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Architecture

Unified Backend for Heterogeneous Data Sources (SAFE)

This system is a centralized backend framework designed to integrate heterogeneous devices and data sources through a repeatable, plugin-driven architecture.

At a high level, the platform provides:

  • a consistent RESTful CRUD model for core resources
  • a unified data model to represent heterogeneous devices
  • a real-time channel (WebSocket) to propagate updates to frontends
  • a publish/subscribe layer for device events and state changes
  • a plugin lifecycle and extension model to avoid rewriting integration logic per device family
  • contract-based plugin validation (runtime contracts)
  • a CLI control plane for repeatable development, testing, packaging, and deployment workflows

This case study is presented in a SAFE form: it intentionally avoids product identifiers, real endpoints, proprietary protocols, and implementation fingerprints.

High-Level Platform Architecture

The architecture can be understood as a layered platform with explicit boundaries between:

  • frontend integration (REST + WebSocket)
  • core platform services (model, validation, eventing)
  • plugin execution (device/domain-specific logic)
  • external systems and devices (heterogeneous sources)
flowchart TB
  UI[Frontend UI] <--> API[Service Layer API]
  API <--> CORE_NODE[Core Platform]

  subgraph CORE_LAYER[Core Platform]
    MODEL[Unified Device Model]
    VALID[Validation and Invariants]
    EVENTS[Eventing PubSub]
    STORE[(Persistence and State)]
  end

  CORE_NODE <--> PLUGINS[Plugin Execution Layer]
  PLUGINS <--> EXT[External Devices and Systems]

  API --> MODEL
  CORE_NODE --> VALID
  CORE_NODE --> EVENTS
  CORE_NODE --> STORE

This structure keeps the system evolvable:

  • plugins encapsulate heterogeneity
  • the core governs invariants and contracts
  • frontend integration stays stable as the ecosystem grows

Resource Model (Abstract)

The core API follows a repeatable CRUD model over a small set of conceptual resources. Names and identifiers are intentionally abstracted.

Typical resource groups include:

  • Workspace / Service Context
    A scoped environment used to isolate deployments or tenants.

  • Installation / Site
    A container representing a physical or logical environment where devices are managed.

  • Gateway / Connector
    A connection point to an external ecosystem or device domain (e.g., a remote service, controller, or network endpoint).

  • Device
    A normalized representation of a device, independent from vendor protocol.

This structure enables a consistent lifecycle across heterogeneous ecosystems.

Unified Device Model

To unify heterogeneous devices under one backend and one frontend integration model, devices are represented using a consistent internal schema.

A typical device representation includes:

  • information
    Identity and descriptive metadata (id, name, category, location hints).

  • properties
    A key/value map representing state and measurements.

  • actions
    Callable operations exposed by the device, represented as action identifiers.

  • widget
    A declarative UI schema describing frontend rendering and interactions.

This model keeps downstream services and frontends device-agnostic.

Declarative UI Schema (Widget DSL)

A key architectural choice is the use of a declarative UI schema to describe frontend rendering and interactions.

Plugins provide a JSON-based schema that can encode:

  • UI components (toggle, slider, numeric input, chart)
  • bindings to device properties
  • event listeners mapping UI interactions to device actions

This yields:

  • faster UI iteration
  • consistent UX across heterogeneous devices
  • a stable contract between device models and frontend rendering

In SAFE documentation, UI schema examples should be toy-oriented and non-identifying.

Plugin Model and Lifecycle

The platform’s extensibility relies on a plugin architecture.

A plugin:

  • extends the platform core
  • implements a well-defined set of methods, typically including:
  • discovery: how devices are identified and enumerated
  • mapping: how raw data is transformed into the unified model
  • actions: how operations are exposed and executed
  • subscriptions: how device events/state updates are propagated

The platform core provides:

  • a consistent execution context
  • shared infrastructure (persistence, eventing, real-time updates)
  • governance (validation and contracts)

Runtime Contracts and Plugin Governance

Plugins are validated through runtime contracts to ensure they meet platform expectations.

