## 5 Research Results
### Case Study: Development of the Blockchain-Based NFT Trading Web 3.0 Application
The WordPress REST API supports pagination and versioning, and pagination was implemented by passing the page and per_page query parameters to the API. The next step was hosting on the cloud using AWS, and the installation was deployed on a LAMP stack. This is given in the following infrastructure diagram. [Client Requests]-[API Gateway (Optional)]-[Web Server (WordPress on LAMP Stack)]-[MySQL Database]  
In the third sprint, the developed microservices were deployed in a cloud-native environment. This was accomplished using Docker, Kubernetes, and a CI/CD pipeline on GitHub. Microservices were containerized using Docker, which ensured that all dependencies were consistent. The containerized microservices were deployed in a Kubernetes cluster for automatic scaling. Here is a snippet of the Kubernetes deployment YAML file used to deploy the User Management Service. apiVersion: apps/v1  
kind: Deployment metadata:  
name: user-management-service  
labels: app: nft-marketplace service: user-management  
spec: replicas: 2  
selector: matchLabels:  
app: nft-marketplace service: user-management  
Figure 3: The relationships and interactions between microservices. A CI/CD pipeline was set up using GitHub actions to automate the build, test, and deployment process for each microservice. This reduced manual intervention and ensured that updates were deployed quickly and consistently across environments. To measure the effects of the case study development, a set of quantitative metrics was used to generate measurable results and demonstrate the benefits of this approach (Table 7). Several key values were tested, including functional correctness, performance, scalability, uptime, and security. Functional correctness was essential to verify that the API endpoints, user operations, and microservices performed as expected, while performance tests measured response times and throughput under varying traffic loads to ensure smooth operation at scale. Scalability was tested to validate the effectiveness of Kubernetes' Horizontal Pod Autoscaler (HPA) in handling increased demand, while uptime tests ensured continuous availability, even during rolling updates. Finally, security tests were conducted to identify and mitigate vulnerabilities. Each of these values is critical to delivering a robust, user-friendly, and scalable NFT marketplace. The results show that the microservices architecture implemented in Sprint 1 proved highly effective in terms of functional correctness (96% success rate), scalability, and security. The Marketplace Service was the most affected during high traffic (1000 users), though scaling improved performance by 25%. During the tests, the system maintained 99.8% uptime, with effective self-healing capabilities through Kubernetes. Security testing showed robust authentication and protection mechanisms, with no critical vulnerabilities detected. The API design and cloud deployment in Sprint 2 demonstrated strong performance across all presented metrics, including scalability, uptime, and CI/CD automation. The system handled up to 1250 concurrent users before significant performance degradation, with auto-scaling ensuring a 33% of performance improvement under high load. The rolling updates ensured high availability, with 99.98% of uptime, and the CI/CD pipeline enabled efficient and frequent deployments. Security testing revealed no critical vulnerabilities. Finally, the cloud-native deployment using Kubernetes in Sprint 3 demonstrated the platform's ability to scale effectively using Horizontal Pod Autoscaler (HPA), with the system handling up to 2500 concurrent users before significant performance degradation. Rolling updates ensured 99.99% of uptime, and the CI/CD pipeline was efficient, with each build and deployment taking approximately 5 min. The platform showed a 36% of