Popular System Design Interview Questions You Should Know (2023) - IQCode

An Introduction to System Design

System design is the process of creating and developing systems that meet a company's objectives and expectations by identifying the modules, architecture, components, interfaces, and data for a specific system based on requirements. It involves analyzing the system's architecture, identifying APIs, design patterns, and integrating them. System design is not about coding but about designing your system appropriately. If your system is designed properly, it can handle the architectural load, reduce expenses, and provide a better experience for users.

System design concepts are vital in IT interviews, and companies like Facebook, Amazon, and Google frequently ask questions related to scalability, load balancing, caching, among others. In this article, we will discuss some frequently asked interview questions on system design.


// No code to optimize

Differences between Horizontal and Vertical Scaling

When it comes to scaling, there are two main approaches – horizontal scaling and vertical scaling. Horizontal scaling involves increasing the number of machines or nodes in the network to distribute the workload among them. Vertical scaling, on the other hand, means increasing the capacity of existing machines by upgrading the hardware components like RAM, CPU, or adding more hard disks.

The main difference between the two is that horizontal scaling allows for potentially unlimited scaling by adding more machines to the network, while vertical scaling has a practical limit as hardware components can only be upgraded so much. Additionally, horizontal scaling can provide better fault-tolerance as failures in one machine can be isolated from the rest of the network.

Both horizontal and vertical scaling have their advantages and disadvantages, and the choice between them depends on the specific use case and requirements of the system.

Understanding Load Balancing in System Design

Load balancing refers to the distribution of workloads across multiple servers, which helps to optimize and enhance the overall performance and efficiency of a system. In simple terms, load balancing involves spreading out incoming traffic and requests across multiple servers to prevent any one server from becoming overburdened with too much traffic, which can cause the system to slow down or even crash.

Load balancing is essential in system design because it helps to ensure that a system can handle large amounts of traffic and requests without experiencing performance issues. By distributing the workload across multiple servers, load balancing helps to prevent any one server from becoming overwhelmed and thereby prevents downtime or other system failures.

Overall, load balancing is a critical component of system design, particularly in applications that experience high levels of traffic and require constant availability and optimal performance. With load balancing, designers can ensure that their systems are reliable, scalable, and can handle large volumes of traffic with ease.

Understanding Latency, Throughput, and Availability in a System

Latency refers to the delay between a request and the response received. It is the time taken for a system to process a request and provide a response. Low latency is desirable for systems that require real-time responses, such as online gaming or financial trading.

Throughput is the rate at which a system can process requests. It is the number of requests that can be handled by the system in a given time period. High throughput is desirable for systems that handle a large number of requests, such as e-commerce websites or social media platforms.

Availability refers to the percentage of time a system is operational and accessible to users. It is the measure of the system's reliability. High availability is crucial for systems that require continuous operation, such as healthcare systems or financial services. A system is considered highly available if it has an uptime of 99.999%, which means it is unavailable for less than 5.26 minutes per year.

Differences between NoSQL Databases and SQL Databases

NoSQL databases differ from SQL databases in several ways. Firstly, NoSQL databases are non-relational, while SQL databases are relational. This means that NoSQL databases do not use tables to store data and do not enforce a specific schema, which allows for more flexibility and scalability.

Secondly, NoSQL databases are horizontally scalable, which means that they can handle large amounts of data across multiple servers. SQL databases, on the other hand, are vertically scalable and can only handle increased traffic by upgrading the hardware of a single server.

Lastly, NoSQL databases are designed for distributed data systems, while SQL databases are designed for centralized data systems. This means that NoSQL databases are better suited for big data applications and real-time web applications, while SQL databases are better suited for transactional systems and traditional applications.

Understanding the Differences between Sharding and Partitioning

In the context of databases, sharding and partitioning are two distinct data management techniques that serve similar purposes. Sharding is the process of dividing a database into smaller, more easily managed pieces called shards, which are distributed across multiple servers. On the other hand, partitioning involves dividing a database into smaller logical segments called partitions, which are organized based on predefined rules, such as the range of data values or the hashing algorithm used.

