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Design Patterns

In software engineering, design patterns are tried‑and‑tested solutions to recurring problems in system design. They provide a shared vocabulary for developers and help create flexible, maintainable, and scalable applications. Broadly, design patterns fall into three categories: Creational, Structural, and Behavioral. In brief, Design Patterns are Reusable Solutions for Common Software Problems. Creational Patterns Creational patterns deal with object creation mechanisms , making systems more independent of how their objects are created.          1.  Singleton   Ensures a class has only one instance and provides a global point of access to it. Example: Logger, configuration settings.                        ```                      // Ensures only one instance of a class exists. // Useful for shared resources like l...
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Load Balancers in System Design

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When building scalable and reliable systems, one of the most critical components is the load balancer. Its job is simple yet powerful: distribute incoming network traffic across multiple servers so that no single server becomes overwhelmed. This ensures smooth performance, high availability, and a better user experience. 🔑 Key Functions of a Load Balancer Traffic Distribution : Spreads requests evenly across servers. Redundancy & Reliability : Keeps services available even if one server fails. Scalability : Makes it easy to add or remove servers as demand changes. Health Monitoring : Continuously checks server status to avoid routing traffic to unhealthy nodes. Session Persistence : Ensures a user’s session stays on the same server when needed. SSL Termination : Offloads encryption/decryption tasks from backend servers. 🛠️ Types of Load Balancers Hardware Load Balancers   Physical devices dedicated to balancing traffic. Often used in enterprise setups.   Software Load Ba...
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Data Partitioning in System Design

Data Partitioning Techniques: Making Databases Scale Better As applications grow and data explodes, databases can become bottlenecks. Queries slow down, servers get overloaded, and scaling becomes a nightmare. That’s where data partitioning comes in - a smart way to split your data into manageable chunks so your system stays fast, efficient, and scalable. The most common partitioning techniques with simple examples and their benefits: 1. Horizontal Partitioning (Sharding) Description: Splitting data across multiple tables or databases based on rows. Example 1 : You run a global app with millions of users. Instead of storing all user data in one giant table, you split it by region - Asia, Europe, and America. Each shard handles users from its region, reducing load and speeding up queries. Example 2 (Layman) : Think of a library with millions of books. Instead of keeping them all in one giant hall, you split them into different buildings by genre - fiction, science, history. Each buildin...
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