In 2026, Meta continues to be one of the leading tech companies that sets the bar high for system design interviews. The questions asked by Meta in these interviews test candidates on their ability to design complex systems, solve technical challenges, and communicate ideas clearly. If you’re preparing for a Meta system design interview, knowing the types of questions you might face and how to approach them is crucial to your success.

In this blog, we’ve compiled the top 25 system design interview questions asked by Meta in recent years. Along with each question, we’ll explain how to approach the answer and provide a sample answer to give you an idea of how to structure your response. These questions are meant to help you get familiar with the interview process and make you feel more confident when you're in the hot seat

1. How would you design a URL shortening service like Bitly?

Start by clarifying the requirements of the URL shortening service. Identify core features like shortening long URLs, redirecting short URLs to original links, and tracking analytics. Discuss database design, how to generate unique IDs, and how to scale the service.

Sample Answer:
To design a URL shortening service, I would begin by defining the requirements. The service should shorten long URLs, redirect to the original URL upon request, and optionally store metadata like usage statistics. I would use a hash function to generate unique shortened URLs. The database can be a NoSQL system for scalability, where each shortened URL’s hash points to the original URL. For scaling, I would implement sharding based on the hash. Caching frequently accessed URLs in a system like Redis would improve performance, and adding rate-limiting would prevent abuse.

2. Design a cache system for a web application.

Explain the concept of caching and why it's important for improving performance. Mention cache eviction policies (e.g., LRU), data consistency, and where to store the cache (e.g., in-memory cache like Redis or Memcached). Also, discuss cache invalidation strategies.

Sample Answer:
To design a caching system for a web application, the cache should be implemented to store the results of expensive database queries, like user profiles or search results. I would use an in-memory cache like Redis to store frequently accessed data. I would implement an LRU (Least Recently Used) eviction policy to ensure that the cache does not grow indefinitely. For consistency, I would use a TTL (Time to Live) strategy to expire cache entries periodically. Cache invalidation would be handled by event-driven updates—for example, when data is updated in the database, the corresponding cache entry would be invalidated.

3. How would you design an online file storage system like Google Drive?

Start by discussing how you would store files, how to handle large files, and the user experience (e.g., versioning, sharing). Consider aspects such as file indexing, search functionality, metadata storage, and scalability.

Sample Answer:
For an online file storage system, I would design it around a distributed file system like HDFS to ensure scalability and fault tolerance. Each file would be stored in chunks across multiple servers. For metadata, I would use a relational database to store file information (name, size, user, permissions). I would implement versioning by keeping previous versions of files and linking them to the current version. The system would allow users to share files via unique URLs and manage permissions through a role-based access control model. To handle search functionality, I would index file metadata and use Elasticsearch for fast searching.

4. Design a messaging system like WhatsApp.

Think about the core features of the system, such as real-time messaging, scalability, and message storage. Consider how to handle push notifications, message delivery guarantees, and data synchronization across devices.

Sample Answer:
To design a messaging system, I would start by considering real-time communication. A pub/sub model can be used for push notifications, where clients subscribe to channels. I would implement message queues (like Kafka) to ensure reliable message delivery between users. For message storage, a NoSQL database such as Cassandra could handle the large volume of messages. To ensure scalability, I would implement horizontal scaling with multiple servers and load balancers. The app would sync messages across multiple devices using WebSockets for real-time data transfer.

5. How would you design a recommendation system like Netflix?

Discuss the different types of recommendation systems (collaborative filtering, content-based, hybrid models). Explain how you would store user preferences, generate recommendations, and scale the system.

Sample Answer:
A recommendation system like Netflix can be designed using a collaborative filtering approach, where recommendations are made based on user behavior (e.g., watching history, ratings). I would use a matrix factorization technique to find patterns in users’ preferences. The system would need to store user interaction data in a distributed database like Cassandra to scale. For real-time recommendations, I would use cache mechanisms like Redis to store frequent queries. A hybrid model that combines collaborative filtering with content-based filtering (e.g., recommending similar movies based on genre, director, etc.) would improve the recommendation accuracy.