While both techniques aim at improving database performance, sharding tends to be preferred for large, distributed databases with high write loads and read operations that do not require cross-shard queries. Partitioning, on the other hand, is better suited for simpler databases with lower data volumes and fewer transactions, or for scaling specific tables or indexes within a database.

It's worth noting that sharding and partitioning are not mutually exclusive, and some databases may use a combination of both techniques for optimal performance and data management.

Understanding the Relationship between Performance and Scalability

Performance and scalability are two key considerations when it comes to designing and implementing software applications. While they are related, they are not interchangeable terms.

Performance refers to the speed and responsiveness of an application. It is a measure of how well an application can execute a given task within a certain amount of time.

Scalability, on the other hand, refers to an application's ability to handle increasing amounts of work or data without sacrificing performance. In other words, a scalable application can handle an increasing amount of traffic, workload, or data without experiencing a drop in performance.

Performance and scalability are related because an application's ability to scale effectively can impact its overall performance. A poorly designed architecture that does not take scalability into account can result in poor performance as the application attempts to handle increased traffic or workloads.

Therefore, it is important to design and implement applications with scalability in mind, to ensure they can handle future growth and traffic. This includes appropriately using caching techniques, employing load balancing and leveraging cloud infrastructure when necessary.

Understanding Caching and Cache Update Strategies

Caching is the process of storing frequently accessed data in memory to improve the performance of an application. When data is cached, subsequent requests for the same data can be served faster because it is already stored in memory.

There are various cache update strategies available in caching. These strategies determine how and when cached data is updated and include:

  • Time-based expiration: Cache data is invalidated after a set amount of time to ensure that it remains up-to-date.
  • Event-based expiration: Cache data is invalidated when certain events occur that signify the data is no longer valid.
  • Write-through caching: Data is written to both the cache and the underlying data store, ensuring that the cache always contains up-to-date data.
  • Write-behind caching: Data is written only to the cache, and is later written to the underlying data store in batches to reduce the number of write operations.

Choosing the right cache update strategy depends on the specific use case and the requirements of the application. By implementing caching and the appropriate cache update strategy, applications can significantly improve their performance and responsiveness.

// Example implementation of write-through caching in Java using the Caffeine cache library

// Create a cache instance with a maximum size of 100 and a write-through adapter
Cache<String, Object> cache = Caffeine.newBuilder()
    .writer(new CacheWriter<String, Object>() {
        public void write(String key, Object value) {
            // Write the data to the underlying data store
            dataStore.put(key, value);

// Get the data from the cache (or the underlying data store if it's not in the cache)
Object data = cache.get(key, k -> {
    // Compute the value if it doesn't exist in the cache
    return computeValue(k);

Consistency Patterns in System Design

In system design, there are various consistency patterns available to maintain the integrity and accuracy of data. Some of these patterns include:

1. Strong Consistency: In this pattern, every transaction must update all copies of data before completing. It ensures that all nodes always have the same version of data.

2. Eventual Consistency: This pattern guarantees that updates will be eventually propagated to all nodes, but not immediately. Users may see different versions of the data at different times.

3. Read-your-write Consistency: This pattern ensures that any update made by a user will be immediately visible to them when they perform a read operation.

4. Monotonic Reads Consistency: This pattern ensures that users will never see old or stale data.

5. Monotonic Writes Consistency: This pattern ensures that updates are applied in the order they were received, and no two updates conflict with each other.

Each consistency pattern has its own trade-offs and must be carefully considered when designing a system.

Understanding Content Delivery Network (CDN)

A Content Delivery Network (CDN) refers to a distributed network of servers that work together to provide fast delivery of web content to end-users. This network of servers is strategically positioned in geographic locations to help reduce latency, minimize delays, and increase the speed of delivery for website content such as HTML pages, images, videos, and other digital assets. By using CDN, website owners can deliver content to their users quickly, reliably, and with high performance regardless of their location.

