πππ¬π’π π§ ππππππ«π§π¬ ππ¬ππ πππ«π¨π¬π¬ ππ’ππππ«ππ§π πππ²ππ«π¬
In the intricate world of web development, where code and creativity converge, the design patterns used can significantly impact a websiteβs performance and user experience. Imagine a digital skyscraper, each floor playing a crucial role in delivering the content and services you interact with daily. In this blog, weβll embark on a journey through the layers of a web application, decoding the language of Design Patterns Used Across Different Layers.
From the client layer, where your device meets the internet, to the database layer, where data resides, each level of our digital skyscraper serves a distinct purpose. So, whether youβre a budding developer or a seasoned pro, join us as we unravel the architecture behind your favorite websites and applications, one layer at a time.
Client Layer
Client-side Load Balancing: Distributes requests from the client directly to the available service instances.
State Pattern: Allows an object to alter its behavior when its internal state changes.
Composite UI Pattern: Composes responses from multiple microservices to render the complete UI.
Load Balancer Layer
Geographical Distribution: Routes traffic based on the geographical location of the client.
Health Checks: Periodically checks the health of the servers and routes traffic only to healthy ones.
Affinity Based Routing: Routes the userβs request to the same server for maintaining session persistence.
Least Connections: Routes traffic to the server with the fewest active connections.
API Gateway Layer
Backend for Frontend (BFF): Tailors API responses to the needs of individual client types.
Circuit Breaker: Detects failures and prevents applications from trying to perform actions that are doomed to fail.
Retry Pattern: Helps to handle transient failures when it tries to connect to a remote service or network resource.
Request Collapsing: Collapses multiple requests for the same operation into a single request.
Web Server Layer
Page Cache Pattern: Stores the output of expensive operations and reuse it to avoid duplicated work.
Compression Pattern: Reduces the size of the response to improve load times.
Lazy Loading: Defers initialization of an object until the point at which it is needed.
Content Negotiation Pattern: The server generates different versions of a resource and serves the one matching the clientβs criteria.
Application Server Layer
Saga Pattern: Manages long-running transactions and deals with failures and compensating transactions.
CQRS (Command Query Responsibility Segregation): Separates read and write operations to improve performance and scalability.
Proxy Pattern: Provides a surrogate or placeholder for another object to control access to it.
Chain of Responsibility: Passes the request along a chain of handlers.
Caching Layer
Sidecar Caching: Deploy a dedicated cache alongside each microservice to provide isolated and scalable caching functionality.
Cache Chaining: Arrange multiple cache layers hierarchically to handle different granularity or lifetime, querying each layer sequentially on a cache miss.
Time-to-Live (TTL) Caching: Assigns a predefined lifespan to each cache entry, removing or refreshing the entry once its lifespan expires.
CDN Layer
Prefetching: Anticipates user actions and loads resources ahead of time.
Parallel Requesting: Makes multiple requests in parallel to improve load times.
Edge Computing: Processes data closer to the location where it is needed.
Domain Sharding: Splits resources across multiple domains to increase parallel downloads.
Adaptive Image Delivery: Delivers images tailored to the device and user context.
Database Layer
Sharding Pattern: Distributes data across multiple databases to improve scalability.
Replication Pattern: Keeps copies of data in multiple locations for availability and reliability.
Read-Replica Pattern: Uses read replicas to offload read operations from the primary database instance.
Query Object Pattern: An object that represents a database query.