6. How would you design a system to handle millions of users for a video streaming service?

Focus on scalability, content delivery, and fault tolerance. Discuss how to handle video storage, streaming protocols, load balancing, and CDN (Content Delivery Networks) for efficient content delivery.

Sample Answer:
For a video streaming service, I would start by using CDNs (such as Akamai or Cloudflare) to distribute video content efficiently to users across the globe. Videos would be stored in a distributed file system with multiple replicas to ensure availability. To handle millions of users, I would use horizontal scaling with load balancers and microservices for different components (e.g., video encoding, playback, recommendations). I would implement adaptive streaming protocols like HLS (HTTP Live Streaming) to ensure smooth playback across devices with varying internet speeds.

7. How would you design a system for real-time data analytics?

Discuss how you would handle streaming data, data storage, and real-time processing. Mention technologies like Apache Kafka, Apache Flink, and Spark Streaming for handling large volumes of real-time data.

Sample Answer:
For real-time data analytics, I would implement a streaming data pipeline using Apache Kafka for data ingestion. The data would be processed in real-time using Apache Flink or Apache Spark Streaming for low-latency analysis. The processed data would be stored in a data warehouse like Amazon Redshift or Google BigQuery for long-term storage. To visualize real-time analytics, I would integrate the system with a dashboard (using tools like Grafana or Tableau). The system would be designed for scalability with the ability to handle high-throughput data and allow for quick decision-making.

8. How would you design an online booking system like Airbnb?

Consider user interactions, property listings, availability checks, and payment integration. Think about how to handle scheduling, real-time updates, and search functionality.

Sample Answer:
For an online booking system like Airbnb, I would start by designing a distributed database to handle property listings, availability, and user profiles. I would implement real-time updates to manage bookings and availability using WebSockets. The system would need a search engine (e.g., Elasticsearch) to allow users to search properties based on filters like location, price, and amenities. For payment processing, I would integrate a secure payment gateway such as Stripe. To handle scaling, I would use microservices to separate different components like search, payment, and messaging.

9. How would you design a social media platform like Facebook?

Think about user profiles, posts, feeds, notifications, and privacy. Discuss how to handle real-time updates, scalable data storage, and content moderation.

Sample Answer:
Designing a social media platform involves managing user profiles, posts, feeds, and interactions. I would store user data in a NoSQL database like Cassandra to handle scalability. For the news feed, I would implement a graph database (e.g., Neo4j) to manage relationships between users, posts, and comments. WebSockets would be used to push real-time updates for comments, likes, and notifications. To handle privacy, I would use role-based access control and ensure encryption for sensitive data. Content moderation can be powered by a combination of automated filters and manual review.

10. How would you design a scalable notification system?

Discuss the need for real-time notifications, scaling challenges, and handling various delivery channels (email, SMS, push notifications). Explain the use of message queues for decoupling services and ensuring reliability in message delivery.

Sample Answer:
For a scalable notification system, I would use a pub/sub architecture, where different services (email, SMS, push) subscribe to notification topics. I’d use message queues like Kafka to decouple notification generation from delivery. For scaling, I would ensure the system is horizontally scalable by adding more servers as traffic grows. Push notifications would use APNs for iOS and Firebase for Android. I’d implement retry logic for failed deliveries and allow for customizable user preferences.

11. Design a rate-limiting service for an API.

Start by explaining the importance of rate limiting to prevent overuse and abuse of the API. Discuss different strategies like token bucket, leaky bucket, or fixed window to limit the number of requests.

Sample Answer:
To design a rate-limiting service, I would use the token bucket algorithm, where each user is allowed a certain number of requests per second, and extra requests are throttled or delayed. The system would store the rate limit data in an in-memory store like Redis to track user activity. If a user exceeds the limit, the system returns a 429 Too Many Requests response. For distributed systems, I would ensure the rate limits are consistent across multiple instances using Redis clustering.

12. How would you design a multi-tenant SaaS system?

Discuss how to handle shared resources and data isolation for multiple customers. Talk about data partitioning, and consider strategies like single database, multiple schemas, or separate databases per tenant for scalability and security.