Understanding Leader Election

Leader Election is the process of selecting a node among a group of nodes to act as a leader. In a distributed system, multiple nodes work together to accomplish some task, and it is crucial to have one leader identified to coordinate the activities of all nodes. The leader is responsible for making important decisions, assigning tasks to other nodes, and ensuring the overall progress of the system. The process of leader election is usually performed automatically when the system starts up or when a leader is no longer functional. Leader election algorithms can vary depending on the requirements of the system and the characteristics of the nodes involved.

How to Answer System Design Interview Questions

In a system design interview, you should approach the problem by breaking it down into smaller components, identifying the constraints, and coming up with a scalable solution. It's also important to consider trade-offs and understand the impact of your design decisions on system performance, reliability, and cost.

When presenting your solution, use clear and concise language, draw diagrams or charts if necessary, and ask for feedback or clarification throughout the process. Don't be afraid to take a step back and consider alternative solutions or modifications based on feedback.

Overall, the key to success in a system design interview is to approach the problem systematically, demonstrate a solid understanding of design principles, and communicate your thought process effectively.

Design Issues in Distributed Systems

Distributed systems are complex systems made up of multiple interconnected processors that communicate and coordinate with each other to perform a task. However, designing a distributed system comes with its own set of challenges and issues that must be taken into consideration. Some of the design issues in distributed systems are:

1. Communication: Ensuring that communication between nodes is reliable, as well as efficient and fast.

2. Consistency: Maintaining consistency between data stored across multiple nodes is crucial and requires careful attention.

3. Fault-tolerance: The system should be designed to handle failures of individual components, and ensure that the system as a whole continues to function in the event of a component failure.

4. Security: Security is crucial in a distributed system, as it is vulnerable to various types of attacks.

5. Scalability: The system should be designed to accommodate additional nodes or components as the requirements increase.

6. Performance: The system should be able to perform well even under heavy load, and should be optimized for speed and efficiency.

Addressing these issues is crucial to designing a distributed system that is robust, reliable, and able to perform its intended functions effectively.

System Design Interview Questions for Experienced:

//This program implements a design for a global chat service similar to WhatsApp or Facebook Messenger

class ChatService { //list of users and their corresponding chat rooms Map> userMap;

//list of chat rooms List chatRooms;

//method to add a new user public void addUser(User user) { if(!userMap.containsKey(user)) { userMap.put(user, new ArrayList()); } }

//method to create a new chat room public void createChatRoom(ChatRoom chatRoom) { chatRooms.add(chatRoom); }

//method to add a user to a chat room public void addUserToChatRoom(User user, ChatRoom chatRoom) { if(userMap.containsKey(user) && chatRooms.contains(chatRoom)) { List rooms = userMap.get(user); rooms.add(chatRoom); userMap.put(user, rooms); } }

//method to send a message in a chat room public void sendMessage(User user, ChatRoom chatRoom, String message) { if(userMap.containsKey(user) && chatRooms.contains(chatRoom)) { List rooms = userMap.get(user); if(rooms.contains(chatRoom)) { chatRoom.addMessage(user, message); } } } }

class User { //user name String name;

public User(String name) { this.name = name; }

public String getName() { return name; } }

class ChatRoom { //list of users in the chat room List users;

//list of messages in the chat room List messages;

public ChatRoom() { users = new ArrayList(); messages = new ArrayList(); }

//method to add a new user to the chat room public void addUser(User user) { if(!users.contains(user)) { users.add(user); } }

//method to add a message to the chat room public void addMessage(User user, String message) { String formattedMessage = user.getName() + " : " + message; messages.add(formattedMessage); } }

This implementation provides a basic framework for a global chat service. Users can be added and placed into chat rooms. Messages can be sent within a chat room. This code can be expanded upon to include additional functionality such as message encryption, presence detection, and notification services.

