Architecture - Clean | Hexagonal | Onion Architecture

Clean Architecture (Uncle Bob)

Idea (one-liner)

Structure your app into concentric rings where inner rings (entities / use-cases) contain enterprise/business rules and outer rings contain frameworks and UI. Dependencies always point inward.

Layers (outer → inner)

• Infrastructure (EF, DB, web frameworks, email)
• Interface Adapters (controllers, presenters, gateways) — translate to/from domain
• Use Cases / Application Services (interactors)
• Entities / Domain (business rules, value objects, aggregates)

Key rules

• Inner layers are framework-agnostic.
• Use dependency inversion: inner layer defines interfaces; outer layers implement them.
• Controllers and UI are at the outermost layer.

Typical folder structure (C#)

/src
  /MyApp.Api                -> Web API (Controllers, DTOs, ASP.NET)
  /MyApp.Application        -> Use cases / Application services / Interfaces for Repos
  /MyApp.Domain             -> Entities, ValueObjects, DomainEvents, Interfaces (rare)
  /MyApp.Infrastructure    -> EF Core, repository implementations, messaging, persistence
  /MyApp.Tests

Tiny C# example (Clean)

Domain (inner):

// MyApp.Domain/Order.cs
public class Order { /*aggregate root*/ }
public interface IOrderRepository
{
    Order GetById(Guid id);
    void Save(Order order);
}

Application (use-case):

// MyApp.Application/PlaceOrderService.cs
public class PlaceOrderService
{
    private readonly IOrderRepository _orders;
    public PlaceOrderService(IOrderRepository orders) => _orders = orders;

    public void Execute(PlaceOrderCommand cmd) {
        var order = new Order(/*...*/);
        // business/use-case logic
        _orders.Save(order);
    }
}

Infrastructure (outer):

// MyApp.Infrastructure/OrderRepository.cs
public class OrderRepository : IOrderRepository
{
    private readonly AppDbContext _db;
    public OrderRepository(AppDbContext db) => _db = db;
    public Order GetById(Guid id) => _db.Orders.Include(...).FirstOrDefault(o=>o.Id==id);
    public void Save(Order order) {
        _db.Orders.Update(order);
        _db.SaveChanges();
    }
}

API wiring (composition root):

// MyApp.Api/Program.cs
services.AddScoped<IOrderRepository, OrderRepository>();
services.AddScoped<PlaceOrderService>();

---

Onion Architecture (Jeffrey Palermo)

Idea (one-liner)

Very similar to Clean: domain model in the center, application services around it, and infrastructure at the outermost ring. Emphasis on domain-centric design and keeping domain independent of data concerns.

Layers

• Domain (entities, value objects, interfaces)
• Application Services (business use-cases)
• Infrastructure (implementations)
• Presentation (UI, API) — sometimes shown outside infrastructure

Key rules

• Dependencies point toward the domain core.
• Domain defines repository interfaces; implementations reside in Infrastructure.
• Typically slightly simpler conceptual mapping than Clean but equivalent in practice.

Folder structure

/src
  /Domain
  /Application
  /Infrastructure
  /Web

C# example differences

Code examples are essentially identical to Clean — both use dependency inversion and keep domain stable. Onion often expresses the idea with an emphasis on domain-first development.

---

Hexagonal Architecture (Ports & Adapters — Alistair Cockburn)

Idea (one-liner)

Design your app around the core domain + application logic and expose ports (interfaces). External systems connect via adapters (implementations). The core is decoupled from I/O and UIs.

Structure

• Domain / Application core (inside)

  • Defines ports (interfaces): e.g., IOrderRepository, IEmailSender

• Adapters (outside)

• Primary adapters: UI / CLI / REST controllers (call the core)
• Secondary adapters: DB, message buses, email (implement ports)

Key rules

• The core depends only on ports (interfaces).
• Adapters implement ports and are swappable (DB → Mongo/SQL without changing core).
• Great for systems where many different input/output mechanisms exist.

