WEDA Architecture
Overview
WEDA implements a comprehensive two-tier architecture comprising WEDA Cloud and WEDA Edge components. This distributed architecture enables seamless development, deployment, and management of edge AI and IoT solutions across cloud and edge environments.
Developer Focus Areas
WEDA handles all infrastructure concerns—device connectivity, data synchronization, container orchestration, security, and lifecycle management—allowing developers to focus exclusively on business logic:
1. Frontend Development with WEDA Core APIs
Build custom management interfaces and dashboards using WEDA's RESTful APIs:
- Management Consoles: Create web-based interfaces for device monitoring and control
- Data Visualization Dashboards: Develop analytics dashboards for time-series data and KPIs
- Custom Workflows: Implement domain-specific operational workflows and automation
Leverage the Opensource UI Boilerplate to accelerate development with pre-built components.
2. AI Solution Development
Develop and deploy intelligent edge applications:
- AI Model Training: Train custom ML/AI models for specific use cases
- Sub Node Development: Build lightweight applications for constrained devices and sensors
WEDA manages model deployment, versioning, and inference infrastructure—developers focus on model accuracy and business outcomes.
Architectural Components
WEDA Cloud Layer
The cloud layer provides centralized management, orchestration, and development capabilities through a suite of API-centric services.
WEDA Core (API Centric Services)
The core platform exposes RESTful APIs for programmatic access to all platform capabilities:
- Device Management: Centralized device provisioning, configuration, and lifecycle management
- Data Management: Time-series data collection, storage, and analytics services
- AI Model Management: Model registry, versioning, and deployment orchestration
- Container Management: Container registry, stack definitions, and deployment workflows
Enablers (Toolkit & Utilities)
Foundational libraries, SDKs, and utilities providing common functionality for application development and system integration.
WEDA Edge Layer
The edge layer runs on physical devices at the network edge, enabling local processing, real-time decision-making, and autonomous operation.
WEDA Node (Device Management Agent)
The core edge runtime providing:
- Device Management Agent: Local device control, telemetry collection, and bidirectional communication with WEDA Cloud
- Data Agent: Local data buffering, preprocessing, and intelligent data forwarding
- Remote Management: Secure remote access, diagnostics, and OTA updates
- Digital Twin: Local digital twin representation for edge autonomy
Container & AI Model Management
Edge-native container runtime and AI inference engine:
- Container Management: Docker-compatible container orchestration
- AI Model Management: On-device model loading, inference execution, and model switching
Protocols & Communication
- Protocols Module: Edge protocol implementations for device connectivity (Modbus, OPC UA, MQTT, etc.)
- WEDA Sub Node (Open Source): Lightweight agent for constrained devices and sensors
Development Resources
- Ready-to-Dev Containers: Pre-configured development containers with toolchains and dependencies
- Device Library (Open Source): Community-contributed device drivers and integration templates
Enablers (Toolkit & Utilities)
Edge-optimized libraries providing common edge computing functionality such as data filtering, edge analytics.
Third-Party Edge Applications
Support for deploying third-party edge applications, microservices, and custom business logic alongside WEDA platform services.
Architecture Characteristics
Cloud-Edge Collaboration
- Bidirectional Synchronization: Seamless data and configuration sync between cloud and edge
- Offline Capability: Edge autonomy with local processing when disconnected from cloud
- Intelligent Workload Distribution: Dynamic workload placement based on latency, bandwidth, and compute constraints
Scalability & Extensibility
- Horizontal Scaling: Support for thousands of edge devices managed from a single cloud instance
- Modular Design: Pluggable architecture allowing custom modules and protocol adapters
- Open Standards: Adherence to industry standards (Docker, Kubernetes, MQTT, OPC UA)
Security & Reliability
- Zero-Trust Architecture: Mutual TLS authentication and encrypted communication channels
- Edge Data Sovereignty: Sensitive data processing at edge without cloud transmission
- Fault Tolerance: Automatic failover and self-healing capabilities at both cloud and edge layers
Bottom Line: WEDA provides the platform; you provide the intelligence. Focus on what makes your solution unique while WEDA handles the complexity of edge infrastructure.