Extended write-up: This project challenged me to optimize rendering performance for large datasets. I implemented virtualized lists and WebGL-accelerated charting to maintain 60fps during high-volatility market events.
The project required orchestrating several services, including MySQL, PostgreSQL, Redis, RabbitMQ, and DynamoDB Local, alongside the retail-store microservices. One of the main challenges was ensuring that these services communicated correctly within the cluster while maintaining high availability and scalability. To address this, I provisioned the entire infrastructure using Terraform, implementing Infrastructure as Code with remote state stored securely in S3 and DynamoDB for state locking. This approach allowed the infrastructure to be consistently reproducible across environments while adhering to best practices in cloud automation.
To streamline deployments, I set up GitHub Actions workflows that automated the CI/CD pipeline. Pull requests were validated, formatted, and planned automatically, while pushes to the main branch triggered automated application of Terraform configurations. This workflow minimized manual intervention, reduced errors, and ensured that updates to the infrastructure were deployed safely and predictably. Additionally, I created a dedicated read-only IAM user for developers, mapped into the EKS cluster, so that they could monitor and view resources without the ability to alter production workloads. This added a critical layer of security while maintaining transparency for the team.
Through Project Bedrock, I gained hands-on experience in orchestrating complex microservices environments on Kubernetes, automating infrastructure provisioning, and implementing scalable CI/CD pipelines. The project not only demonstrated my ability to build professional, production-ready cloud infrastructure but also allowed me to document the process clearly for other developers. The repository was structured to be beginner-friendly, providing step-by-step guidance on deploying a real-world application using EKS, Terraform, and GitHub Actions.
Overall, Project Bedrock sharpened my skills in cloud automation, container orchestration, infrastructure as code, and DevOps practices, while reinforcing the importance of scalability, security, and maintainability in cloud engineering projects. This deployment showcases my capability to take on complex cloud initiatives and deliver solutions that are both technically sound and aligned with real-world production standards.