Folder structure

/src
  /Core          -> Domain, Ports (interfaces), Use Cases
  /Adapters
    /Rest        -> Controllers calling use-cases
    /Ef         -> EF Core implementation of repository port
    /Messaging

C# example (port/adapter style)

Core (port definition):

// Core/Ports/IOrderRepository.cs
public interface IOrderRepository
{
    Order Load(Guid id);
    void Store(Order order);
}

Adapter (EF):

// Adapters/Ef/OrderRepositoryEf.cs
public class OrderRepositoryEf : IOrderRepository { /*implements using DbContext*/ }

Controller (primary adapter):

// Adapters/Rest/OrdersController.cs
[HttpPost]
public IActionResult Create(OrderDto dto) {
    var order = _mapper.Map<Order>(dto);
    _placeOrderUseCase.Execute(order);
    return Ok();
}

---

Visual / conceptual differences (short)

• Clean vs Onion: almost same in practice. Clean uses explicit layers named “entities/use cases/controllers”, Onion emphasizes domain core and rings. Both use dependency inversion.
• Hexagonal: emphasizes ports & adapters — think of core exposing ports and everything else being adapters. It’s focused on input/output boundaries rather than strict concentric layers.

---

When to choose which

• Small/Medium app / DDD approach — Onion or Clean both work well; pick the vocabulary your team prefers.
• Many different input/output channels (CLI, REST, event bus, scheduled jobs) — Hexagonal is a natural fit because it models ports/adapters explicitly.
• Strict separation and testability — All three help, but Hexagonal makes adapter-swapping explicit which is great for testing with fakes.

---

Mapping to DDD concepts (your earlier list)

• Aggregates: live in Domain (core). Repositories in Application or Domain define interfaces that operate on Aggregates.
• Repositories: interface (port) in Domain or Application layer; implementation in Infrastructure/Adapters.
• Domain Events: defined in Domain; published from Aggregates; handled by handlers in Application or Infrastructure (depending on side-effects).
• DTOs: used at outer layers (API/presentation) to transport data in/out. Map to/from domain objects in Interface Adapters / Controllers.
• Bounded Contexts (BC): each BC can be its own Clean/Onion/Hexagonal application — maintain separate domain models and services; integration via well-defined anti-corruption layers or translation adapters.

---

Concrete interview-ready comparisons (table)

Concern	Clean	Onion	Hexagonal
Core idea	Inner business rules, outer frameworks	Domain-first rings	Ports (interfaces) and adapters
Dependencies	Inward, DI + interfaces	Inward, domain-centric	Core depends only on ports
Where repos live	Interface in inner, impl outer	Interface inner, impl outer	Port in core, adapter implements port
Best for	General large apps	Domain-driven design	Systems with many I/O channels
Testability	Excellent	Excellent	Excellent + explicit adapter fakes
Typical complexity	Medium	Medium	Slightly higher modeling upfront

---

Extra: short, realistic example — where to put code

• Domain (MyApp.Domain)

• Order, OrderItem, Money (value object)
• OrderPlacedEvent
• IOrderRepository (or Ports/OrderRepository in Hexagonal)

• Application (MyApp.Application)

• Use-cases: PlaceOrder, CancelOrder
• Domain event dispatching orchestration (or decoupled into a DomainEvents mechanism)

• Infrastructure (MyApp.Infrastructure)

• EfOrderRepository implements IOrderRepository
• EmailSender implements IEmailSender

• API / UI (MyApp.Api)

  • Controllers, DTOs, mappers to domain

• Composition Root

  • Wire DI: register repositories, event bus, mapper, use-cases

---

Practical tips / gotchas

1. Don't put EF attributes in domain objects if you want a pure domain model. If you prefer convenience, accept slight coupling.
2. Keep domain logic inside domain (rich model) and avoid anemic models that move rules into services.
3. Define repository interfaces in the domain (or core) so implementations can be swapped.
4. Treat DTOs as translation objects — no business logic in DTOs.
5. Bounded Contexts: prefer separate projects/apps when models diverge significantly — use anti-corruption layers for translations.
6. Start pragmatic: very small projects may be over-architected if you create many projects — aim for clarity and testability rather than perfect structure.

Architecture - .NET Project Architecture Design Framework

🧭 Step 1: Understand the Business and Technical Requirements

🧩 Step 2: Choose the Right .NET Application Type

🧱 Step 3: Select an Architecture Style

🧠 Step 4: Define Solution Structure (Clean Architecture Example)

⚙️ Step 5: Choose Technologies

🧰 Step 6: CI/CD with AWS DevOps

🔒 Step 7: Security & Compliance

🧪 Step 8: Testing, Quality & Observability

📘 Step 9: Documentation & Governance

🔁 Step 10: Iterate and Improve

🧭 Step 1: Understand the Business and Technical Requirements

Before starting, gather and document:

• Functional and non-functional requirements.
• User personas, traffic expectations, and performance needs.
• Compliance, security, and availability goals.
• Integration needs with internal systems or third-party APIs.

