System Design FAQ: Top Questions

A Real-Time Analytics Dashboard displays up-to-date insights from streaming data (e.g., user events, metrics, logs). It is widely used in marketing, e-commerce, monitoring, and operational tools.

📋 Functional Requirements

• Ingest high-velocity event streams (clicks, conversions, API hits)
• Pre-aggregate metrics by time window and dimension
• Support filtering by time, user cohort, device, geo
• Real-time visualization with low-latency updates

📦 Non-Functional Requirements

• Sub-second latency for recent data
• Durability and late-arriving event handling
• Backpressure control and partitioning

🏗️ Architecture Overview

• Event Producer: Frontend or API emits events
• Streaming Broker: Kafka or Kinesis buffers data
• Stream Processor: Flink, Spark Streaming, or Kafka Streams
• Aggregation Store: Redis, ClickHouse, Druid, or Pinot
• Dashboard: React + WebSocket or polling API

🧪 Kafka + Flink Example

// Flink: Aggregate clicks by minute
DataStream events = ...
events
  .keyBy(event -> event.userId)
  .window(TumblingEventTimeWindows.of(Time.minutes(1)))
  .aggregate(new CountAggregator())
  .addSink(new RedisSink<>(...));
        

📊 ClickHouse Table Schema

CREATE TABLE pageviews (
  timestamp DateTime,
  user_id String,
  country String,
  page String
) ENGINE = MergeTree()
PARTITION BY toDate(timestamp)
ORDER BY (timestamp, user_id);
        

📈 Real-Time WebSocket Feed (Node.js)

const WebSocket = require("ws");
const wss = new WebSocket.Server({ port: 8080 });

setInterval(() => {
  const update = { metric: "visits", count: Math.random() * 100 };
  wss.clients.forEach(client => client.send(JSON.stringify(update)));
}, 1000);
        

📌 Dashboard Features

• Time filters (last 5m, 1h, 24h)
• Custom charts (line, bar, heatmaps)
• Segment filters (device, campaign, referrer)

🧰 Tools & Stack

• Stream Broker: Kafka, Pulsar, Kinesis
• Processing: Flink, Kafka Streams, Materialize
• Storage: ClickHouse, Pinot, RedisTimeSeries
• Frontend: React, D3.js, Highcharts

📌 Final Insight

Real-time dashboards combine streaming pipelines with time-series storage and reactive UIs. Minimize chart latency using push mechanisms like WebSockets and roll up metrics at multiple granularities for responsive querying.