数据分析

Realtime Dashboard

试用

Complete guide to building real-time dashboards with streaming data, WebSocket/SSE, and live updates. Orchestrates dual-stream architecture, React hooks, and data visualization. Use when building trading dashboards, monitoring UIs, or live analytics. Triggers on realtime dashboard, live data, streaming dashboard, trading UI, monitoring.

它能做什么

Complete guide to building real-time dashboards with streaming data.

技能文档

Real-Time Dashboard (Meta-Skill)

Complete guide to building real-time dashboards with streaming data.

Installation

OpenClaw / Moltbot / Clawbot

npx clawhub@latest install realtime-dashboard

When to Use

  • Building trading or financial dashboards
  • Monitoring and analytics UIs
  • Any dashboard needing live data updates
  • Systems with server-to-client push requirements

Architecture Overview

┌─────────────────────────────────────────────────────────────┐
│                    Data Sources                              │
│  APIs, Databases, Message Queues                            │
└─────────────────────────────────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────┐
│                    Backend Services                          │
├─────────────────────────────────────────────────────────────┤
│  Kafka (durable)     │     Redis Pub/Sub (real-time)       │
│  See: dual-stream-architecture                               │
└─────────────────────────────────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────┐
│                    WebSocket/SSE Gateway                     │
│  See: websocket-hub-patterns                                 │
└─────────────────────────────────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────┐
│                    React Application                         │
├─────────────────────────────────────────────────────────────┤
│  Real-time Hooks          │  Data Visualization             │
│  See: realtime-react-hooks│  See: financial-data-visualization
├─────────────────────────────────────────────────────────────┤
│  Animated Displays        │  Connection Handling            │
│  See: animated-financial  │  See: resilient-connections     │
└─────────────────────────────────────────────────────────────┘

Implementation Steps

Step 1: Event Publishing

Set up dual-stream publishing for durability + real-time.

Read: ai/skills/realtime/dual-stream-architecture

func (p *DualPublisher) Publish(ctx context.Context, event Event) error {
    // 1. Kafka: Must succeed (durable)
    err := p.kafka.WriteMessages(ctx, kafka.Message{...})
    if err != nil {
        return err
    }

    // 2. Redis: Best-effort (real-time)
    p.publishToRedis(ctx, event)
    return nil
}

Step 2: WebSocket Gateway

Create horizontally-scalable WebSocket connections.

Read: ai/skills/realtime/websocket-hub-patterns

type Hub struct {
    connections   map[*Connection]bool
    subscriptions map[string]map[*Connection]bool
    redisClient   *redis.Client
}

// Lazy Redis subscriptions
func (h *Hub) subscribeToChannel(conn *Connection, channel string) {
    // Only subscribe to Redis on first local subscriber
}

Step 3: React Hooks

Connect React to real-time data.

Read: ai/skills/realtime/realtime-react-hooks

const { data, isConnected } = useSSE({ 
  url: '/api/events',
  onMessage: (data) => updateState(data),
});

// Or with SWR integration
const { data } = useRealtimeData('metrics', fetchMetrics);

Step 4: Resilient Connections

Handle connection failures gracefully.

Read: ai/skills/realtime/resilient-connections

const { isConnected, send } = useWebSocket({
  url: 'wss://api/ws',
  reconnect: true,
  maxRetries: 5,
  onMessage: handleMessage,
});

Step 5: Data Visualization

Build dark-themed financial charts.

Read: ai/skills/design-systems/financial-data-visualization

= 0} 
/>

Step 6: Animated Displays

Add smooth number animations.

Read: ai/skills/design-systems/animated-financial-display




Component Skills Reference

SkillPurpose
dual-stream-architectureKafka + Redis publishing
websocket-hub-patternsScalable WebSocket server
realtime-react-hooksSSE/WebSocket React hooks
resilient-connectionsRetry, circuit breaker
financial-data-visualizationChart theming
animated-financial-displayNumber animations

Key Patterns

Streaming Over Blocking

Never wait for all data. Show immediately, improve progressively:

Phase 1: Initial data + hints      → Immediate display
Phase 2: Background refinement     → Prices update in place
Phase 3: Historical data           → Charts populate

Additive-Only Updates

Never zero out data when refinement fails. Only update when you have better data.

Connection Status

Always show users their connection state:


NEVER Do

  • Never block on data fetching — Show immediately, refine progressively
  • Never skip connection status indicators — Users need to know they're live
  • Never use polling when SSE/WebSocket available — Real-time means push, not pull
  • Never forget graceful degradation — System should work (degraded) when connection lost
  • Never zero out data on refinement failure — Only update when you have better data
  • Never reconnect without exponential backoff — Prevents thundering herd
  • Never skip Redis Pub/Sub failure handling — Redis is best-effort; log and continue
  • Never send full payloads over Redis — Send IDs only, clients fetch from API
  • Never share WebSocket pubsub across channels — Each channel needs own subscription
  • Never forget ping/pong on WebSocket — Load balancers close "idle" connections

Checklist

  • Set up dual-stream publishing (Kafka + Redis)
  • Create WebSocket/SSE gateway
  • Implement React hooks for real-time data
  • Add reconnection with exponential backoff
  • Build dark-themed chart components
  • Add animated number displays
  • Show connection status to users
  • Handle errors gracefully

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