What is CONSISTENT HASHING and Where is it used?

About this video

### Summary of the Text: 1. **Problem Statement**: - The main issue is not load balancing but dynamically adding or removing servers, which disrupts the local data distribution across servers. 2. **Proposed Solution: Consistent Hashing**: - Use a ring structure to map hashed request IDs and server IDs. - Hash requests and servers using the same (or different) hash functions, then take the remainder with `M` (size of the hash space). - Servers are placed on the ring at positions determined by their hash values. 3. **Request Assignment**: - Requests are assigned to the nearest server clockwise on the ring. - This ensures uniform load distribution due to the random nature of hashing. 4. **Dynamic Server Management**: - **Adding Servers**: New servers are added to the ring, and only nearby requests are reassigned, minimizing changes to existing server loads. - **Removing Servers**: Requests from a removed server are reassigned to the next nearest server clockwise. 5. **Challenges with Few Servers**: - With a small number of servers, load distribution can become skewed, as some servers may handle disproportionately more requests. 6. **Improvement with Virtual Servers**: - To address skewness, use multiple hash functions to create "virtual servers" for each physical server. - Each server gets multiple points on the ring, reducing the likelihood of uneven load distribution. - For example, with `K` hash functions, 4 servers will have `4 * K` points on the ring, improving balance. 7. **Efficiency of Virtual Servers**: - Adding or removing a server affects only its virtual points, distributing the load change across multiple regions. - This minimizes disruption and maintains uniform load distribution. 8. **Applications of Consistent Hashing**: - Used in distributed systems like web caches and databases for efficient load balancing. - Provides flexibility and scalability in dynamic environments. 9. **Practical Implementation**: - Choose an appropriate value for `K` (e.g., logarithmic in the number of servers) to minimize skewed loads. - Ensure minimal changes in load distribution when servers are added or removed. 10. **Conclusion**: - Consistent hashing is a powerful technique for managing dynamic server environments. - It ensures efficient and uniform load balancing, making it essential for modern distributed systems. This summary captures the key concepts and practical applications of consistent hashing as described in the text.

Course: System Design Playlist

**Course Description: System Design Playlist** This comprehensive course, titled "System Design Playlist," is designed to provide students with a deep understanding of system design principles and practices through real-world analogies and technical explanations. The course begins by using the analogy of running a pizza restaurant to illustrate fundamental concepts in system design, such as optimizing processes, scaling resources, and ensuring resilience. Students will learn about vertical scaling—enhancing the capabilities of existing resources—and horizontal scaling—adding more resources to distribute the workload. Through this engaging example, participants will grasp essential strategies for improving throughput, eliminating single points of failure, and implementing backup systems to maintain operational continuity. As the course progresses, students will delve into advanced topics like microservice architecture, where responsibilities within a system are clearly defined and divided among specialized teams or services. This approach allows for efficient scaling and management of different components based on their specific needs. Additionally, the course covers distributed systems, highlighting the importance of fault tolerance and quick response times by strategically placing servers closer to users. Concepts such as load balancing, which intelligently routes requests to optimize performance, and decoupling systems to enhance flexibility and adaptability, are thoroughly explored. Participants will also learn about logging and metrics to monitor system health and make informed decisions. The course wraps up by contrasting high-level system design, which focuses on overarching architectural decisions, with low-level system design, which deals with the actual coding and implementation details. By mapping business scenarios to technical solutions, students will gain insights into designing scalable, reliable, and extensible systems. Whether you're new to system design or looking to deepen your expertise, this course equips you with the knowledge and tools needed to tackle complex design challenges and develop robust systems capable of meeting diverse user demands.