🎯 Output: A clear understanding of system goals and constraints.

---

🧩 Step 2: Choose the Right .NET Application Type

Application Type	Framework / Tech Stack	Use Case
Web API / Microservice	ASP.NET Core Web API	Backend REST APIs, integrations
Web App (UI)	ASP.NET Core MVC / Razor Pages / Blazor	Full-stack web apps
Background Processing	Worker Service / AWS Lambda	Jobs, scheduling, event processing
Desktop App	WPF / WinUI / MAUI	Desktop or cross-platform apps
Cloud-Native App	ASP.NET Core + Containers (Docker, ECS, EKS)	Scalable distributed systems

🎯 Output: Application type and high-level stack selection.

---

🧱 Step 3: Select an Architecture Style

Architecture	Description	Use When
Layered (N-tier)	Simple separation into UI, business, and data layers.	Small to medium monoliths.
Clean / Hexagonal / Onion	Domain-focused, testable, decoupled.	Modern enterprise solutions.
Microservices	Independent, API-based services.	Large, distributed applications.
Modular Monolith	Monolith organized into modules.	Mid-sized apps; future-ready.
Event-driven	Uses AWS SQS/SNS/EventBridge for async comms.	Real-time or decoupled systems.

💡 Recommendation: Start with Clean Architecture for modularity and maintainability.

---

🧠 Step 4: Define Solution Structure (Clean Architecture Example)

src/

├── Presentation (API/UI)

│ └── Controllers, Views

├── Application

│ └── Business logic, CQRS, DTOs, Validation

├── Domain

│ └── Entities, Value Objects, Domain Events, Interfaces

├── Infrastructure

│ └── EF Core, AWS SDK integrations, Logging, External Services

└── Tests

└── Unit, Integration, and API tests

Dependency flow: Presentation → Application → Domain → Infrastructure (implementing domain interfaces)

---

⚙️ Step 5: Choose Technologies

Backend 

Framework: .NET 8 (LTS)

API: ASP.NET Core Web API / Minimal API

ORM: Entity Framework Core / Dapper

Authentication: JWT, Cognito, or OAuth2

Validation: FluentValidation

Mapping: AutoMapper

Frontend (optional):

React, Angular, Blazor, or Razor Pages

Communicate via REST/gRPC

Database

Amazon RDS (SQL Server, PostgreSQL)

DynamoDB (NoSQL)

EF Core Migrations for schema evolution

Caching

Amazon ElastiCache (Redis)

Messaging / Events

AWS SQS, SNS, EventBridge, or Kinesis Streams

File Storage

Amazon S3

Logging & Monitoring

ILogger (built-in), Serilog, Amazon CloudWatch, X-Ray

---

🧰 Step 6: CI/CD with AWS DevOps

• Version control: Git (GitHub / CodeCommit)
• CI/CD: AWS CodePipeline, CodeBuild, GitHub Actions or Harness
• Stages:
• Build and test
• Static analysis (SonarQube / Checkmarx)
• Deploy to dev/test/prod
• Infrastructure as Code (IaC): AWS CloudFormation / Terraform
• Container orchestration: ECS or EKS (Kubernetes)

---

🔒 Step 7: Security & Compliance

• Use AWS Identity and Access Management (IAM) for roles and permissions.

• Secure secrets via AWS Secrets Manager or Parameter Store.

• Enable HTTPS using AWS Certificate Manager.

• Apply OWASP Top 10 principles and encryption at rest (KMS).

---

🧪 Step 8: Testing, Quality & Observability

• Testing: Unit, Integration, API, and Performance tests.

• Static Code Analysis: SonarQube / Checkmarx.

• Observability: CloudWatch, X-Ray, Serilog.

• Metrics: Track latency, throughput, and error rates.

---

📘 Step 9: Documentation & Governance

• Document APIs using Swagger/OpenAPI.

• Maintain Architecture Decision Records (ADRs).

• Use consistent Git branching and code review practices.

• Reassess architecture periodically for improvements.

