Real-time features in HLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Architecture

intermediate

Designing a scalable chat system with real-time messaging

You are tasked with designing a chat system that supports real-time messaging between millions of users. Which architectural component is essential to ensure messages are delivered instantly and reliably?

A A batch processing system to send messages every few minutes

B A relational database to store all messages synchronously

C A message broker or pub/sub system to handle message distribution

D A static file server to serve chat logs

💡 Hint

Think about how messages can be pushed to many users instantly without delay.

A message broker or pub/sub system allows real-time distribution of messages to connected clients, ensuring low latency and scalability. Databases and batch processing are too slow for instant delivery, and static file servers cannot push updates.

❓ scaling

intermediate

Scaling WebSocket connections for real-time updates

Your application uses WebSocket connections to push real-time updates to users. As user count grows to millions, what is the best approach to scale WebSocket servers?

A Distribute connections across multiple servers with a load balancer and share state via a centralized message broker

B Use a single powerful server to handle all WebSocket connections

C Switch to HTTP polling to reduce server load

D Store all WebSocket messages in a database before sending

💡 Hint

Consider how to handle many simultaneous connections and keep clients updated consistently.

Scaling WebSocket connections requires multiple servers behind a load balancer. A centralized message broker helps synchronize messages across servers so clients receive consistent updates. A single server cannot handle millions of connections, polling is inefficient, and databases add latency.

❓ tradeoff

advanced

Choosing between WebSocket and Server-Sent Events (SSE)

You need to implement a real-time notification system for a web app. Which tradeoff is true when choosing WebSocket over SSE?

A SSE supports binary data natively, WebSocket only supports text

B WebSocket supports full-duplex communication, allowing client and server to send messages independently, while SSE is unidirectional from server to client

C WebSocket connections are stateless, SSE connections maintain state

D SSE requires a separate protocol, WebSocket uses standard HTTP

💡 Hint

Think about the direction and type of communication each protocol supports.

WebSocket allows two-way communication (full-duplex), so both client and server can send messages anytime. SSE only allows server-to-client messages (unidirectional). WebSocket supports binary and text, SSE supports only text. Both use HTTP for connection setup.

🧠 Conceptual

advanced

Ensuring message ordering in a distributed real-time system

In a distributed real-time messaging system, what is the best approach to guarantee that messages are delivered to clients in the exact order they were sent?

A Use multiple message brokers without synchronization

B Send messages in parallel from different servers to reduce latency

C Allow each server to send messages independently without coordination

D Use a centralized message queue that preserves message order and assign sequence numbers to messages

💡 Hint

Think about how to keep track of message sequence across distributed components.

A centralized message queue that preserves order and sequence numbers ensures clients receive messages in the correct order. Independent servers or unsynchronized brokers can cause out-of-order delivery. Parallel sending without coordination risks message reordering.

❓ estimation

expert

Estimating server capacity for a real-time stock ticker system

You are designing a real-time stock ticker system that pushes price updates to 5 million users. Each user receives 10 updates per second. Each update message is approximately 500 bytes. Estimate the total outgoing bandwidth required per second.

A Approximately 25 gigabytes per second

B Approximately 2.5 gigabytes per second

C Approximately 250 megabytes per second

D Approximately 50 gigabytes per second

💡 Hint

Calculate total messages per second and multiply by message size, then convert bytes to gigabytes.

Total messages per second = 5,000,000 users * 10 updates = 50,000,000 messages/sec. Total bytes per second = 50,000,000 * 500 = 25,000,000,000 bytes/sec = 25 GB/sec.

Practice

1. Which protocol is commonly used to enable real-time communication in web applications?

easy

A. SMTP

B. HTTP/1.1

C. WebSocket

D. FTP

Solution

1. Step 1: Understand real-time communication needs

   Real-time apps require a protocol that supports two-way, instant data exchange.

