Ecosystem

3:30 PM CST, UTC+8 , November 19

Apache Pulsar + KubeEdge: Managing Edge Devices with Low Latency and Persistent Storage

Edge device management is an important scenario in edge computing. Currently, there are many challenges in this aspect, such as edge device lifecycle management, digital twin technology for edge devices, lightweight edge framework, as well as data storage, distribution and consumption.
KubeEdge is a cloud-native edge computing open-source platform built on top of Kubernetes. It is a CNCF incubating project. KubeEdge supports the interaction and collaboration between cloud and edge apps. It provides a Device Management Interface (DMI), which integrates device management APIs, optimizes device management capabilities in edge computing scenarios, and builds a device digital twin management platform based on cloud native technologies. In the DMI framework, the device management plane data is decoupled from the device service plane data. In this way, device CRDs are only used for the lifecycle management of the device itself, and the device service plane data is directly provided for data-consuming applications through microservices. In this architecture, devices are no longer pure data sources. Instead, they are cloud native device microservices. The DMI framework also provides multiple data push modes, enabling data consumers to obtain device data more flexibly and providing better user experience.
In this session, I will introduce a management solution for edge devices implemented through the Device Management Interface of KubeEdge and Apache Pulsar. In this solution, Mapper, an edge device driver app developed through the DMI, collects device data and push them to Pulsar brokers. The data are then delivered to consumer apps on the cloud based on preset configurations. Pulsar is a great fit for the implementation as it provides strong support for managing edge devices with low latency and persistent storage for edge data.

Speaker

Ryan Zhao

Senior Software Engineer at Huawei Cloud

Chenlin Liu

Software Engineer at DaoCloud