---

🔁 Step 10: Iterate and Improve

• Start with MVP, evolve as usage grows.

• Review scaling patterns regularly.

• Encourage feedback and innovation from the team.

---

🧱 Clean Architecture Overview

+---------------------------+

| Presentation |

| (Controllers / API Layer) |

+------------+--------------+

↓

+---------------------------+

| Application |

| (Use Cases, CQRS, DTOs) |

+------------+--------------+

↓

+---------------------------+

| Domain |

| (Entities, Interfaces) |

+------------+--------------+

↓

+---------------------------+

| Infrastructure |

| (EF Core, AWS SDK, etc.) |

+---------------------------+

---

✅ Summary Principles

Principle	Description
SOLID	Maintainable and scalable design
KISS & DRY	Simplicity and no duplication
Dependency Inversion	Depend on abstractions
Separation of Concerns	Isolated business logic
Testability	Unit and integration ready
Scalability & Resilience	AWS-native scaling and fault tolerance

---

Outcome: A scalable, testable, and secure .NET 8 application leveraging AWS-native services for CI/CD, observability, and automation.

Dotnet Core - Dependency Injection

Dependency Injection (DI) is a design pattern that allows a class to receive its dependencies from external sources rather than creating them internally.

It’s part of the broader Inversion of Control (IoC) principle — meaning:
Instead of your class controlling its dependencies, something else (the DI container) provides them.

---

🔍 Simple Example (Without DI)

public class NotificationService
{
    private readonly EmailService _emailService;

    public NotificationService()
    {
        _emailService = new EmailService(); // tightly coupled
    }

    public void SendNotification(string message)
    {
        _emailService.SendEmail(message);
    }
}

Problem:

• NotificationService is tightly coupled to EmailService.

• If you want to switch to SmsService, you must modify and recompile this class.

---

✅ With Dependency Injection

public interface IMessageService
{
    void SendMessage(string message);
}

public class EmailService : IMessageService
{
    public void SendMessage(string message)
    {
        Console.WriteLine($"Email sent: {message}");
    }
}

public class NotificationService
{
    private readonly IMessageService _messageService;

    // Dependency injected via constructor
    public NotificationService(IMessageService messageService)
    {
        _messageService = messageService;
    }

    public void Notify(string message)
    {
        _messageService.SendMessage(message);
    }
}

Now, the class depends on an abstraction (interface) — not a concrete implementation.

---

⚙️ How .NET Core Implements DI

.NET Core has a built-in dependency injection container — you don’t need external libraries like Autofac or Ninject (though you can still use them if needed).

You register your services in the Startup.cs (for .NET Core 3.1) or Program.cs (for .NET 6/7/8).

---

🧩 Example: Registering Services in .NET 6+

var builder = WebApplication.CreateBuilder(args);

// Register services with DI container
builder.Services.AddTransient<IMessageService, EmailService>();
builder.Services.AddScoped<NotificationService>();

var app = builder.Build();

app.MapGet("/notify", (NotificationService notification) =>
{
    notification.Notify("Hello from DI!");
    return "Notification sent!";
});

app.Run();

---

🧱 Service Lifetime Scopes in .NET Core

When registering dependencies, you choose their lifetime — how long they live in memory.

Lifetime	Description	Example Use Case
Transient	Created each time they are requested.	Lightweight, stateless services.
Scoped	Created once per request (HTTP request).	Web API services, database context.
Singleton	Created only once for the entire app lifetime.	Configuration, caching, logging.

Example:

builder.Services.AddTransient<IEmailService, EmailService>();   // new every time
builder.Services.AddScoped<IUserRepository, UserRepository>();  // per HTTP request
builder.Services.AddSingleton<ILogger, ConsoleLogger>();        // one shared instance

---

🧩 How Dependencies Are Injected

.NET Core supports 3 injection methods:

Type	Description	Example
Constructor Injection	Most common — dependencies passed via constructor.	public MyClass(IMyService service)
Method Injection	Dependencies passed directly into method.	void MyMethod(IMyService service)
Property Injection	Dependencies assigned to public property (less common).	public IMyService MyService { get; set; }

---

💡 Example in ASP.NET Core Controller

[ApiController]
[Route("api/[controller]")]
public class UserController : ControllerBase
{
    private readonly IUserService _userService;

    // Constructor Injection
    public UserController(IUserService userService)
    {
        _userService = userService;
    }

    [HttpGet("{id}")]
    public IActionResult GetUser(int id)
    {
        var user = _userService.GetUserById(id);
        return Ok(user);
    }
}

And in Program.cs:

builder.Services.AddScoped<IUserService, UserService>();

---

🧩 Real-Life Analogy

Think of DI like ordering coffee ☕:

• You (the controller) need coffee (a dependency).