Sample Answer:
For a multi-tenant SaaS system, I would use multi-tenancy with separate schemas within a single database for scalability. This allows us to manage tenants independently while sharing the same database resources. For higher isolation, I’d implement separate databases per tenant, especially for high-security clients. To scale, I’d use load balancers to distribute traffic evenly across servers and ensure that tenants are isolated in terms of performance, security, and data access.

13. How would you design an online voting system?

Address the requirements of security, scalability, and data integrity. Discuss encryption for vote confidentiality, and how to prevent fraud or tampering, as well as ensuring auditability and scalability under high traffic.

Sample Answer:
For an online voting system, I would use end-to-end encryption to ensure vote confidentiality. I’d implement a distributed ledger like blockchain for transparency and immutability, where each vote is stored in a block. For scalability, I’d use sharding to distribute data and ensure high availability. To prevent tampering, I’d integrate multi-factor authentication and email verification. The system would allow for auditing through a secure log of all transactions.

14. How would you design an API gateway?

Explain the role of an API gateway in managing traffic, routing requests to backend services, and ensuring security. Discuss features like authentication, rate limiting, and load balancing.

Sample Answer:
An API gateway acts as a single entry point for all client requests. It routes incoming requests to the appropriate backend services, performs authentication, and applies rate-limiting to ensure fair usage. I would implement load balancing across multiple instances to distribute traffic evenly. For security, the gateway would use JWT tokens for authentication and OAuth for third-party integrations. The gateway would also handle logging and API versioning to ensure smooth transitions during updates.

15. How would you design a job scheduling system?

Discuss the task queuing mechanism, how to handle task prioritization, and how to ensure that tasks are executed reliably and on time. Consider retry mechanisms and failover strategies for robustness.

Sample Answer:
For a job scheduling system, I would use a distributed queue like RabbitMQ to enqueue tasks. The system would pick up tasks in order of priority, and I’d use a worker pool to process tasks concurrently. For failed jobs, the system would retry execution with exponential backoff. To scale, I’d implement horizontal scaling of workers, adding more as needed based on the queue size. To ensure fault tolerance, I would use replication and backup systems to avoid single points of failure.

16. How would you design a search engine like Google?

Start by discussing how to crawl and index websites, how to rank pages based on relevance, and how to ensure fast search results. Mention data storage, distributed computing, and caching for performance.

Sample Answer:
To design a search engine, I would start by creating a crawler to index the web and store the data in a distributed database like HBase. I would use MapReduce to process and rank pages based on factors like keyword frequency, page authority, and content quality. To speed up searches, I would implement caching for frequently accessed pages and use load balancing to distribute search requests evenly across servers. The ranking algorithm would involve machine learning models to continuously improve the relevance of search results.

17. Design a scalable logging system.

Discuss how to collect, store, and process logs from different services. Address log aggregation, real-time processing, and how to scale the system to handle large volumes of log data.

Sample Answer:
For a scalable logging system, I would use a log aggregation tool like Fluentd to collect logs from multiple sources. The logs would be stored in Elasticsearch for easy search and analysis. To handle large volumes of logs, I’d implement sharding and partitioning in the database. For real-time log processing, I would use Apache Kafka to stream logs to a processing pipeline where they can be analyzed for trends, errors, or system health. The system would scale horizontally to handle increased traffic during peak times.

18. How would you design an event-driven architecture for a microservices system?

Explain how microservices can communicate asynchronously using events. Discuss event sourcing, event queues, and decoupling services for scalability and fault tolerance.

Sample Answer:
In an event-driven architecture, microservices communicate asynchronously through event queues like Kafka. Each service emits events when its state changes (e.g., “order created”), and other services can subscribe to these events. I would use event sourcing to store the history of all events, allowing services to reconstruct the state at any time. This architecture helps decouple services, ensuring that they are not tightly coupled to each other’s execution. Retry mechanisms and dead-letter queues would be used to ensure reliability and fault tolerance.

19. How would you design a real-time multiplayer game?

Discuss the need for low-latency communication, game state synchronization, and how to handle user inputs. Mention network protocols and server architecture to handle real-time interactions.

