Interview Questions and Answers

The system can use a consistent hashing algorithm to distribute keys across multiple cache nodes, and a mechanism to handle cache misses by fetching data from the main storage.

Example:

When a node receives a cache miss, it fetches the data from the main database and stores it in the cache for future requests.

The system includes edge servers strategically placed worldwide to cache and deliver static content, reducing latency and improving performance.

Example:

A user in Asia requests an image, and it's served from the nearest edge server instead of the origin server.

The system comprises a feed generation service, a storage system for user posts, and algorithms to rank and personalize the feed based on user interests.

Example:

User sees posts in their feed based on relevance and recency.

The system can replicate data across multiple servers, use erasure coding for data durability, and implement techniques like sharding for better performance.

Example:

Even if one server fails, the system ensures data availability and integrity.

The system includes a content delivery network, video encoding/transcoding servers, and a recommendation engine to provide a seamless streaming experience.

Example:

A user selects a movie, and the system streams it in high quality without buffering.

The system involves a master server for metadata, chunk servers for storing data, and a replication mechanism for fault tolerance.

Example:

A user uploads a large file, and it gets distributed and replicated across multiple servers for reliability.

The system includes a trading engine, order matching algorithm, and a distributed database for storing real-time stock prices and transaction history.

Example:

A user places a stock order, and the system executes it in real-time based on market conditions.

The system involves audio/video processing, real-time communication, and scalability to support multiple participants in a conference.

Example:

Multiple users join a video call, and the system ensures smooth communication with low latency.

The system uses machine learning models, user reports, and manual review to identify and filter inappropriate content.

Example:

A user posts content, and the system automatically detects and removes content violating community guidelines.

The system involves indexing products, ranking algorithms, and handling user queries with efficient search and filtering capabilities.

Example:

A user searches for 'laptops,' and the system returns relevant products with sorting options.

The system involves device connectivity, data processing, and storage for managing a large number of IoT devices and their data.

Example:

Sensors in smart home devices send data to the platform, and the system processes and stores the information for analysis.

The system involves message producers, queues, and consumers, with features like message persistence, load balancing, and fault tolerance.

Example:

Services in a microservices architecture communicate by sending messages through the queue.

The system involves real-time collaboration, version control, and conflict resolution mechanisms to enable multiple users to edit a document simultaneously.

Example:

Several users edit a document together, and changes are reflected in real-time across all collaborating users.

The system involves game servers, matchmaking algorithms, and real-time communication for a seamless multiplayer gaming experience.

Example:

Players from different locations connect to the game server and engage in a multiplayer game with low latency.

The system uses events to trigger actions, ensuring real-time updates and responses to market changes in the financial trading domain.

Example:

A change in stock prices triggers automatic buy/sell orders in response to predefined trading algorithms.

The system involves data ingestion, processing, and analytics in real-time to provide insights on streaming data.

Example:

Sensor data from IoT devices is continuously analyzed to detect anomalies and trigger alerts in real-time.

The system manages the distribution and execution of tasks across multiple nodes, considering load balancing and fault tolerance.

Example:

A cluster of servers schedules and executes tasks in parallel to efficiently process a large workload.