• Instead of making it yourself (creating new CoffeeMaker()), you ask the barista (DI container) to provide one.

• The barista knows which coffee maker to use (EmailService, SmsService, etc.).

• You just consume it — no need to know how it’s made.

---

🧰 Benefits of Dependency Injection

✅ Loose coupling – Easier to swap implementations.
✅ Better testability – Mock dependencies in unit tests easily.
✅ Simpler maintenance – Fewer code changes when dependencies evolve.
✅ Centralized configuration – All service wiring is in one place.
✅ Improved scalability – Encourages modular architecture.

---

🧪 Example: Unit Testing with DI

public class NotificationTests
{
    [Fact]
    public void ShouldSendNotificationUsingEmail()
    {
        var mockMessageService = new Mock<IMessageService>();
        var notificationService = new NotificationService(mockMessageService.Object);

        notificationService.Notify("Test");

        mockMessageService.Verify(m => m.SendMessage("Test"), Times.Once);
    }
}

---

.Net Framework Vs .Net Core

1. What They Are

Platform	Description
.NET Framework	The original .NET platform released by Microsoft in 2002. It runs only on Windows and is used for building desktop (WPF, WinForms) and web (ASP.NET) apps.
.NET Core	A modern, cross-platform, open-source reimplementation of .NET, introduced in 2016. Runs on Windows, Linux, and macOS, designed for cloud and container environments.

---

2. Platform Support

Feature	.NET Framework	.NET Core
OS Support	Windows only	Cross-platform (Windows, Linux, macOS)
Deployment	Installed system-wide (via Windows Update)	Can be installed per app (self-contained)
Container Support	Limited	Fully supported (Docker/Kubernetes friendly)
Mobile / IoT / Cloud	Not supported directly	Supported via .NET (Core → 5/6/7/8) ecosystem

Summary: .NET Core is built for modern, cloud-native and cross-platform development.

---

3. Runtime & Architecture

Area	.NET Framework	.NET Core
Runtime	Common Language Runtime (CLR)	CoreCLR (lightweight, modular)
Base Class Library (BCL)	Windows-specific APIs	Modular libraries (System.* NuGet packages)
Compilation	JIT (Just-In-Time) only	JIT + AOT (Ahead-of-Time) with ReadyToRun support
Performance	Heavier, slower startup	Optimized for speed and scalability
App Isolation	Shares runtime	Each app can have its own runtime version

Summary: .NET Core uses a modular, faster, and isolated runtime.

---

4. Application Models Supported

Application Type	.NET Framework	.NET Core
ASP.NET Web Forms	✅ Yes	❌ No
ASP.NET MVC / Web API	✅ Yes	✅ Rebuilt as ASP.NET Core
WPF / Windows Forms	✅ Yes	✅ Yes (Windows-only starting .NET Core 3.0+)
Console Apps	✅ Yes	✅ Yes
Windows Services	✅ Yes	✅ Yes (.NET 6+)
Cross-platform (Linux/Mac)	❌ No	✅ Yes
Blazor / MAUI / Minimal APIs	❌ No	✅ Yes

Summary: .NET Core adds support for new app models and modern architectures like microservices and serverless.

---

5. Package & Dependency Management

Feature	.NET Framework	.NET Core
Package Manager	GAC (Global Assembly Cache) + NuGet	NuGet only
Deployment	Shared assemblies (can cause version conflicts)	Self-contained or framework-dependent
Versioning	Machine-wide	App-local, side-by-side

Summary: .NET Core eliminates the old “DLL Hell” problem — each app can carry its own dependencies.

---

6. CLI Tools & Development Experience

Feature	.NET Framework	.NET Core
Command-line Tools	Limited	dotnet CLI powerful toolchain
Build System	MSBuild only	MSBuild + cross-platform CLI
Project Format	.csproj (verbose XML)	Simplified .csproj (SDK-style)
IDE Support	Visual Studio (Windows only)	VS, VS Code, Rider (cross-platform)

Summary: .NET Core offers a modern, developer-friendly toolchain with CLI-first design.