Designing a URL Shortening Service

URL shortening service like TinyURL and Bit.ly are very popular services that help to reduce the length of long URLs. Below are the steps to design a URL shortening service:

  1. Generating a Shortened URL: When a long URL is entered into the system, the system should generate a unique shortened URL which will redirect to the original long URL.

  2. Storing the URLs: Once a URL is entered in the system and a shortened URL is generated, the system should store both the original URL and the shortened URL. This could be done by using a database. This would allow for easy retrieval of the original URL when given the shortened URL.

  3. Redirecting to the Original URL: When a user clicks on the shortened URL, they should be redirected to the original URL. This can be achieved by setting up a redirect on the shortened URL to point to the original long URL in the database.

  4. Analytics: A good URL Shortener service should also provide analytics for each shortened URL. Analytics could include the number of clicks on a link, the location of the users who have clicked on the link, and the devices used to click on the link. This could be helpful in determining the effectiveness of a particular marketing campaign.

In order to design a scalable and efficient URL shortening service, one could make use of load balancers, caching, and asynchronous processing of requests. Also, the service should efficiently handle any exceptions and unexpected errors.

// Sample code to generate shortened URL
import hashlib

class URLShortener:
    def __init__(self):
        self.url_map = {}

    def generate_short_url(self, long_url: str) -> str:
        # Generate unique shortened URL
        hashed = hashlib.md5(long_url.encode())
        short_url = hashed.hexdigest()[:8]

        # Store the original and the shortened URL in a map
        self.url_map[short_url] = long_url

        return short_url

    def redirect_to_long_url(self, short_url: str) -> str:
        # Retrieve the original long URL
        long_url = self.url_map.get(short_url)

        return long_url

Designing a Forum System like Quora, Reddit or HackerNews

To design a forum-like system similar to Quora, Reddit, or HackerNews, we need to consider several aspects of the system design.

First, we need to define the user roles and permissions. The system will typically have three user roles: administrators, moderators, and regular users. Administrators will have complete control over the system, whereas moderators will have the ability to manage and moderate user-generated content. Regular users will be able to create and interact with content but will have limited permissions.

Next, we need to determine the functionalities that the system will provide to the users. This includes the ability to create new posts, comment on existing posts, upvote or downvote posts, search for content, and follow other users. The system should also include features to prevent spam and ensure user security.

To ensure scalability and performance, we can use a distributed architecture with multiple servers and a caching mechanism to reduce the load on the database. We can also incorporate technologies such as Elasticsearch for efficient search operations.

Overall, designing a forum-like system requires careful consideration of user roles, system functionalities, and technical requirements to ensure a stable and efficient platform.

Designing Facebook's Newsfeed System

To design Facebook's newsfeed system, we need to consider several things, such as:

  • The user's activity level
  • The type of content posted
  • The user's interaction with the content
  • The time of posting
  • The user's preferences

We can start with a simple algorithm that ranks posts based on the above factors. To determine which posts to show on the user's newsfeed, we can assign a score to each post based on its relevance to the user. The score can be calculated using a weighted average of various factors such as the number of comments, likes, shares, and the time of posting.

To make the Newsfeed more personal and user-friendly, we can also use machine learning algorithms to predict the content that the user will be interested in. These algorithms can analyze the user's past behavior, such as the pages they follow, the posts they like, and the comments they make, to determine their preferences.

In addition, we can also allow the user to customize their Newsfeed by giving them the option to follow or unfollow specific pages or people. This will give the user more control over the content they see on their Newsfeed.

Overall, designing Facebook's Newsfeed system is a complex task that requires continuous optimization and improvement. By analyzing user data and feedback, we can create a more personalized and engaging experience for Facebook users.

