Cloud-Native Scalable Application

Inspiration

We were inspired by the challenges faced by applications when user traffic suddenly increases. Server overload, unexpected downtime, and database bottlenecks can affect the user experience. We wanted to explore how cloud-native technologies can help applications remain scalable, available, and reliable, even under heavy traffic.

What We Learned

Through this project, we explored important cloud-native concepts such as horizontal scaling, load balancing, auto scaling, database scalability, real-time monitoring, and fault recovery. We also learned how these components work together to improve application performance and availability.

How We Built It

We designed a lightweight Task Management Application as the foundation of our project. Our proposed architecture includes multiple application instances behind a load balancer, an auto-scaling mechanism, and a scalable database with read replicas and Redis caching.

We also planned a monitoring dashboard using Prometheus and Grafana to track server health, CPU usage, request rates, response times, and error rates. Our architecture includes automated health checks and instance replacement to support fault recovery.

Challenges We Faced

One of our main challenges was understanding how to design a system that can handle sudden traffic spikes without affecting performance. We also had to consider how to distribute requests efficiently, avoid database bottlenecks, and recover from server failures.

Designing an architecture that combines all these components into one scalable system helped us understand the importance of planning and coordination in cloud-native development.

What's Next

Our next step is to implement and test the proposed architecture under different workloads. We aim to evaluate its performance during normal traffic, heavy traffic, and simulated server failures.