Day 1 Introduction to System Design

What is System Design?

System design is the process of defining the architecture, components, and interfaces of a system to satisfy specific requirements. It involves making high-level choices about how a system should function and how its components will interact with one another.

Key Concepts in System Design:

1. Scalability:

   • Scalability refers to a system's ability to handle growing amounts of work or its potential to expand to accommodate that growth.

   • Types of scalability:

     • Vertical scaling (scaling up): Increasing the capacity of a single machine (e.g., adding more CPU or memory).

     • Horizontal scaling (scaling out): Adding more machines to distribute the load.

2. Reliability:

   • Reliability is the system’s ability to operate continuously without failure.

   • Strategies to improve reliability:

     • Redundancy: Having backup components in case of failure.

     • Replication: Duplicating services or data across multiple servers.

3. Availability:

   • Availability is the percentage of time a system is operational. It depends on the system’s ability to remain functional even in the face of failures.

   • High availability (HA): A system designed to operate continuously without failure for a long time.

4. Performance:

   • Performance refers to how quickly a system responds to requests.

   • Factors that affect performance:

     • Latency: Time taken to process a request.

     • Throughput: Number of requests a system can handle in a given period.

5. Maintainability:

   • Maintainability is how easy it is to update and improve a system over time. Clean code, modular architecture, and clear documentation all contribute to maintainability.

6. Consistency, Availability, and Partition Tolerance (CAP Theorem):

   • CAP theorem states that it is impossible for a distributed system to simultaneously provide all three guarantees:

     • Consistency: Every read receives the most recent write.

     • Availability: Every request receives a response, even if it's not the most recent one.

     • Partition Tolerance: The system continues to operate despite network partitioning (communication failures between servers).

7. Trade-offs in System Design:

   • System design involves making trade-offs between various properties (e.g., scalability vs. consistency, performance vs. reliability).

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Steps to Approach System Design Problems:

1. Understand the Requirements:

   • Clarify functional and non-functional requirements (e.g., performance, scalability, reliability).

   • Identify constraints (e.g., latency, throughput).

2. High-Level Architecture:

   • Break down the system into components (e.g., client, server, database).

   • Identify the communication between components.

3. Key Design Decisions:

   • Decide on data storage (SQL or NoSQL, distributed database).

   • Choose communication protocols (e.g., REST, gRPC, WebSocket).

   • Think about caching, load balancing, and replication strategies.

4. Component Design:

   • Detail the internals of each major component (e.g., how the database or API layer works).

   • Focus on data flow and interactions between components.

5. Scale the Design:

   • Plan for how the system will scale as traffic increases (e.g., through sharding or load balancing).

   • Consider strategies for failure recovery and replication.

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Common System Design Patterns:

1. Microservices Architecture:

   • Breaking down a system into small, independently deployable services that communicate over a network.

2. Monolithic Architecture:

   • A single unified codebase where all components of the system are packaged and deployed together.

3. Client-Server Architecture:

   • A structure where the server provides services, and the client makes requests.

4. Master-Slave Architecture:

   • A design where one node (the master) directs the operations, and other nodes (slaves) follow its instructions.

5. Event-Driven Architecture:

   • A system where components react to events, promoting loose coupling and scalability.

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