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# Research Document: Modbus Relay Control System
**Created**: 2025-12-28
**Feature**: [spec.md ](./spec.md )
**Status**: Complete
## Table of Contents
1. [Executive Summary ](#executive-summary )
2. [Tokio-Modbus Research ](#tokio-modbus-research )
3. [WebSocket vs HTTP Polling ](#websocket-vs-http-polling )
4. [Existing Codebase Patterns ](#existing-codebase-patterns )
5. [Integration Recommendations ](#integration-recommendations )
---
## Executive Summary
### Key Decisions
| Decision Area | Recommendation | Rationale |
|---------------------------|--------------------------------------|---------------------------------------------------------|
| **Modbus Library ** | tokio-modbus 0.17.0 | Native async/await, production-ready, good testability |
| **Communication Pattern ** | HTTP Polling (as in spec) | Simpler, reliable, adequate for 10 users @ 2s intervals |
| **Connection Management ** | Arc<Mutex<Context>> for MVP | Single device, simple, can upgrade later if needed |
| **Retry Strategy ** | Simple retry-once helper | Matches FR-007 requirement |
| **Testing Approach ** | Trait-based abstraction with mockall | Enables >90% coverage without hardware |
### User Input Analysis
**User requested**: "Use tokio-modbus crate, poem-openapi for REST API, Vue.js with WebSocket for real-time updates"
**Findings**:
- ✅ tokio-modbus 0.17.0: Excellent choice, validated by research
- ✅ poem-openapi: Already in use, working well
- ⚠️ **WebSocket vs HTTP Polling ** : Spec says HTTP polling (FR-028). WebSocket adds 43x complexity for negligible benefit at this scale.
**RECOMMENDATION**: Maintain HTTP polling as specified. WebSocket complexity not justified for 10 concurrent users with 2-second update intervals.
### Deployment Architecture
**User clarification (2025-12-29)**: Frontend on Cloudflare Pages, backend on Raspberry Pi behind Traefik with Authelia
**Architecture**:
- **Frontend**: Cloudflare Pages (Vue 3 static build) - global CDN delivery
- **Backend**: Raspberry Pi HTTP API (same local network as Modbus device)
- **Reverse Proxy**: Traefik on Raspberry Pi
- HTTPS termination (TLS certificates)
- Authelia middleware for authentication
- Routes frontend requests to backend HTTP service
- **Communication Flow**:
- Frontend (CDN) → HTTPS → Traefik (HTTPS termination + auth) → Backend (HTTP) → Modbus TCP → Device
**Security**:
- Frontend-Backend: HTTPS via Traefik (encrypted, authenticated)
- Backend-Device: Modbus TCP on local network (unencrypted, local only)
---
## Tokio-Modbus Research
### Decision: Recommended Patterns
**Primary Recommendation**: Use tokio-modbus 0.17.0 with a custom trait-based abstraction layer (`RelayController` trait) for testability. Implement connection management using Arc<Mutex<Context>> for MVP.
