Awesome GitHub RepositoriesEdge Computing Platforms

K3s is a lightweight Kubernetes distribution designed for resource-constrained environments, edge computing, and simplified deployment across diverse hardware architectures. It functions as a container orchestration engine that automates the deployment, scaling, and management of containerized applications. By bundling all necessary control plane components and dependencies into a single binary, it minimizes the system footprint and streamlines the installation process. The project distinguishes itself through a flexible architecture that supports both high-availability clustering and minimal

SurrealDB is a multi-model database engine designed to store and query document, graph, relational, and vector data within a single ACID-compliant platform. It functions as an AI-native data store, integrating vector search, graph traversal, and machine learning model execution directly into its query layer. By providing a unified declarative query language, the platform eliminates the need for external middleware to synchronize data across different storage models. The platform distinguishes itself through its ability to manage agent memory and complex workflows natively. It allows developer

MicroK8s is a lightweight, single-package Kubernetes distribution designed for resource-constrained environments, edge computing, and local development. It packages all Kubernetes control-plane components into a single daemon process, reducing resource overhead while maintaining full Kubernetes conformance. The project is distributed as a snap package, enabling automatic updates and strict confinement for secure deployment on Linux systems. The distribution distinguishes itself through its minimal footprint and self-contained architecture, running all Kubernetes services as one process with a

KubeEdge is a distributed edge computing framework that extends Kubernetes to manage containerized workloads and hardware devices at the edge. It functions as a Kubernetes edge orchestration system, allowing the deployment and management of applications across distributed edge nodes using native Kubernetes APIs and workflows. The project distinguishes itself through a specialized focus on IoT integration and node autonomy. It employs digital-twin state modeling to represent physical hardware devices as virtual objects, utilizing an MQTT-based messaging bus for communication with heterogeneous