2. Step 2: Identify protocol features

   WebSocket allows full-duplex communication over a single connection, unlike HTTP/1.1 which is request-response only.

3. Final Answer:

   WebSocket -> Option C

4. Quick Check:

   Real-time = WebSocket [OK]

Hint: Real-time needs two-way instant data flow: WebSocket fits best [OK]

Common Mistakes:

• Confusing HTTP with WebSocket for real-time
• Choosing FTP or SMTP which are not real-time protocols
• Thinking HTTP/2 is the same as WebSocket

2. Which component in a real-time system is responsible for distributing messages from producers to consumers?

easy

A. Broker

B. Producer

C. Consumer

D. Database

Solution

1. Step 1: Define roles in real-time messaging

   Producers send data, consumers receive data, and brokers route messages between them.

2. Step 2: Identify the distributor

   The broker acts as the middleman ensuring messages reach the right consumers.

3. Final Answer:

   Broker -> Option A

4. Quick Check:

   Message routing = Broker [OK]

Hint: Broker connects producers and consumers by routing messages [OK]

Common Mistakes:

• Confusing producer as distributor
• Thinking consumer sends messages
• Assuming database handles message routing

3. Consider a chat app using WebSocket. If the server receives a message from User A and broadcasts it to 100 connected users, what is the main bottleneck to scale this real-time feature?

medium

A. User A's device speed

B. Client browser rendering speed

C. Database read latency

D. Server CPU and network bandwidth

Solution

1. Step 1: Analyze message flow in real-time chat

   The server receives and then sends the message to all connected users, requiring CPU and network resources.

2. Step 2: Identify bottleneck

   Server CPU handles message processing; network bandwidth handles sending to many users simultaneously.

3. Final Answer:

   Server CPU and network bandwidth -> Option D

4. Quick Check:

   Scaling real-time = Server resources [OK]

Hint: Server resources limit broadcast scale, not client or DB speed [OK]

Common Mistakes:

• Blaming client device speed for server load
• Focusing on database latency which is less critical here
• Ignoring network bandwidth limits

4. A real-time notification system uses MQTT but users report delayed messages. Which is the most likely cause?

medium

A. Clients are using WebSocket instead of MQTT

B. Broker is overloaded and dropping messages

C. Messages are too small to send quickly

D. Users have disabled notifications on their devices

Solution

1. Step 1: Understand MQTT broker role

   The broker routes messages; if overloaded, it queues or drops messages causing delays.

2. Step 2: Evaluate other options

   Clients using WebSocket instead of MQTT would cause connection issues, not delays; small messages send faster; disabled notifications affect display, not delivery.

3. Final Answer:

   Broker is overloaded and dropping messages -> Option B

4. Quick Check:

   Delays usually mean broker overload [OK]

Hint: Delays often mean broker overload, not client protocol mismatch [OK]

Common Mistakes:

• Blaming client protocol mismatch for delays
• Assuming small messages cause delays
• Ignoring broker capacity limits

5. You are designing a real-time stock price update system for millions of users. Which approach best ensures scalability and low latency?

hard

A. Use a distributed message broker cluster with topic partitions and WebSocket connections

B. Store all prices in a single database and poll clients every second

C. Send updates via email to all users when prices change

D. Use HTTP long polling from clients to server for updates

Solution

1. Step 1: Understand scalability needs

   Millions of users require distributed systems to handle load and maintain low latency.

2. Step 2: Evaluate options

   Distributed brokers with topic partitions allow parallel processing; WebSocket supports instant push updates. Polling and email cause delays and high load.

3. Final Answer:

   Use a distributed message broker cluster with topic partitions and WebSocket connections -> Option A

4. Quick Check:

   Scalable real-time = Distributed broker + WebSocket [OK]

Hint: Distributed brokers + WebSocket scale best for millions [OK]

Common Mistakes:

• Choosing polling which wastes resources and adds latency
• Using email which is not real-time
• Relying on a single database causing bottlenecks