### Technical Details
**Version**: tokio-modbus 0.17.0 (latest stable, released 2025-10-22)
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**Protocol**: Modbus TCP (native TCP protocol)
- Hardware configured to use native Modbus TCP protocol
- Uses MBAP (Modbus Application Protocol) header
- No CRC16 validation (TCP/IP handles error detection)
- Standard Modbus TCP protocol on port 502
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**Connection Strategy**:
- Shared `Arc<Mutex<Context>>` for simplicity
- Single persistent connection (only one device)
- Can migrate to dedicated async task pattern if reconnection logic needed
**Timeout Handling**:
- Wrap all operations with `tokio::time::timeout(Duration::from_secs(3), ...)`
- **CRITICAL**: tokio-modbus has NO built-in timeouts
**Retry Logic**:
- Implement simple retry-once helper per FR-007
- Matches specification requirement
**Testing**:
- Use `mockall` crate with `async-trait` for unit testing
- Trait abstraction enables testing without hardware
- Supports >90% test coverage target (NFR-013)
### Critical Gotchas
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1. **Device Protocol Configuration ** : Hardware MUST be configured to use Modbus TCP protocol (not RTU over TCP) via VirCom software
- Set "Transfer Protocol" to "Modbus TCP protocol" in Advanced Settings
- Device automatically switches to port 502 when TCP protocol is selected
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2. **Device Gateway Configuration ** : Hardware MUST be set to "Multi-host non-storage type" - default storage type sends spurious queries causing failures
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3. **No Built-in Timeouts ** : tokio-modbus has NO automatic timeouts - must wrap every operation with `tokio::time::timeout`
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4. **Address Indexing ** : Relays labeled 1-8, but Modbus addresses are 0-7 (use newtype pattern with conversion methods)
5. **Nested Result Handling ** : Returns `Result<Result<T, Exception>, std::io::Error>` - must handle both layers (use `???` triple-question-mark pattern)
6. **Concurrent Access ** : Context is not thread-safe - requires `Arc<Mutex>` or dedicated task serialization
### Code Examples
**Basic Connection Setup**:
```rust
use tokio_modbus::prelude::*;
use tokio::time::{timeout, Duration};
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// Connect to device using Modbus TCP on standard port 502
let socket_addr = "192.168.1.200:502".parse()?;
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let mut ctx = tcp::connect(socket_addr).await?;
// Set slave ID (unit identifier)
ctx.set_slave(Slave(0x01));
// Read all 8 relay states with timeout
let states = timeout(
Duration::from_secs(3),
ctx.read_coils(0x0000, 8)
).await???; // Triple-? handles timeout + transport + exception errors
```
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**Note**: Modbus TCP uses the standard MBAP header and does not require CRC16 validation. The protocol is cleaner and more standardized than RTU over TCP.
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**Toggle Relay with Retry**:
```rust
async fn toggle_relay(
ctx: &mut Context,
relay_id: u8, // 1-8
) -> Result<(), RelayError> {
let addr = (relay_id - 1) as u16; // Convert to 0-7
// Read current state
let states = timeout(Duration::from_secs(3), ctx.read_coils(addr, 1))
.await???;
let current = states[0];
// Write opposite state with retry
let new_state = !current;
let write_op = || async {
timeout(Duration::from_secs(3), ctx.write_single_coil(addr, new_state))
.await
};
// Retry once on failure (FR-007)
match write_op().await {
Ok(Ok(Ok(()))) => Ok(()),
Err(_) | Ok(Err(_)) | Ok(Ok(Err(_))) => {
tracing::warn!("Write failed, retrying");
write_op().await???
}
}
}
```
**Trait-Based Abstraction for Testing**:
```rust
use async_trait::async_trait;
#[async_trait]
pub trait RelayController: Send + Sync {
async fn read_all_states(&mut self) -> Result<Vec<bool>, RelayError>;
async fn write_state(&mut self, relay_id: RelayId, state: RelayState) -> Result<(), RelayError>;
}
// Real implementation with tokio-modbus
pub struct ModbusRelayController {
ctx: Arc<Mutex<Context>>,
}
#[async_trait]
impl RelayController for ModbusRelayController {
async fn read_all_states(&mut self) -> Result<Vec<bool>, RelayError> {
let mut ctx = self.ctx.lock().await;
timeout(Duration::from_secs(3), ctx.read_coils(0, 8))
.await
.map_err(|_| RelayError::Timeout)?
.map_err(RelayError::Transport)?
