A system design interview guide from entry-level to senior
Last updated
Was this helpful?
The architecture of the system is typically designed to balance performance, scalability, and security requirements. It may include multiple layers of caching, load balancing, and failover mechanisms to ensure that requests are distributed evenly across multiple servers and that data is stored and retrieved efficiently.
Requests are typically handled by the system's request handler, which listens for incoming requests and dispatches them to the appropriate server or service. The request handler may also handle load balancing and failover mechanisms to ensure that requests are distributed evenly across multiple servers.
Requests are typically distributed across multiple servers using a load balancing mechanism, which distributes incoming requests evenly across all available servers. The load balancer may also monitor the health of each server and route requests to healthy servers only.
Requests are typically stored and retrieved from a database or cache using a key-value store or a cache provider. The key-value store or cache provider may use a distributed cache to store and retrieve data efficiently across multiple servers.
Data is typically stored and retrieved from a database or cache using a key-value store or a cache provider. The key-value store or cache provider may use a distributed cache to store and retrieve data efficiently across multiple servers.
Security is typically implemented using a combination of authentication, authorization, and encryption mechanisms. The system may use SSL/TLS to encrypt data in transit, and may also use encryption at rest to protect sensitive data. The system may also use rate limiting and other security mechanisms to prevent attacks and ensure that the system is secure.
Load balancing is typically implemented using a load balancer or a reverse proxy. The load balancer or reverse proxy may distribute incoming requests evenly across all available servers, and may also monitor the health of each server and route requests to healthy servers only.
Fault tolerance is typically implemented using redundancy and failover mechanisms. The system may use multiple servers to ensure that requests are distributed evenly across all available servers, and may also use failover mechanisms to switch to a backup server if a server fails.
Scalability is typically implemented using a combination of horizontal and vertical scaling techniques. The system may use a scaling strategy that adds or removes servers based on demand, or it may use a scaling strategy that adjusts the resources allocated to each server based on demand.
Performance optimization is typically implemented using a combination of caching, compression, and other techniques. The system may use caching to store frequently accessed data in memory, and may also use compression to reduce the size of data that is transmitted over the network.
Monitoring and logging are typically implemented using a monitoring system and logging framework. The monitoring system may monitor the health of each server, the performance of each server, and the overall performance of the system, and may generate alerts or notifications if any of these metrics exceed a certain threshold. The logging framework may log all requests and responses, as well as other relevant information, to help diagnose and troubleshoot issues.
Documentation and support are typically provided through a user manual, a help desk, and a knowledge base. The user manual may provide detailed instructions on how to use the system, including how to navigate the user interface, how to perform common tasks, and how to report issues. The help desk may provide support for users who encounter issues with the system, and may also provide training on how to use the system effectively. The knowledge base may provide detailed information on how the system is designed, how it works, and how to troubleshoot issues.
The system is designed for scalability and performance by using a combination of caching, load balancing, and other techniques. The system may use a caching provider to store frequently accessed data in memory, and may also use a load balancer to distribute incoming requests evenly across all available servers. The system may also use a scaling strategy that adds or removes servers based on demand, or it may use a scaling strategy that adjusts the resources allocated to each server based on demand.
The system is designed for security and reliability by using a combination of authentication, authorization, and encryption mechanisms. The system may use SSL/TLS to encrypt data in transit, and may also use encryption at rest to protect sensitive data. The system may also use rate limiting and other security mechanisms to prevent attacks and ensure that the system is secure. The system may also use redundancy and failover mechanisms to ensure that the system is resilient to failures.
The system is designed for maintainability and evolution by using a modular architecture that allows for easy customization and extension. The system may use a microservices architecture to break the system into smaller, independent services that can be developed, tested, and deployed independently. The system may also use a version control system to track changes to the code and documentation, and may use automated testing
Frugal Streaming is a technique used to approximate the results of a query over a data stream, while using minimal memory. It is often used in scenarios where the data stream is too large to fit into memory, but approximate results are acceptable. One example of Frugal Streaming is the Count-Min Sketch algorithm, which uses a fixed-size array of counters to estimate the frequency of items in a data stream. Each item is hashed to a set of counters, and the minimum count in that set is incremented. The estimate for the frequency of an item is the minimum count across all sets.
Leaky bucket and Token bucket are two algorithms used for traffic shaping and rate limiting in computer networks. The Leaky bucket algorithm regulates the rate at which data is transmitted by imposing a constant rate of data removal from a buffer. Any data that arrives in excess of the rate is discarded. The Token bucket algorithm regulates the rate at which data is transmitted by issuing tokens at a fixed rate. Each token allows a fixed amount of data to be transmitted. If there are no tokens available, data transmission is blocked.
Loosy Counting is a technique used to estimate the frequency of items in a data stream, while using minimal memory. It is similar to Frugal Streaming, but allows for a small amount of error in the estimates. One example of Loosy Counting is the HyperLogLog algorithm, which uses a fixed-size array of registers to estimate the number of distinct items in a data stream. Each item is hashed to a register, and the maximum number of leading zeros in the binary representation of the register values is used to estimate the number of distinct items.
Operational Transformation is a technique used to synchronize the state of a shared document or data structure across multiple clients in a distributed system. It is often used in collaborative editing applications, such as Google Docs. Operational Transformation works by transforming the operations performed by each client into a common form that can be applied in any order without affecting the final state of the document. This allows each client to see the changes made by other clients in real-time, while ensuring that the final state of the document is consistent across all clients.
Reverse index, also known as an inverted index, is a data structure used to index and search text documents. It works by creating an index of all the words in the documents, along with a list of the documents that contain each word. This allows for efficient searching of documents based on the words they contain. Reverse index is used in many applications, such as search engines and document management systems.
Rsync is a file synchronization algorithm used to efficiently transfer files between two systems over a network. It works by comparing the contents of the files on both systems and transferring only the differences between them. This can greatly reduce the amount of data that needs to be transferred, especially for large files or files that have only small changes. Rsync is commonly used for backups and for transferring large files over the internet.
Geohash and S2 Geometry are two related techniques used to represent and index geographic locations on a two-dimensional surface, such as a map. Geohash is a hierarchical spatial data structure that uses a string of characters to represent a location. Each character in the string represents a subdivision of the space, with longer strings representing smaller subdivisions. S2 Geometry is a library for manipulating geometric shapes on the surface of a sphere, such as the Earth. It uses a hierarchical grid system to partition the surface of the sphere into cells of varying sizes. Both Geohash and S2 Geometry are useful for indexing and querying large datasets of geographic locations.
Quadtree and Rtree are two related spatial data structures used for indexing and querying two-dimensional data, such as points, lines, and polygons. Quadtree is a hierarchical data structure that recursively subdivides a two-dimensional space into four quadrants, with each quadrant represented by a node in the tree. Rtree is a similar data structure that uses a hierarchical tree of rectangles to represent the data. Both Quadtree and Rtree are useful for spatial indexing and querying in applications such as geographic information systems and computer graphics.
Ray casting is a technique used to render three-dimensional scenes in computer graphics. It works by tracing rays from the viewer's eye through each pixel in the image plane and into the scene. The rays are tested for intersections with objects in the scene, and the color of the pixel is determined based on the properties of the closest object. Ray casting is a computationally intensive process, but can produce high-quality images with realistic lighting and shading effects.
A Trie, also known as a prefix tree, is a tree-like data structure used to store and retrieve strings efficiently. Each node in the tree represents a prefix of one or more strings, and the edges represent the characters that can follow the prefix. Tries are useful for applications such as autocomplete and spell checking, where fast string lookups are required.