 //implementation code here

Designing a Parking Lot System


class ParkingLot:
    def __init__(self, name, capacity):
        self.name = name
        self.capacity = capacity
        self.available_spaces = capacity
    def is_full(self):
        return self.available_spaces == 0
    def is_empty(self):
        return self.available_spaces == self.capacity
    def park_vehicle(self):
        if self.is_full():
            print("Sorry, the parking lot is full")
            return False
        self.available_spaces -= 1
        print("Vehicle parked successfully")
        return True
    def remove_vehicle(self):
        if self.is_empty():
            print("The parking lot is already empty")
            return False
        self.available_spaces += 1
        print("Vehicle removed successfully")
        return True

This ParkingLot class can be used to manage a parking lot system. Upon initialization, it takes in a name and capacity, with available_spaces initially equal to capacity. The is_full and is_empty methods check for the parking lot's capacity status, while the park_vehicle and remove_vehicle methods are used to park and remove a vehicle respectively.

To use the ParkingLot class, create an instance of it and call its methods appropriately, as shown below:

parking_lot = ParkingLot("ABC Parking Lot", 50)
print(parking_lot.is_empty()) # output: True
parking_lot.park_vehicle() # output: Vehicle parked successfully

Note: This is a basic implementation. A more complex parking lot system would require additional features, such as tracking parked vehicles' location, the ability to reserve parking spots, and accepting payments.

Designing a Recommendation System

A recommendation system can be designed by following these steps:

  1. Define the problem and objectives: Identify the purpose of the recommendation system and the business objectives to be achieved.
  2. Understand the data: Determine the types of data required, such as user data, item data, and rating data. Conduct data analysis to identify patterns and relationships between different variables.
  3. Select the recommendation algorithm: Choose the right algorithm based on the type and amount of data available. Popular algorithms include collaborative filtering, content-based filtering, and hybrid filtering.
  4. Develop a prototype: Build a basic recommendation system prototype and test it with a sample dataset. Evaluate its performance by using metrics such as accuracy, coverage, and diversity.
  5. Refine the model: Improve the accuracy and effectiveness of the recommendation system by adjusting the model parameters, identifying and removing outliers, and improving the quality of data and input features.
  6. Deploy the model: Integrate the recommendation system into the target application and evaluate it with real users. Monitor its performance and continue to refine the model over time to improve its effectiveness.

Code: N/A

Design an API Rate Limiter System for GitHub or Firebase Sites

In order to prevent abuse and to ensure the efficient use of resources, APIs often have rate limits. The following is a basic design for an API rate limiter system for GitHub or Firebase sites:

1. Basic Setup

Create a configuration file that includes: - The number of requests allowed per user per hour - A list of user IDs and their current request count for the hour

2. Incoming Requests

When an incoming request is received by the API server, the rate limiter system should check: - If the request is authorized (using API keys, OAuth tokens, etc.) - If the user has exceeded their request limit for the hour

If the user has exceeded their request limit, the rate limiter system should reject the request with a HTTP 429 status code (Too Many Requests) and return an error message. Otherwise, the request should be allowed to proceed.

3. Updating Request Counts

For each successful request, the rate limiter system should update the request count for the user. This can be done using an in-memory cache or a persistent store like a database.

4. Resetting Request Counts

At the end of each hour, the rate limiter system should reset the request count for each user in the configuration file.

Designing Global File Storage and Sharing Services like Google Drive and Dropbox

The design of global file storage and sharing services like Google Drive and Dropbox involves several key considerations.

Firstly, a reliable and scalable infrastructure must be built to ensure that users can access their files from anywhere in the world. This involves setting up a distributed system that can handle high traffic loads and provide quick access to files.

Secondly, security measures must be put in place to protect user data from unauthorized access or cyber attacks. This involves implementing strong encryption protocols and access control mechanisms.

Thirdly, the user interface must be designed to be intuitive and easy to use, allowing users to upload, share and collaborate on files seamlessly. This involves developing a responsive web application or a mobile application that works across multiple platforms.

Lastly, customer support must be available to assist users with any issues they may encounter while using the service. This involves setting up a support team that can provide timely and efficient support to users via email, phone, or chat.