Contract enforcement guarantees that plugins:

  • implement required methods and structures
  • respect platform invariants and integration rules
  • produce device models compatible with the unified schema
  • expose actions and UI schemas in a predictable way
flowchart LR
  P[Plugin Package] --> CV[Contract Validation]
  CV -->|valid| INIT[Initialize Context]
  CV -->|invalid| REJ[Reject Plugin]

  INIT --> DISC[Discovery Phase]
  DISC --> MAP[Mapping Phase]
  MAP --> UDM[Unified Device Model]
  UDM --> UIX[UI Schema Widget DSL]
  UDM --> API[REST API]
  UDM --> WS[WebSocket Updates]
  UDM --> EV[PubSub Events]

  CV -.->|runtime contracts| GOV[Governance Rules]
  GOV -.->|enforced across lifecycle| DISC
  GOV -.->|enforced across lifecycle| MAP

Execution Units and Context Isolation

The platform treats framework + plugin as the effective execution unit.

Each plugin runs with a separate execution context, isolating:

  • configuration and environment variables
  • credentials and secrets
  • runtime assumptions and boundaries
  • integration state and operational behavior

This isolation helps prevent:

  • accidental cross-plugin coupling
  • configuration leakage
  • dependency conflicts across heterogeneous connectors
  • unpredictable side effects during integration

and supports a controlled, scalable plugin ecosystem.

Real-Time Updates and Eventing

The platform combines:

  • REST for CRUD and query workflows
  • WebSocket for push-based updates to frontends
  • pub/sub for event distribution and reactive workflows
sequenceDiagram
  participant UI as Frontend
  participant API as REST API
  participant CORE as Core Platform
  participant PL as Plugin
  participant WS as WebSocket

  UI->>API: CRUD / Queries
  API->>CORE: Read/Write operations
  PL->>CORE: Device updates / events
  CORE-->>WS: Push state changes
  WS-->>UI: Real-time updates
  CORE-->>CORE: Publish/Subscribe routing

This design enables real-time dashboards without polling and supports reactive processing built around device state changes.

Control Plane: CLI, Compose, and Dev Deployment

Operations are part of the architecture.

A CLI acts as a control plane that supports repeatable workflows such as:

  • plugin validation before execution
  • safe device testing in controlled environments (e.g., action sandboxing)
  • generating and operating on a local composition setup (compose generation + lifecycle commands)
  • building deployable artifacts (e.g., container images)
  • deploying in development-oriented mode to orchestrated environments (e.g., Kubernetes)
flowchart TB
  DEV[Developer] --> CLI[CLI Control Plane]

  subgraph CP[Control Plane Workflows]
    V[Validate plugins and contracts]
    T[Safe device testing actions]
    C[Generate and operate composition setup]
    B[Build deployable artifacts]
    D[Dev-oriented orchestration deploy]
  end

  CLI --> V
  CLI --> T
  CLI --> C
  CLI --> B
  CLI --> D

  DU[Deployable Unit Framework plus Plugin] --> RT[Target Runtime]
  B --> DU
  D --> RT
  C --> RT

  RT --> TGT[Server-class and embedded targets]

This approach keeps development predictable and reduces operational drift between local environments and deployment targets.

Portability Across Heterogeneous Targets

The system is designed to run across heterogeneous compute environments:

  • standard server-class hardware
  • resource-constrained embedded systems

This portability requirement influences architectural decisions such as:

  • bounded resource usage and predictable workloads
  • consistent runtime contracts across environments
  • repeatable packaging and deployment workflows
  • isolation of device-specific complexity in plugins

Portability is treated as a design constraint, not an afterthought.

Error Semantics (Abstract)

The platform exposes predictable error semantics:

  • authentication failures → unauthorized
  • missing resources → not found
  • unexpected internal failures → generic safe error output

This keeps client behavior deterministic and reduces the risk of leaking sensitive implementation details through error messages.

SAFE Disclosure

This case study intentionally omits:

  • product identifiers and company references
  • real endpoints, tokens, and operational examples
  • proprietary protocols and implementation details

The focus is exclusively on:

  • architectural patterns
  • integration governance via runtime contracts
  • plugin lifecycle design and context isolation
  • unified modeling and frontend decoupling
  • transferable system design principles