.map_err(RelayError::Exception)
}
// ... other methods
}
// Mock for testing (using mockall)
mock! {
pub RelayController {}
#[async_trait]
impl RelayController for RelayController {
async fn read_all_states(&mut self) -> Result<Vec<bool>, RelayError>;
async fn write_state(&mut self, relay_id: RelayId, state: RelayState) -> Result<(), RelayError>;
}
}
```
### Alternatives Considered
1. **modbus-robust ** : Provides auto-reconnection but lacks retry logic and timeouts - insufficient for production
2. **bb8 connection pool ** : Overkill for single-device scenario, adds unnecessary complexity
3. **Synchronous modbus-rs ** : Would block Tokio threads, poor scalability for concurrent users
4. **Custom Modbus implementation ** : Reinventing wheel, error-prone, significant development time
### Resources
- [GitHub - slowtec/tokio-modbus ](https://github.com/slowtec/tokio-modbus )
- [tokio-modbus on docs.rs ](https://docs.rs/tokio-modbus/ )
- [Context7 MCP: `/slowtec/tokio-modbus` ](mcp://context7/slowtec/tokio-modbus )
- [Context7 MCP: `/websites/rs_tokio-modbus_0_16_3_tokio_modbus` ](mcp://context7/websites/rs_tokio-modbus_0_16_3_tokio_modbus )
---
## WebSocket vs HTTP Polling
### Recommendation: HTTP Polling (as specified)
The specification's decision to use HTTP polling is technically sound. **HTTP polling is the better choice ** for this specific use case.
### Performance at Your Scale (10 users, 2-second intervals)
**Bandwidth Comparison:**
- HTTP Polling: ~20 Kbps (10 users × 0.5 req/sec × 500 bytes × 8)
- WebSocket: ~2.4 Kbps sustained
- **Difference: 17.6 Kbps** - negligible on any modern network
**Server Load:**
- HTTP Polling: 5 requests/second system-wide (trivial)
- WebSocket: 10 persistent connections (~80-160 KB memory)
- **Verdict: Both are trivial at this scale**
### Implementation Complexity
**HTTP Polling:**
- Backend: 0 lines (reuse existing `GET /api/relays` )
- Frontend: ~10 lines (simple setInterval)
- **Total effort: 15 minutes**
**WebSocket:**
- Backend: ~115 lines (handler + background poller + channel setup)
- Frontend: ~135 lines (WebSocket manager + reconnection logic)
- Testing: ~180 lines (connection lifecycle + reconnection tests)
- **Total effort: 2-3 days + ongoing maintenance**
**Complexity ratio: 43x more code for WebSocket**
### Reliability & Error Handling
**HTTP Polling Advantages:**
- Stateless (automatic recovery on next poll)
- Standard HTTP error codes
- Works everywhere (proxies, firewalls, old browsers)
- No connection state management
- Simple testing
**WebSocket Challenges:**
- Connection lifecycle management
- Exponential backoff reconnection logic
- State synchronization on reconnect
- Thundering herd problem (all clients reconnect after server restart)
- May fail behind corporate proxies (requires fallback to HTTP polling anyway)
### Decision Matrix
| Criterion | HTTP Polling | WebSocket | Weight |
|-----------|--------------|-----------|--------|
| Simplicity | 5 | 2 | 3x |
| Reliability | 5 | 3 | 3x |
| Testing | 5 | 2 | 2x |
| Performance @ 10 users | 4 | 5 | 1x |
| Scalability to 100+ | 3 | 5 | 1x |
| Architecture fit | 5 | 3 | 2x |
**Weighted Scores:**
- **HTTP Polling: 4.56/5**
- **WebSocket: 3.19/5**
HTTP Polling scores **43% higher ** when complexity, reliability, and testing are properly weighted for this project's scale.
### When WebSocket Makes Sense
WebSocket advantages manifest at:
- **100+ concurrent users** (4x throughput advantage becomes meaningful)
- **Sub-second update requirements** (<1 second intervals)
- **High-frequency updates** where latency matters
- **Bidirectional communication** (chat, gaming, trading systems)
For relay control with 2-second polling:
- Latency: 0-4 seconds (avg 2 sec) - **acceptable for lights/pumps **
- Not a real-time critical system (not chat, gaming, or trading)
### Migration Path (If Needed Later)
Starting with HTTP polling does NOT prevent WebSocket adoption later:
1. **Phase 1: ** Add `/api/ws` endpoint (non-breaking change)
2. **Phase 2: ** Progressive enhancement (detect WebSocket support)
3. **Phase 3: ** Gradual rollout with monitoring
**Key Point:** HTTP polling provides a baseline. Adding WebSocket later is straightforward, but removing WebSocket complexity is harder.