---

7. Open Source & Community

Feature	.NET Framework	.NET Core
Open Source	Partially (reference source only)	Fully open source (MIT License)
Development	Microsoft-only	Microsoft + .NET Foundation community
Source Code	Not on GitHub	100% on Github

Summary: .NET Core is open, transparent, and community-driven.

---

8. Performance

Area	.NET Framework	.NET Core
Startup	Slower	Faster
Throughput	Moderate	Optimized
Memory Footprint	Higher	Lower
Async & Parallelism	Legacy support	Native async-friendly design
Container Startup	Poor	Excellent

Summary: .NET Core’s runtime and libraries are optimized for microservices and high-performance workloads.

---

9. Future & Support Lifecycle

Feature	.NET Framework	.NET Core / .NET 5+
Active Development	Maintenance mode only	Ongoing (current: .NET 8, .NET 9 soon)
New Features	❌ No new features	✅ Continuous updates
End of Life	4.8 is the last major version	Unified platform (Core → 5 → 6 → 7 → 8...)

Summary:
➡️ .NET Framework = Legacy (maintenance only)
➡️ .NET Core / .NET 5+ = Future of .NET

---

10. Real-world Example

Scenario	Use .NET Framework	Use .NET Core / .NET 6+
Maintaining an old enterprise ASP.NET Web Forms app	✅	❌
Building a new cross-platform Web API	❌	✅
Deploying to Linux or Docker	❌	✅
Creating a modern microservices architecture	❌	✅
Integrating with legacy Windows-only components	✅	❌ (or limited)

---

Summary Table

Feature	.NET Framework	.NET Core / .NET 6+
Platform	Windows only	Cross-platform
Open Source	Limited	Fully open source
Performance	Moderate	High performance
Deployment	System-wide	Self-contained
Future	Legacy	Active development
App Models	Limited	Modern (Blazor, MAUI, etc.)

---

Final Takeaway

• .NET Framework → Best for existing legacy apps that run on Windows only.

• .NET Core / .NET 6+ → The future of .NET: cross-platform, open-source, high-performance, and cloud-ready.

AWS - Elastic Cache

Amazon ElastiCache is a fully managed, in-memory caching service that helps you speed up application performance by retrieving data from a fast, managed cache instead of repeatedly querying a slower database (like RDS or DynamoDB).

In short: It’s like keeping your most frequently used data in RAM, so your apps can access it within microseconds instead of milliseconds.

How It Works

Normally, your app talks directly to a database:

App → Database → Response (slow)

With ElastiCache, you add a caching layer:

App → ElastiCache (cache hit → super fast)
     ↓
     Database (cache miss → slower, then store in cache)

This pattern is called “Cache-aside” (lazy loading).

Core Components

Component	Description
Cache Cluster	A collection of one or more cache nodes (instances).
Cache Node	A single in-memory instance (like an EC2 instance, but optimized for caching).
Parameter Group	Defines runtime settings (similar to DB parameter groups).
Subnet Group	Defines which subnets your cache can run in (for VPC).
Replication Group	Manages primary/replica nodes for high availability (Redis only).
Engine	ElastiCache supports Redis and Memcached.

---

Supported Engines

Redis

• Open-source, key-value data store with advanced features.

• Supports:

  • Data persistence

  • Pub/Sub messaging

  • Replication and failover

  • Cluster mode for sharding

  • Encryption and authentication

Best for: real-time analytics, session stores, leaderboards, caching with persistence

---

Memcached

• Simple, in-memory key-value store designed purely for caching.

• No persistence, no replication, no complex data structures.

• Scales horizontally by adding/removing nodes.

Best for: simple caching, ephemeral data, distributed caching

---

Redis vs Memcached Comparison

Feature	Redis	Memcached
Data Structures	Strings, lists, sets, sorted sets, hashes, bitmaps, streams	Strings only
Persistence	Yes (RDB, AOF)	No
Replication	Yes	No
High Availability (Multi-AZ)	Yes	No
Cluster Mode	Yes (sharding)	Yes (client-side)
Pub/Sub Messaging	Supported	No
Use Case	Caching + real-time analytics + message queues	Simple, fast caching

---

Common Caching Patterns

Pattern	Description
Cache-aside (Lazy loading)	App checks cache first → if data missing → fetch from DB → store in cache
Write-through	Data written to cache and DB simultaneously
Write-behind	Data written to cache first → asynchronously written to DB
Session store	Store user session data (Redis supports TTLs)
Pub/Sub	Redis channels used for message broadcasting

---

Example Architecture: RDS + ElastiCache + Application

Let’s walk through a common real-world architecture.

