WebSocket for real-time communication in HLD - Architecture Diagram

System Overview - WebSocket for real-time communication

This system enables real-time, two-way communication between users and servers using WebSocket technology. It supports instant message delivery, low latency updates, and scalable connections for many users simultaneously.

Architecture Diagram

User
  |
  v
Load Balancer
  |
  v
WebSocket Server Cluster
  |
  +----------------+
  |                |
Cache (Redis)   Message Broker (Kafka)
  |                |
  v                v
Database         Notification Service

Components

User

client

Initiates WebSocket connection and sends/receives real-time messages

Load Balancer

load_balancer

Distributes incoming WebSocket connection requests evenly across servers

WebSocket Server Cluster

service

Maintains WebSocket connections, handles message routing and session management

Cache (Redis)

cache

Stores frequently accessed session data and recent messages for quick retrieval

Message Broker (Kafka)

message_queue

Manages asynchronous message delivery and event streaming between services

Database

database

Persists user data, message history, and connection metadata

Notification Service

service

Sends push notifications or alerts based on real-time events

Request Flow - 8 Hops

User → Load Balancer

Load Balancer → WebSocket Server Cluster

WebSocket Server Cluster → Cache (Redis)

User → WebSocket Server Cluster

WebSocket Server Cluster → Message Broker (Kafka)

Message Broker (Kafka) → Notification Service

Notification Service → User

WebSocket Server Cluster → Database

Failure Scenario

Component Fails:Load Balancer

Impact:All incoming WebSocket connection requests fail, causing service unavailability for new connections.

Mitigation:Use multiple load balancers with failover and health checks to ensure high availability.

Architecture Quiz - 3 Questions

Which component handles the initial WebSocket connection request from the user?

A WebSocket Server Cluster

B Load Balancer

C Message Broker

D Cache

Design Principle

This architecture uses a load balancer to distribute WebSocket connections, caches to speed up session data access, and a message broker to handle asynchronous event processing. This design supports scalable, low-latency real-time communication with fault tolerance and separation of concerns.

Practice

1. What is the primary advantage of using WebSocket over traditional HTTP for real-time communication?

easy

A. It requires no server-side support to function.

B. It uses less bandwidth by compressing all messages automatically.

C. It keeps a persistent connection open for instant two-way data exchange.

D. It guarantees message delivery order without any additional setup.

Solution

1. Step 1: Understand WebSocket connection behavior

   WebSocket establishes a persistent connection between client and server, unlike HTTP which opens and closes connections per request.

2. Step 2: Identify the key benefit for real-time apps

   This persistent connection allows instant two-way communication, ideal for real-time updates.

3. Final Answer:

   It keeps a persistent connection open for instant two-way data exchange. -> Option C

4. Quick Check:

   Persistent connection = Instant two-way communication [OK]

Hint: WebSocket keeps connection open for fast two-way data [OK]

Common Mistakes:

• Confusing WebSocket with HTTP polling
• Assuming WebSocket compresses all messages automatically
• Thinking WebSocket works without server support

2. Which of the following is the correct syntax to open a WebSocket connection in JavaScript?

easy

A. const ws = new WebSocket('http://example.com/socket');

B. const ws = new WebSocket('ws://example.com/socket');

C. const ws = WebSocket.connect('ws://example.com/socket');

D. const ws = WebSocket.open('http://example.com/socket');

Solution

1. Step 1: Recall WebSocket URL scheme

   WebSocket URLs start with ws:// or wss:// for secure connections, not http://.

2. Step 2: Identify correct constructor usage

   The WebSocket object is created with new WebSocket(url), no .connect() or .open() methods exist.

3. Final Answer:

   const ws = new WebSocket('ws://example.com/socket'); -> Option B

4. Quick Check:

   WebSocket uses ws:// + new WebSocket() [OK]

Hint: WebSocket URLs start with ws:// or wss:// [OK]

Common Mistakes:

• Using http:// instead of ws://
• Calling non-existent connect() or open() methods
• Omitting the new keyword

3. Consider this simplified server-side pseudocode handling WebSocket messages:

onMessage(client, message) {
  broadcastToAllClients(message);
}

What will happen if 1000 clients send messages simultaneously?

medium

A. Server may become overwhelmed, causing message delays or dropped connections.

B. All messages will be broadcasted instantly to all clients without delay.

C. Only the first client's message will be broadcasted; others ignored.

D. Clients will automatically queue messages on their side until server is free.

Solution

1. Step 1: Analyze server load with simultaneous messages

   When many clients send messages at once, the server must process and broadcast each, increasing CPU and network load.

2. Step 2: Understand server resource limits

   Without scaling or message queuing, the server can get overwhelmed, causing delays or dropped connections.

3. Final Answer:

   Server may become overwhelmed, causing message delays or dropped connections. -> Option A

4. Quick Check:

   High load without scaling = delays/drops [OK]

Hint: High simultaneous messages can overload server without scaling [OK]

Common Mistakes:

• Assuming instant broadcast without delay
• Thinking clients queue messages automatically
• Believing only first message is processed

4. A developer wrote this WebSocket server snippet:

ws.on('message', (msg) => {
  ws.send(msg);
});

Why might this cause problems in a multi-client chat application?

medium

A. It closes the connection after sending the message.

B. It broadcasts the message to all clients, causing duplicates.

C. It causes syntax errors due to incorrect event name.

D. It only sends the message back to the sender, not to other clients.

Solution

1. Step 1: Understand the code behavior

   The code listens for a message from a client and sends the same message back only to that client (ws.send(msg)).

2. Step 2: Identify issue in multi-client context

   Other connected clients do not receive the message, so chat messages are not broadcasted properly.

3. Final Answer:

   It only sends the message back to the sender, not to other clients. -> Option D

4. Quick Check:

   ws.send(msg) sends only to sender [OK]

Hint: ws.send(msg) sends only to sender, not all clients [OK]

Common Mistakes:

• Assuming ws.send broadcasts to all clients
• Thinking event name 'message' is incorrect
• Believing connection closes after send

5. You are designing a scalable chat app using WebSocket. Which architectural component helps efficiently distribute messages to thousands of clients without overloading the main server?

hard

A. A message broker (e.g., Redis Pub/Sub) between WebSocket servers and clients.

B. A single powerful WebSocket server handling all connections directly.

C. Using HTTP long polling instead of WebSocket for all clients.

D. Storing all messages in a database before sending to clients.

Solution

1. Step 1: Understand scaling challenges with many clients

   A single server can become a bottleneck when handling thousands of WebSocket connections and broadcasting messages.

2. Step 2: Identify role of message broker

   A message broker like Redis Pub/Sub can distribute messages efficiently across multiple WebSocket servers, balancing load and improving scalability.

3. Final Answer:

   A message broker (e.g., Redis Pub/Sub) between WebSocket servers and clients. -> Option A

4. Quick Check:

   Message broker enables scalable message distribution [OK]

Hint: Use message broker to scale WebSocket message distribution [OK]

Common Mistakes:

• Relying on a single server for all connections
• Switching to HTTP long polling loses real-time benefits
• Storing messages in DB adds latency, not scaling