorized primarily as an industrial IoT edge platform (edge computing / IIOT), with secondary roles in data integration (enterprise and cloud connectors), device and protocol connectivity (OT connectivity), and data pipeline processing (ingestion, buffering, and transformation) for operational environments.