Summary of "I ACED my Technical Interviews knowing these System Design Basics"
Main Ideas and Concepts
- 
        Starting Point for System Design
        
- Begin with a simple web server and a single database.
 - Recognize that this setup won't scale as user demands grow.
 
 - 
        Distributed Systems
        
- Defined as networks of independent computers working together.
 - Key characteristics:
                
- Scalability: Ability to handle growth through horizontal (adding servers) or vertical (upgrading hardware) scaling.
 - Reliability: System continues functioning correctly despite component failures.
 - Availability: The operational percentage of the system, often expressed in "nines."
 - Efficiency: Measured by latency (response delay) and throughput (operations handled).
 
 
 - 
        CAP Theorem
        
- States that a distributed system can only guarantee two out of three properties:
                
- Consistency: All nodes display identical data.
 - Availability: Every request receives a response without guaranteeing the most recent data.
 - Partition Tolerance: System continues functioning despite network failures.
 
 
 - States that a distributed system can only guarantee two out of three properties:
                
 - 
        Load Balancing
        
- Essential for distributing incoming requests across multiple servers to prevent overload.
 - Load balancers can be placed at various levels and use different algorithms (e.g., least connections, round robin, IP hash).
 - Redundancy in load balancers is necessary to avoid single points of failure.
 
 - 
        Caching
        
- Improves data retrieval speed by storing frequently accessed data.
 - Challenges include maintaining data consistency and synchronization with the original database.
 - Various Caching strategies include write-through, write-around, and write-back.
 
 - 
        Database Choices
        
- SQL Databases: Structured, rigid schema, ideal for compliance and consistent data.
 - NoSQL Databases: Flexible schema, better for large volumes of unstructured data and rapid development.
 
 - 
        Indexing
        
- Improves query performance by creating separate data structures pointing to actual data.
 - Types of indexes include primary key, secondary index, composite index, and foreign key.
 
 - 
        Data Partitioning
        
- Used when databases can no longer scale vertically.
 - Techniques include horizontal, vertical, and directory-based partitioning.
 - Challenges include complexity in joining data across partitions and data rebalancing.
 
 
Methodology and Instructions
- Designing a Scalable Architecture:
        
- Start with a basic setup and gradually implement Distributed Systems.
 - Incorporate load balancers to manage traffic and prevent server overload.
 - Utilize Caching strategies to enhance performance.
 - Choose the appropriate database based on data structure needs.
 - Implement Indexing to improve query speeds.
 - Consider data partitioning techniques when scaling issues arise.
 
 
Speakers or Sources Featured
The video is presented by a single speaker who discusses system design principles in the context of preparing for technical interviews. Specific names or external sources are not mentioned in the subtitles.
Category
Educational