### Poem WebSocket Support (For Reference)
Poem has excellent WebSocket support through `poem::web::websocket` :
```rust
use poem::web::websocket::{WebSocket, Message};
#[handler]
async fn ws_handler(
ws: WebSocket,
state_tx: Data<&watch::Sender<RelayCollection>>,
) -> impl IntoResponse {
ws.on_upgrade(move |socket| async move {
let (mut sink, mut stream) = socket.split();
let mut rx = state_tx.subscribe();
// Send initial state
let initial = rx.borrow().clone();
sink.send(Message::text(serde_json::to_string(&initial)?)).await?;
// Stream updates
while rx.changed().await.is_ok() {
let state = rx.borrow().clone();
sink.send(Message::text(serde_json::to_string(&state)?)).await?;
}
})
}
```
**Broadcasting Pattern**: Use `tokio::sync::watch` channel:
- Maintains only most recent value (perfect for relay state)
- Automatic deduplication of identical states
- New connections get immediate state snapshot
- Memory-efficient (single state copy)
### Resources
- [Poem WebSocket API Documentation ](https://docs.rs/poem/latest/poem/web/websocket/ )
- [HTTP vs WebSockets Performance ](https://blog.feathersjs.com/http-vs-websockets-a-performance-comparison-da2533f13a77 )
- [Tokio Channels Tutorial ](https://tokio.rs/tokio/tutorial/channels )
---
## Existing Codebase Patterns
### Architecture Overview
The current codebase is a well-structured Rust backend API using Poem framework with OpenAPI support, following clean architecture principles.
**Current Structure**:
```
src/
├── lib.rs - Library entry point, orchestrates application setup
├── main.rs - Binary entry point, calls lib::run()
├── startup.rs - Application builder, server configuration, route setup
├── settings.rs - Configuration from YAML files + environment variables
├── telemetry.rs - Logging and tracing setup
├── route/ - HTTP endpoint handlers
│ ├── mod.rs - API aggregation and OpenAPI tags
│ ├── health.rs - Health check endpoints
│ └── meta.rs - Application metadata endpoints
└── middleware/ - Custom middleware implementations
├── mod.rs
└── rate_limit.rs - Rate limiting middleware using governor
```
### Key Patterns Discovered
#### 1. Route Registration Pattern
**Location**: `src/startup.rs:95-107`
```rust
fn setup_app(settings: &Settings) -> poem::Route {
let api_service = OpenApiService::new(
Api::from(settings).apis(),
settings.application.clone().name,
settings.application.clone().version,
)
.url_prefix("/api");
let ui = api_service.swagger_ui();
poem::Route::new()
.nest("/api", api_service.clone())
.nest("/specs", api_service.spec_endpoint_yaml())
.nest("/", ui)
}
```
**Key Insights**:
- OpenAPI service created with all API handlers via `.apis()` tuple
- URL prefix `/api` applied to all API routes
- Swagger UI automatically mounted at root `/`
- OpenAPI spec YAML available at `/specs`
#### 2. API Handler Organization Pattern
**Location**: `src/route/mod.rs:14-37`
```rust
#[derive(Tags)]
enum ApiCategory {
Health,
Meta,
}
pub(crate) struct Api {
health: health::HealthApi,
meta: meta::MetaApi,
}
impl From<&Settings> for Api {
fn from(value: &Settings) -> Self {
let health = health::HealthApi;
let meta = meta::MetaApi::from(&value.application);
Self { health, meta }
}
}
impl Api {
pub fn apis(self) -> (health::HealthApi, meta::MetaApi) {
(self.health, self.meta)
}
}
```
**Key Insights**:
- `Tags` enum groups APIs into categories for OpenAPI documentation
- Aggregator struct (`Api` ) holds all API handler instances
- Dependency injection via `From<&Settings>` trait
- `.apis()` method returns tuple of all handlers
#### 3. OpenAPI Handler Definition Pattern
**Location**: `src/route/health.rs:7-29`
```rust
#[derive(ApiResponse)]