Use Case:

Your application reads product details from an RDS database frequently. To reduce latency and DB load, you introduce an ElastiCache Redis cluster.

---

Flow

1. User requests product info → App Server checks ElastiCache Redis.

2. If cache hit, return instantly from cache (fast).

3. If cache miss, app queries RDS, then stores the result in Redis for next time.

4. Optional: Set TTL (Time-to-Live) to expire old cache data.

---

Architecture Components

Component	Role
Application (EC2 / ECS / Lambda)	Queries Redis for frequently accessed data
ElastiCache (Redis Cluster)	In-memory cache, primary + replicas for HA
Amazon RDS (MySQL/PostgreSQL)	Persistent storage for data
Amazon CloudWatch	Monitors cache metrics (CPU, memory, evictions)
IAM + Security Groups	Restrict access (only app servers can access cache)

---

Architecture Diagram (text form)

                +-------------------------+
                |     Application Tier    |
                |  (EC2 / ECS / Lambda)   |
                +-----------+-------------+
                            |
                            | (Check cache first)
                            v
                  +------------------+
                  | ElastiCache Redis|
                  |  In-memory cache |
                  +--------+---------+
                           |
                (Cache miss → Query DB)
                           |
                           v
                    +--------------+
                    | Amazon RDS   |
                    | MySQL / Postgres |
                    +--------------+

---

Key Benefits

Performance: Sub-millisecond latency
Scalability: Easily scale in/out
Cost saving: Reduce database load & cost
High availability: Multi-AZ + automatic failover
Managed: AWS handles patching, backups, and monitoring

---

Example (Boto3 – Python)

import redis

# Connect to Redis cluster
r = redis.StrictRedis(
    host='mycachecluster.xxxxxx.ng.0001.use1.cache.amazonaws.com',
    port=6379,
    decode_responses=True
)

# Check cache
value = r.get("product:123")

if not value:
    # Simulate DB query
    value = "Product data from DB"
    # Store in cache for 1 hour
    r.setex("product:123", 3600, value)

print(value)

---

When to Use ElastiCache

Use ElastiCache when you need:

• Sub-millisecond access to frequently read data

• To reduce pressure on databases (RDS, DynamoDB)

• To store session or stateful data for apps

• To implement leaderboards, counters, or pub/sub systems

• To scale real-time analytics dashboards

---------------------------------------------------------------------------------------------------------------------------

Here’s a description of an architecture diagram for Amazon ElastiCache (Redis) integrated with an application and RDS:

Title: Amazon ElastiCache Integration Architecture

Components:

1. User / Client

   • Initiates request to the application.

2. Application Tier (EC2 / ECS / Lambda)

   • Receives user requests.

   • Checks the ElastiCache Redis cluster for cached data.

   • If data exists (cache hit), returns immediately.

   • If data does not exist (cache miss), queries RDS and then stores result in cache.

3. Amazon ElastiCache (Redis Cluster)

   • Acts as in-memory cache layer.

   • Stores frequently accessed data with TTL (Time-to-Live).

   • Optional: Redis replicas for high availability.

4. Amazon RDS (MySQL / PostgreSQL)

   • Persistent data storage.

   • Queried only on cache misses.

5. Amazon CloudWatch

   • Monitors cache and database performance metrics (CPU, memory, connections, evictions).

6. IAM & Security Groups

   • Restrict access between application, cache, and database.

Data Flow:

1. User request → Application Tier

2. Application → Check ElastiCache Redis

   • Cache Hit → Return Data

   • Cache Miss → Query RDS → Store Data in Redis → Return Data

3. Monitoring and metrics via CloudWatch.

Diagram Layout :

Optional Enhancements:

• Multi-AZ Redis replication group.

• Read replicas in RDS for read-heavy workloads.

• Redis cluster mode enabled for sharding large datasets.

This architecture provides high performance, scalability, and reduced database load using ElastiCache as an in-memory caching layer.