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Designing a secure and scalable AWS architecture for public-facing applications experiencing sudden traffic spikes. ๐Ÿ“‚ GitHub repo: SoumyaKhaskel/secure_elastic_WebArchitecture Overview Many small web applications work perfectly under normal traffic but struggle when traffic suddenly increases. The problem often begins with a simple architecture designed around average traffic: A single computeโ€ฆ

Designing a secure and scalable AWS architecture for public-facing applications experiencing sudden traffic spikes is crucial for maintaining performance and availability during unexpected traffic surges. Traditional architectures, which consist of a single compute instance hosting both application and database functions, along with static files served directly from the application server, can quickly become bottlenecks during sudden traffic spikes.

This is due to the lack of flexibility in handling increased load, resulting in higher latency, timeouts, and potential service unavailability. To address these challenges, a proposed AWS architecture focuses on separating the application's major responsibilities into dedicated layers, thereby increasing resilience and scalability.

In this proposed architecture, Amazon Route 53 serves as the DNS layer, directing traffic from users to the application delivery layer. Amazon CloudFront acts as the edge delivery layer, caching static content at edge locations to reduce the number of requests reaching the backend infrastructure and improve response latency for users.

Amazon S3 is used to store static application assets, such as HTML, CSS, JavaScript, and images, thereby decoupling static content delivery from application processing. AWS WAF provides a security control point for incoming application traffic, offering features like web request filtering, managed security rules, rate-based controls, and application-layer protection.

Amazon API Gateway serves as the dynamic request entry point, handling API requests before they reach the application logic and providing controls such as throttling and validation. Finally, AWS Lambda is utilized as an elastic compute layer, allowing for automatic scaling based on the application's demands.

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