Product Management

How Microservices Work: An Overview

Vijay Gupta's photo
Vijay Gupta
·

4 min read

Microservices is an architectural style for designing and developing software applications as a collection of small, independent, and loosely coupled services. Each service is responsible for a specific business functionality and communicates with other services through lightweight protocols, typically REST APIs or messaging queues.

Key Characteristics of Microservices:

  1. Independent Deployment: Each microservice can be deployed, updated, or scaled independently without affecting other services.

  2. Single Responsibility: Each service is built around a specific business capability or function (e.g., user management, payment processing).

  3. Decentralized Data Management: Each service manages its own database, ensuring data encapsulation and reducing dependencies.

  4. Technology Agnostic: Different services can use different programming languages, frameworks, or databases based on their specific requirements.

  5. Fault Isolation: A failure in one service does not impact the entire system.

Advantages of Microservices:

  • Scalability: Easier to scale specific components based on demand.

  • Flexibility: Teams can use the best tools and technologies for each service.

  • Faster Development: Smaller, focused teams can develop services in parallel.

  • Resilience: Fault isolation reduces the risk of a system-wide outage.

Challenges of Microservices:

  • Complexity: Managing a distributed system requires robust tools and processes for communication, monitoring, and debugging.

  • Network Overhead: Inter-service communication can introduce latency and potential bottlenecks.

  • Data Consistency: Maintaining consistency across multiple databases can be challenging.

  • Deployment Overhead: Requires a sophisticated DevOps setup for CI/CD, containerization, and orchestration (e.g., Kubernetes).

Use Case Example:

In an e-commerce platform:

  • Order Service: Manages orders.

  • User Service: Handles user profiles and authentication.

  • Payment Service: Processes payments.

  • Inventory Service: Tracks inventory levels.

These services work together to provide the functionality of the platform but operate independently, making it easier to develop, scale, and maintain.

Monolithic Architecture:

  • A single, large application that includes all functionalities like user management, payment processing, inventory, etc.

  • One database for the entire application.

  • Tight coupling between components, making it harder to update or scale specific parts without affecting the whole system.

+-------------------------------------+
|             Monolithic App          |
|   +-----------------------------+   |
|   | User Management             |   |
|   | Payment Processing          |   |
|   | Inventory Management        |   |
|   +-----------------------------+   |
+-------------------------------------+
             Single Database

Microservices Architecture:

  • Multiple smaller, independent services (e.g., User Service, Payment Service, Inventory Service).

  • Each service has its own database, making it easier to manage data independently.

  • Services communicate with each other through APIs or message queues, ensuring loose coupling.

sqlCopy code+---------------------+       +---------------------+
|    User Service     |       |   Payment Service   |
| +-----------------+ |       | +-----------------+ |
| |  User Database  | |<----->| | Payment Database | |
| +-----------------+ |       | +-----------------+ |
+---------------------+       +---------------------+

            |
            V

+---------------------+
|  Inventory Service  |
| +-----------------+ |
| | Inventory DB    | |
| +-----------------+ |
+---------------------+

This textual diagram illustrates the modular nature of microservices versus the all-in-one nature of a monolith.

In a microservices architecture, services are decoupled, so they don’t share a single database. Instead, integration between services is achieved through communication mechanisms, such as:

  1. API Calls: One service can request data from another using REST or gRPC.

  2. Message Queues/Event Brokers: Services can publish and subscribe to events via tools like Kafka or RabbitMQ.

  3. Data Replication/Syncing: Relevant data can be duplicated across services if needed.

For your example:

Scenario: Adding a User

  • User Service: Adds the new user to its own database.

  • Payment Service: Needs to recognize this new user, but it doesn’t share the same database.

How It Works:

  1. Event-Driven Approach:

    • After a user is added, the User Service publishes an event (e.g., "UserCreated") to a message queue or broker.

    • The Payment Service subscribes to this event, receives the new user data, and creates an associated record in its own database.

  2. Synchronous API Call:

    • The Payment Service queries the User Service directly via an API when it needs user details. However, this creates runtime dependencies.

  3. Data Synchronization:

    • The User Service periodically syncs user data to other services that need it.

Integration Workflow Example (Event-Driven)

  1. Step 1: Add a User in User Service

    • User Service adds the user to its database.

    • Publishes an event:
      {"event": "UserCreated", "data": {"userId": 123, "name": "John Doe"}}.

  2. Step 2: Payment Service Receives the Event

    • The Payment Service listens to "UserCreated" events.

    • On receiving the event, it creates a new entry in its own database:
      {"userId": 123, "balance": 0}.

Why This Works:

  • Decoupling: The services operate independently but collaborate through events or APIs.

  • Data Integrity: Each service owns its data but updates it based on relevant external events.

  • Scalability: Services are not tightly bound, allowing for easier scaling and maintenance.

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