By taking these considerations into account, global file storage and sharing services can be designed to provide a reliable, secure, and user-friendly experience for users around the world. Code

Developing a Type-Ahead Search Engine

In this project, we will be designing a type-ahead search engine service. This search engine will be capable of providing quick search results as the user types in the search query. We will be using HTML, CSS, and JavaScript to build and style the search box and display the results.

//Sample code for fetching search results from API
const searchBox = document.getElementById("search-box");
const searchResults = document.getElementById("search-results");

searchBox.addEventListener("input", function() {
  //Fetch search results from API
    .then(response => response.json())
    .then(data => {
      //Clear previous search results
      searchResults.innerHTML = "";

      //Display new search results
      data.forEach(result => {
        const resultItem = document.createElement("li");
        resultItem.innerText = result;
    .catch(error => {

The above code demonstrates how we can use fetch() API to fetch search results from an API endpoint. We are also using the input event listener to detect changes in the search box input field and automatically fetch new results. We are displaying the results in an unordered list in the HTML document.

By following this approach, we can create an efficient and responsive type-ahead search engine service that can provide quick and accurate results for the users.

Design a Tic-Tac-Toe Game

// Define the game board as a 2D array
let board = [
   ['', '', ''],
   ['', '', ''],
   ['', '', '']

// Define the initial player and an empty winner variable
let currentPlayer = 'X';
let winner = '';

// Function to check if a move is valid
function isValidMove(x, y) {
   if (board[x][y] === '') {
      return true;
   } else {
      return false;

// Function to check if the game has been won
function checkWinner() {
   // Check the rows
   for (let i = 0; i < board.length; i++) {
      if (board[i][0] !== '' && board[i][0] === board[i][1] && board[i][1] === board[i][2]) {
         winner = board[i][0];
         return true; 
   // Check the columns
   for (let j = 0; j < board[0].length; j++) {
      if (board[0][j] !== '' && board[0][j] === board[1][j] && board[1][j] === board[2][j]) {
         winner = board[0][j];
         return true;
   // Check the diagonals
   if (board[0][0] !== '' && board[0][0] === board[1][1] && board[1][1] === board[2][2]) {
      winner = board[0][0];
      return true;
   if (board[0][2] !== '' && board[0][2] === board[1][1] && board[1][1] === board[2][0]) {
      winner = board[0][2];
      return true;
   // If no winner, return false
   return false;

// Function to switch players after a turn
function switchPlayer() {
   if (currentPlayer === 'X') {
      currentPlayer = 'O';
   } else {
      currentPlayer = 'X';

// Function to print the current game board
function printBoard() {
   console.log(board[0][0] + ' | ' + board[0][1] + ' | ' + board[0][2]);
   console.log(board[1][0] + ' | ' + board[1][1] + ' | ' + board[1][2]);
   console.log(board[2][0] + ' | ' + board[2][1] + ' | ' + board[2][2]);

// Function to play the game
function playGame() {
   // Loop through the game until there's a winner or it's a tie
   while (!checkWinner() && !isTie()) {
      // Ask the current player to make a move
      let x = parseInt(prompt("Enter row for " + currentPlayer));
      let y = parseInt(prompt("Enter column for " + currentPlayer));
      // Check if the move is valid
      if (isValidMove(x, y)) {
         // Add the move to the board
         board[x][y] = currentPlayer;
         // Switch players
         // Print the board
      } else {
         // If the move is not valid, ask again
         alert("Invalid move. Please try again.");
   // Once the loop ends, check if there's a winner or it's a tie
   if (checkWinner()) {
      console.log('Game over! ' + winner + ' won!');
   } else if (isTie()) {
      console.log("It's a tie!");

// Function to check if the game is a tie
function isTie() {
   // Get all the cells that are empty
   let emptyCells = 0;
   for (let i = 0; i < board.length; i++) {
      for (let j = 0; j < board[0].length; j++) {
         if (board[i][j] === '') {
   // If there are no empty cells, it's a tie
   if (emptyCells === 0) {
      return true;
   } else {
      return false;