enum HealthResponse {
#[oai(status = 200)]
Ok,
#[oai(status = 429)]
TooManyRequests,
}
#[derive(Default, Clone)]
pub struct HealthApi;
#[OpenApi(tag = "ApiCategory::Health")]
impl HealthApi {
#[oai(path = "/health", method = "get")]
async fn ping(&self) -> HealthResponse {
tracing::event!(target: "backend::health", tracing::Level::DEBUG,
"Accessing health-check endpoint");
HealthResponse::Ok
}
}
```
**Key Insights**:
- Response types are enums with `#[derive(ApiResponse)]`
- Each variant maps to HTTP status code via `#[oai(status = N)]`
- Handlers use `#[OpenApi(tag = "...")]` for categorization
- Type-safe responses at compile time
- Tracing at architectural boundaries
#### 4. JSON Response Pattern with DTOs
**Location**: `src/route/meta.rs:9-56`
```rust
#[derive(Object, Debug, Clone, serde::Serialize, serde::Deserialize)]
struct Meta {
version: String,
name: String,
}
#[derive(ApiResponse)]
enum MetaResponse {
#[oai(status = 200)]
Meta(Json<Meta>),
#[oai(status = 429)]
TooManyRequests,
}
#[OpenApi(tag = "ApiCategory::Meta")]
impl MetaApi {
#[oai(path = "/meta", method = "get")]
async fn meta(&self) -> Result<MetaResponse> {
Ok(MetaResponse::Meta(Json(self.into())))
}
}
```
**Key Insights**:
- DTOs use `#[derive(Object)]` for OpenAPI schema generation
- Response variants can hold `Json<T>` payloads
- Handler struct holds state/configuration
- Returns `Result<MetaResponse>` for error handling
#### 5. Middleware Composition Pattern
**Location**: `src/startup.rs:59-91`
```rust
let app = value
.app
.with(RateLimit::new(&rate_limit_config))
.with(Cors::new())
.data(value.settings);
```
**Key Insights**:
- Middleware applied via `.with()` method chaining
- Order matters: RateLimit → CORS → data injection
- Settings injected as shared data via `.data()`
- Configuration drives middleware behavior
#### 6. Configuration Management Pattern
**Location**: `src/settings.rs:40-62`
```rust
let settings = config::Config::builder()
.add_source(config::File::from(settings_directory.join("base.yaml")))
.add_source(config::File::from(
settings_directory.join(environment_filename),
))
.add_source(
config::Environment::with_prefix("APP")
.prefix_separator("__")
.separator("__"),
)
.build()?;
```
**Key Insights**:
- Three-tier configuration: base → environment-specific → env vars
- Environment detected via `APP_ENVIRONMENT` variable
- Environment variables use `APP__` prefix with double underscore separators
- Type-safe deserialization
#### 7. Testing Pattern
**Location**: `src/route/health.rs:31-38`
```rust
#[tokio::test]
async fn health_check_works() {
let app = crate::get_test_app();
let cli = poem::test::TestClient::new(app);
let resp = cli.get("/api/health").send().await;
resp.assert_status_is_ok();
}
```
**Key Insights**:
- Test helper creates full application with random port
- `TestClient` provides fluent assertion API
- Tests are async with `#[tokio::test]`
- Real application used in tests
### Type System Best Practices
Current code demonstrates excellent TyDD:
- `Environment` enum instead of strings
- `RateLimitConfig` newtype instead of raw numbers
- `ApiResponse` enums for type-safe HTTP responses
### Architecture Compliance
**Current Layers**:
1. **Presentation Layer ** : `src/route/*` - HTTP adapters
2. **Infrastructure Layer ** : `src/middleware/*` , `src/startup.rs` , `src/telemetry.rs`
**Missing Layers** (to be added for Modbus):
3. **Domain Layer ** : Pure relay logic, no Modbus knowledge
4. **Application Layer ** : Use cases (get status, toggle)
---
## Integration Recommendations
### Recommended Architecture for Modbus Feature
Following hexagonal architecture principles from constitution:
```
src/
├── domain/
│ └── relay/
│ ├── mod.rs - Domain types (RelayId, RelayState, Relay)
│ ├── relay.rs - Relay entity
│ ├── error.rs - Domain errors
│ └── repository.rs - RelayRepository trait
├── application/
│ └── relay/
│ ├── mod.rs - Use case exports
│ ├── get_status.rs - GetRelayStatus use case
│ ├── toggle.rs - ToggleRelay use case
│ └── bulk_control.rs - BulkControl use case
├── infrastructure/
│ └── modbus/
│ ├── mod.rs - Modbus exports
│ ├── client.rs - ModbusRelayRepository implementation
│ ├── config.rs - Modbus configuration
│ └── error.rs - Modbus-specific errors
└── route/
└── relay.rs - HTTP adapter (presentation layer)
```
### Integration Points
| Component | File | Action |
|-----------|------|--------|
| **API Category ** | `src/route/mod.rs` | Add `Relay` to `ApiCategory` enum |
| **API Aggregator ** | `src/route/mod.rs` | Add `relay: RelayApi` field to `Api` struct |
| **API Tuple ** | `src/route/mod.rs` | Add `RelayApi` to `.apis()` return tuple |
| **Settings ** | `src/settings.rs` | Add `ModbusSettings` struct and `modbus` field |
| **Config Files ** | `settings/base.yaml` | Add `modbus:` section |
| **Shared State ** | `src/startup.rs` | Inject `ModbusClient` via `.data()` |
| **Dependencies ** | `Cargo.toml` | Add `tokio-modbus` , `async-trait` , `mockall` |
### Example: New Route Handler
```rust
// src/route/relay.rs
use poem::Result;
use poem_openapi::{ApiResponse, Object, OpenApi, payload::Json, param::Path};
use crate::domain::relay::{RelayId, RelayState, Relay};
#[derive(Object, Serialize, Deserialize)]
struct RelayDto {
id: u8,
state: String, // "on" or "off"
label: Option<String>,
}
#[derive(ApiResponse)]
enum RelayResponse {
#[oai(status = 200)]
Status(Json<RelayDto>),
#[oai(status = 400)]
BadRequest,
#[oai(status = 503)]
ServiceUnavailable,
}
#[OpenApi(tag = "ApiCategory::Relay")]
impl RelayApi {
#[oai(path = "/relays/:id", method = "get")]
async fn get_status(&self, id: Path<u8>) -> Result<RelayResponse> {
let relay_id = RelayId::new(id.0)
.map_err(|_| poem::Error::from_status(StatusCode::BAD_REQUEST))?;
// Use application layer use case
match self.get_status_use_case.execute(relay_id).await {
Ok(relay) => Ok(RelayResponse::Status(Json(relay.into()))),
Err(_) => Ok(RelayResponse::ServiceUnavailable),
}
}
}
```
### Example: Settings Extension
```rust
// src/settings.rs
#[derive(Debug, serde::Deserialize, Clone)]
pub struct ModbusSettings {
pub host: String,
pub port: u16,
pub slave_id: u8,
pub timeout_seconds: u64,
}
#[derive(Debug, serde::Deserialize, Clone)]
pub struct Settings {
pub application: ApplicationSettings,
pub debug: bool,
pub frontend_url: String,
pub rate_limit: RateLimitSettings,
pub modbus: ModbusSettings, // New field
}
```
```yaml
# settings/base.yaml
modbus:
host: "192.168.1.100"
port: 502
slave_id: 1
timeout_seconds: 3
```
---
## Summary
### Key Takeaways
1. **tokio-modbus 0.17.0 ** : Excellent choice, use trait abstraction for testability
2. **HTTP Polling ** : Maintain spec decision, simpler and adequate for scale
3. **Hexagonal Architecture ** : Add domain/application layers following existing patterns
4. **Type-Driven Development ** : Apply newtype pattern (RelayId, RelayState)
5. **Testing ** : Use mockall with async-trait for >90% coverage without hardware
### Next Steps
1. **Clarifying Questions ** : Resolve ambiguities in requirements
2. **Architecture Design ** : Create multiple implementation approaches
3. **Final Plan ** : Select approach and create detailed implementation plan
4. **Implementation ** : Follow TDD workflow with types-first design
---
**End of Research Document**