Sample Answer:
For a real-time multiplayer game, I would use WebSockets for low-latency communication between clients and servers. The game state would be maintained on the server and synchronized with the clients in real time. To reduce lag, I’d implement state interpolation on the client-side to smooth out gameplay. The server architecture would involve multiple game instances to handle large numbers of players. I would use a load balancer to distribute players to the appropriate game server, and employ region-based servers to minimize latency based on the player’s location.

20. How would you design an e-commerce checkout system?

Discuss how to handle user sessions, payment gateways, inventory management, and order processing in the checkout flow. Mention how to ensure scalability, security, and fault tolerance.

Sample Answer:
To design an e-commerce checkout system, I would start by implementing a shopping cart stored in the user’s session. The system would allow for real-time inventory management, checking stock levels before processing orders. Payment would be handled through secure payment gateways like Stripe or PayPal. To ensure scalability, the system would use microservices for order processing, shipping, and payment handling. Caching would be used to store frequently accessed product data, and data replication would ensure fault tolerance across multiple regions.

21. How would you design a content delivery network (CDN)?

Focus on how to cache content, how to handle content replication, and how to ensure low latency for users across different geographies. Discuss edge servers, caching policies, and load balancing.

Sample Answer:
A CDN delivers content to users by replicating it across edge servers located in various geographical locations. When a user requests content, the CDN directs the request to the nearest edge server. I would use caching to store static content like images, videos, and webpages on edge servers, with cache expiration policies to ensure that the content is always up-to-date. For dynamic content, I’d use load balancing and dynamic routing to ensure low latency. The CDN would scale by adding more edge servers as the user base grows.

22. How would you design a system for managing user authentication?

Explain the need for secure authentication and how to handle user sessions, password storage, and multi-factor authentication.

Sample Answer:
For user authentication, I would implement JWT (JSON Web Tokens) for stateless authentication, where the token is stored on the client-side and used for making authenticated requests. Passwords would be securely hashed using bcrypt before being stored in the database. For added security, I would implement multi-factor authentication (MFA), sending a one-time passcode via SMS or email after the initial login. OAuth would be used for third-party authentication (e.g., Google or Facebook logins).

23. How would you design a distributed messaging system?

Talk about message queues, message brokers, scaling, and fault tolerance.

Sample Answer:
A distributed messaging system would use a message broker like Kafka or RabbitMQ to send messages between producers and consumers. Messages would be stored in persistent queues, ensuring reliable delivery even in case of failure. For scalability, the system would support horizontal scaling by adding more consumers and partitioning the message queues. Retry policies would be implemented to handle temporary failures, and acknowledgment mechanisms would be in place to ensure that messages are successfully processed.

24. How would you design a real-time analytics dashboard?

Explain how to collect and visualize data in real time. Discuss the use of data pipelines, streaming technologies, and dashboards like Grafana or Power BI.

Sample Answer:
For a real-time analytics dashboard, I would use a data pipeline with tools like Apache Kafka to collect real-time data. The data would be processed using Apache Flink or Spark Streaming and then stored in a data warehouse like Google BigQuery. For visualization, I would integrate the processed data with a dashboard tool like Grafana, allowing users to see live metrics such as sales, website traffic, or system performance. The dashboard would be updated every few seconds, ensuring real-time monitoring.

25. How would you design a collaborative document editing system like Google Docs?

Discuss how to handle real-time updates, data consistency, and multi-user collaboration.

Sample Answer:
In a collaborative document editing system, I would use operational transformation (OT) or CRDT (Conflict-free Replicated Data Types) to handle real-time document updates. Changes made by multiple users would be applied in real-time without conflicts. The document data would be stored in a NoSQL database like Couchbase for fast updates and retrieval. To ensure data consistency, I’d implement version control and allow users to track changes. The system would use WebSockets for real-time communication between users.

Conclusion

Meta’s system design interview questions assess a candidate’s ability to think critically and design scalable, efficient, and reliable systems. By practicing answers to these common questions and focusing on explaining your thought process clearly, you’ll be well-prepared for your interview.

These top 25 system design questions, with their sample answers, provide a great starting point for preparing. Remember, it’s not just about getting the right answer it’s about demonstrating your ability to tackle complex problems and communicate your design choices effectively.

Good luck with your Meta system design interview prep!