// Call the playGame function to start the game

Designing a Traffic Control System


// Define constants for traffic light colors
const RED = 'red';
const YELLOW = 'yellow';
const GREEN = 'green';

// Define initial traffic light state
let trafficLightState = RED;

// Define function to change the traffic light state
function changeTrafficLightState() {
  if (trafficLightState === RED) {
    trafficLightState = GREEN;
  } else if (trafficLightState === GREEN) {
    trafficLightState = YELLOW;
  } else if (trafficLightState === YELLOW) {
    trafficLightState = RED;

// Define function to display the current traffic light state
function displayTrafficLightState() {
  console.log(`Current traffic light state: ${trafficLightState}`);

// Set the initial state

// Simulate traffic light changes
for (let i = 0; i < 10; i++) {

The above code simulates a traffic control system by defining constants for the traffic light colors and a variable to keep track of the current traffic light state. It also defines functions to change and display the traffic light state. The initial state is set to red and a loop is used to simulate traffic light changes for 10 iterations. Each time the state changes, the new state is displayed in the console.

Designing a Web Crawler

As a programmer, you may need to design a web crawler in order to collect data from the internet efficiently. A web crawler is an automated program that scans and extracts data from websites. Here are a few tips to keep in mind while designing a web crawler:

// Import necessary libraries

import requests
from bs4 import BeautifulSoup
import time

// Define function to crawl web pages

def web_crawler(url_list):
    for url in url_list:
            response = requests.get(url)
            soup = BeautifulSoup(response.text, 'html.parser')
            // Extract the data you need from the webpage using BeautifulSoup
            // Store the data in a file or database
            // Handle any errors that may arise
        // Limit the crawling speed to be respectful of the website you are extracting data from

Remember to be respectful of the websites you are crawling by limiting the speed at which the web crawler extracts data. You should also make sure your web crawler adheres to the website's terms of use and privacy policy. Happy crawling!

Designing an ATM System

To design an ATM system, several factors need to be considered, such as user interface, security, transaction processes, and hardware components.

One of the critical components of an ATM system is the user interface. It should be intuitive and easy to use for people of all backgrounds. The interface should prompt users to input their PIN, select the transaction type, and provide clear and concise instructions at each step.

Another important aspect is security. The system should employ encryption techniques to safeguard user information and prevent unauthorized access. It should also have a mechanism to detect and respond to fraudulent activities.

Transaction processes should be efficient and fast, with the system able to process multiple transactions simultaneously. The hardware components such as the card reader, dispenser, and printer should be reliable and well-maintained to ensure smooth operation.

Overall, designing an ATM system requires careful consideration of all its components to provide a convenient, secure, and user-friendly experience for customers.

Designing a Ride-Hailing System like Uber, Ola, or Lyft

In today's world, ride-hailing systems like Uber, Ola, or Lyft have revolutionized the transportation industry. Here are some key features that need to be considered while designing such a system:

1. Registration and Authentication: users should be able to create an account and authenticate it using email or phone number.

2. Geolocation and routing: use GPS data to locate nearby drivers, estimate arrival time, and optimize the route.

3. Ride booking: allow users to book a ride in advance or instantly by specifying their pickup location, destination, and preferred ride type.

4. Fare estimation and payment: calculate the fare based on distance, time, and surge pricing. Payment options should be flexible and secure.

5. Driver tracking: allow users to track their driver's location and ETA in real-time.

6. Ratings and feedback: let users rate their ride and provide feedback to improve the overall experience.

7. Admin dashboard: provide an interface for managing users, drivers, rides, payments, and other system settings.

To develop such a system, various technologies such as MEAN stack, Spring Boot, AWS, and Google Maps API can be used. Proper testing and maintenance should be done to ensure a smooth and reliable user experience.

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