A Cloud Migration Journey from One Region to Another
Explores the strategic migration of a client’s AWS operations from Oregon to Mumbai. With a growing user base exceeding 50,000, the client faced latency issues in real-time data processing for air quality monitoring.
Problem Statement
As our client’s IoT network grew, managing the surge in data became challenging. The AWS infrastructure in Oregon struggled to keep up with the local user base, causing performance issues:
- Data Surge: The expansion of IoT devices caused a massive increase in data volume.
- Infrastructure Mismatch: Existing AWS infrastructure in Oregon couldn’t support the growing local user base.
- Latency Concerns: Increased data transmission distances and system overload led to noticeable latency, impacting user experience.
Additionally, the current infrastructure demanded extensive manual handling, making operations harder and diverting focus from innovation
Latency Issue
Data Management Complexity
Our Solutions
These are the solutions were meticulously crafted to address key pain points and optimize the client’s cloud environment for enhanced performance, scalability, and efficiency
Solution Technical Stack
Our solution leverages a robust technical stack to address the challenges faced during the migration process. The key components of our technical stack include:
- AWS Data Migration Services (DMS)
- AWS Schema Conversion Tool (SCT)
- AWS MGN
- AWS Relational Database Serives (RDS)
- Terraform
- GitHub Actions (CICD)
- AWS Route 53
Final Outcomes
The migration resulted in significant improvements across many aspects of our operations. Transitioning to the Mumbai AWS region resulted in remarkable enhancements:
- Operational Efficiency: Response times decreased by 50%, and data processing speed surged by 40%, enabling us to serve our user base of over 50,000 with unprecedented speed and reliability. Automation played a crucial role in streamlining processes, reducing manual efforts, and ensuring consistent performance.
- Cost Savings: Infrastructure costs were reduced by 30%, facilitating effective resource reallocation and enabling scalability in our efforts to combat air pollution
Reduced Latency
Reduced infrastructure costs
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