Okay, let's begin 2.4 System Design Patterns. These are common, reusable solutions and architectural approaches used to solve recurring problems in system design, especially for distributed systems.

We will cover:

  • 2.4.a Microservices Architecture
  • 2.4.b Message Queues
  • 2.4.c API Gateways
  • 2.4.d Proxy Servers (Review & Context)
  • 2.4.e Content Delivery Networks (CDNs) (Review & Context)

Let's start with 2.4.a Microservices Architecture.

  • Definition: Microservices architecture is an architectural style that structures an application as a collection of small, independent, and loosely coupled services. Each service typically implements a specific business capability, runs in its own process, and communicates with other services over a network (often using lightweight protocols like HTTP/REST or asynchronous messaging).

  • Contrast with Monolithic Architecture:

    • Monolith: The entire application is built as a single, large, tightly coupled unit. All components (UI, business logic, data access) are deployed together. Scaling requires scaling the entire application. A failure in one part can potentially bring down the whole system.
    • Microservices: The application is broken down into smaller, independent parts.

  • Key Characteristics & Principles:

    • Single Responsibility: Each microservice focuses on doing one thing well (e.g., managing user accounts, processing payments, handling product inventory).
    • Independently Deployable: Changes to one service can be deployed without needing to redeploy the entire application. This enables faster release cycles.
    • Decentralized Governance: Teams can often own individual services end-to-end, fostering autonomy and specialized expertise.
    • Technology Diversity (Polyglot Persistence/Programming): Teams can choose the best technology stack (programming language, database, etc.) for their specific service's needs.
    • Resilience / Design for Failure: Microservices architectures acknowledge that failures will happen and often incorporate patterns (like circuit breakers, discussed later) to handle partial failures gracefully.
    • Network Communication: Services communicate over the network, typically via REST APIs or message queues.

  • Pros of Microservices:

    • Improved Scalability: Individual services can be scaled independently based on their specific resource needs (e.g., scale the payment service more than the user profile service).
    • Faster Development & Deployment: Smaller codebases and independent deployments allow teams to iterate and release features more quickly.
    • Technology Flexibility: Use the right tool for the job for each service. Easier to adopt new technologies or rewrite individual services.
    • Fault Isolation: A failure in one non-critical service is less likely to impact the entire application (if designed correctly).
    • Team Autonomy: Smaller, focused teams can own services, leading to increased ownership and potentially faster development.
    • Better Maintainability (potentially): Smaller, well-defined services can be easier to understand and maintain than a large, complex monolith.

  • Cons & Challenges of Microservices:

    • Distributed System Complexity: You now have a distributed system, inheriting all its challenges: network latency, fault tolerance, need for robust inter-service communication.
    • Operational Overhead: Requires mature DevOps practices and infrastructure for deployment automation, service discovery, centralized logging, distributed tracing, and monitoring across many services.
    • Testing Complexity: End-to-end testing across multiple services is significantly more complex than testing a monolith.
    • Data Consistency: Maintaining data consistency across services that own their own databases is challenging. Often requires embracing eventual consistency and using patterns like the Saga pattern.
    • Network Latency & Reliability: Inter-service calls over the network are slower and less reliable than in-process calls within a monolith.
    • Debugging: Tracing a request or debugging an issue that spans multiple services can be difficult without proper tooling (distributed tracing).

  • When to Consider Microservices:

    • Large, complex applications.
    • Applications requiring high scalability and independent scaling of components.
    • Organizations with multiple development teams that can work independently.
    • When technology diversity is a significant advantage.
    • Caution: Don't default to microservices for simple applications. The operational complexity can outweigh the benefits. Starting with a well-structured "modular monolith" and potentially breaking it out later is often a pragmatic approach.

  • In an Interview: Understand the core idea, the contrast with monoliths, and be able to articulate the key pros and cons. Acknowledge the significant operational complexity involved. Justify why you might (or might not) choose microservices based on the system's requirements.

Advertisement