10 Backend Design Pattern Laws of Senior Engineers and Architects

Ten Backend Design Patterns

The video explains ten backend design patterns as solutions to recurring problems in growing applications. Its central point is to understand the problem each pattern addresses and apply it when useful—not to add patterns automatically.

1. Repository — Separates database operations from business logic. Services use a repository without depending directly on a particular database, making business logic easier to test with mocks and database implementations easier to change. Repository-based approaches are common in frameworks such as Spring Boot, ASP.NET Core, and NestJS.

2. Factory — Centralizes object creation when there are multiple implementations. For example, a payment system can request a payment provider while a factory selects Stripe, Razorpay, or PayPal. This avoids scattering provider-specific creation logic throughout the application.

3. Singleton — Ensures that only one instance of a shared resource exists during the application’s lifecycle, such as a configuration or logging service. However, overusing singletons can create hidden dependencies and make code harder to test. Dependency-injection frameworks often manage shared lifecycles without requiring a manually implemented singleton.

4. Strategy — Puts alternative algorithms or business rules into separate, interchangeable strategies. For instance, premium, student, and promotional discounts can be implemented independently rather than accumulated in one large method full of conditional statements. The same approach can apply to authentication, shipping, tax, and payment processing.

5. Observer — Lets one component publish an event while other components respond independently. After an order is placed, inventory, email, loyalty, and analytics services can each handle the event without the order service directly coordinating every action. The video connects this event-driven approach to technologies such as Kafka, RabbitMQ, and Azure Service Bus.

6. Builder — Creates complex objects step by step rather than passing many optional values into a long constructor. This makes configuration clearer and reduces mistakes caused by confusing parameter order. Similar approaches appear in Java, Kotlin, C#, and cloud SDKs.

7. Adapter — Translates an external system’s interface or data format into one the application expects. It can normalize differences such as field names, casing, or JSON versus XML, allowing the rest of the application to use a consistent interface. Changes to a vendor’s API can then be isolated in its adapter.

8. Decorator — Adds behavior by wrapping an existing service rather than continually modifying its core implementation. Caching, logging, metrics, authorization, auditing, or rate limiting can be layered as needed. Middleware in backend frameworks is a familiar related idea.

9. CQRS (Command Query Responsibility Segregation) — Separates operations that change data (commands) from operations that retrieve it (queries). Read and write sides can be optimized independently and, in larger systems, may use different models or infrastructure. CQRS can add unnecessary complexity to a simple CRUD application.

10. Circuit breaker — Protects an application from repeated calls to a failing dependency. After recurring failures, the circuit opens and stops sending requests, allowing the system to fail quickly or return a fallback instead of tying up resources waiting for timeouts. After a delay, it allows trial requests. If the dependency has recovered, the circuit closes and normal traffic resumes. The video cites Resilience4j, Polly, and Istio service meshes as implementations or related technologies.

These patterns can be combined because each addresses a different concern. The video emphasizes using them to keep code understandable, testable, extensible, and resilient as applications and teams grow.

Main Speaker and Source

• Cloud X Berry — Single narrator presenting an introductory overview of backend design patterns.