Infrastructure & Database Migration to AWS for High Performance
- Cloud Development
- Saas
- Vue.js
- MongoDB
- AWS
- Node.js
Overview of Our Client
Our client was a rapidly expanding digital services platform that operated in several regions. As the number of users increased, their existing setup, which was spread across Coolify, Netlify, Hetzner, and MongoDB Atlas on Google Cloud Platform, was no longer able to handle the workloads necessary for daily operations. Their engineering team needed a solution to integrate all the parts into one managed environment without interrupting the ongoing business.
Challenge
The key problem was that the infrastructure was scattered among numerous providers. This resulted in inconsistent performance, increased latency, and more difficult monitoring. Additionally, MongoDB Atlas on GCP posed performance challenges due to strict IOPS limitations, which slowed down large queries or heavy analytics. On top of that, scaling the system in a fragmented manner became both expensive and very risky.
Primary Objectives
The primary objectives of the relocation included:
- To integrate all the applications, services, and databases into AWS, which would make it easier to scale and manage all the parts from a central location.
- To bypass IOPS scaling limitations by migrating MongoDB Atlas from GCP to AWS, enabling configurable performance parameters and higher throughput.
- To conduct the migration in a series of stages, so that the time when the system was not working was reduced to a minimum and data-loss incidents were completely eliminated.
- To get the infrastructure ready for the future increase in load and more sophisticated analytics.
Summary of the Project
We came up with a sequential migration strategy through which the client could move to AWS while maintaining full stability. We first moved the web applications and static assets and put them in a new AWS environment that was configured for future expansion. Having stabilized the application layer, we resolved the database bottleneck issue by relocating MongoDB Atlas clusters from GCP to AWS that offered flexible storage and IOPS tuning.
- Location: Europe
- Sector: Digital Services / SaaS
- Period: 6 months
Solution
As a result, the final infrastructure was a totally integrated AWS ecosystem that had better control, monitoring, and scalability. The applications, databases, and integration services were the entities that benefited from the unified environment with the adjustable resources that matched the real-time demand. IOPS was optimized for MongoDB Atlas clusters on AWS, thus, stable performance was guaranteed for both transactional and analytical operations.
Platform Features
- The client was moved to a centralized AWS infrastructure from Coolify, Netlify, and Hetzner.
- MongoDB Atlas was transferred from GCP to AWS that had customizable IOPS settings.
- Migrating to a unified AWS infrastructure for both application logic and MongoDB Atlas minimized I/O latency and optimized OPEX by cutting out expensive cross-cloud data transfer charges.
- The storage configurations were of the high-throughput kind to be able to accommodate large volumes of reads, writes, and analytic tasks.
- The phased transition plan cut down the time when the system was not working and at the same time removed the migration-related risks.
- Monitoring and logging were the two tasks that were carried out in a unified manner across all environments, hence, the performance visibility was greatly enhanced.
- The architectural design was flexible and scalable, thus it was well prepared for any future load surges and feature expansion.
Technology Stack
We chose the technology stack below to fulfill all the requirements of the project:
Infrastructure
- AWS (EC2, ECS, S3, CloudFront, ELB).
Database
- MongoDB Atlas.
Deployment
- AWS Native CI/CD Suite
- GitHub Actions
Monitoring
- AWS CloudWatch and MongoDB Atlas built-in monitoring and observability tools
Core Team
- Cloud Architect: Responsible for designing the AWS architecture and crafting the migration roadmap.
- Backend Engineer: Oversaw database transition and managed performance tuning.
- Frontend Engineer: Ensured a convenient user experience.
- QA Engineer: Validated system stability, data integrity, and performance at each stage.
- DevOps Engineer: Set up CI/CD, automation, monitoring, and logging.
- Project Manager: Coordinated delivery, timelines, and client communication.
Impact
After completing the migration, the client received a high-performance and fully scalable AWS infrastructure. Service fragmentation, which had led to instability in the previous environment, was eliminated thanks to the unified environment, database throughput significantly increased, and analytical workloads stabilized. The elimination of IOPS limits and the operation of all components on a single cloud platform made the project more resilient, easier to manage, and better prepared for growth.