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Distributed Link Curation Platform, Modern Cloud Architecture Through Real-World Production Engineering

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As part of a continuous effort to deepen expertise in distributed systems and modern cloud-native architectures, a personal project was developed around a link curation platform inspired by services such as Linktree and lnk.bio. Beyond its functional purpose, the platform served as a practical laboratory for validating security and architectural concepts, deployment strategies, and software quality practices under real production conditions.


Desktop Sample View

Built with React and Next.js, the application leverages widely adopted technologies including Tailwind CSS and Chakra UI, providing a maintainable and scalable front-end architecture while ensuring a consistent user experience. The project was intentionally designed to revisit microservices principles and distributed computing concepts, integrating modern development workflows with platforms such as Vercel and GitHub Actions to automate builds, deployments, and continuous validation processes.


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A strong emphasis was placed on software quality and regression prevention. End-to-end testing with Cypress was employed not only to validate application behavior but also to automatically generate visual snapshots of the interface. These screenshots act as visual baselines, allowing changes introduced by new releases to be compared against previous versions, making it possible to detect unintended UI modifications without relying on a dedicated QA team. Combined with unit and integration tests, this strategy established a highly reliable and fast validation pipeline that significantly reduced the risk of regressions.

The platform also incorporates a distributed media infrastructure based on private Google Cloud Storage buckets. This architecture protects digital assets from unauthorized bulk downloads and abusive behavior. Access patterns are continuously monitored, and automated defensive mechanisms can identify suspicious activity and restrict users whose behavior indicates malicious intent, improving both security and operational resilience.

To optimize performance and reduce bandwidth consumption, the media processing pipeline automatically converts uploaded images into the modern WebP format. Animated content, including GIFs and video files, is transformed into animated WebP assets without audio, resulting in significantly smaller file sizes and faster delivery to end users. This approach minimizes storage and network overhead while improving page load times and overall user experience.

To further improve scalability and runtime efficiency, a Redis-based caching layer was introduced to minimize unnecessary database queries and reduce the overall load on the persistence layer. Frequently accessed data is temporarily stored in memory, allowing the application to serve requests with significantly lower latency. This approach not only improves response times but also enables seamless vertical scaling of containerized application instances, ensuring that additional compute resources can be provisioned without proportionally increasing pressure on the database infrastructure.

The project ultimately became more than a link aggregation tool, it evolved into a production-grade engineering environment where concepts involving microservices, distributed storage, automated quality assurance, CI/CD pipelines, media optimization, and cloud-native operations could be explored and validated through practical implementation.

Checkout the application at https://lnk4st.co to see it by yourself.

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