Migration of Financial Data Solutions to AWS
Business Challenge
The organization faced growing challenges in managing its expanding data infrastructure. Its on-premise systems struggled to efficiently process and store vast amounts of real-time financial market data, resulting in delays in data delivery, suboptimal performance, and increased maintenance costs. Additionally, a more agile platform was needed to quickly integrate new services, including advanced analytics and AI-driven insights, to meet client demands for real-time financial data and market intelligence. Scalability, data security, and compliance with financial regulations were key concerns.
JRD Solution
The JRD Systems team implemented an AWS cloud solution to modernize the platform, ensuring scalability, real-time processing, and robust data management while reducing infrastructure overhead. Key AWS services utilized included:
- Amazon EC2: Provisioned scalable virtual servers to handle compute-heavy tasks such as real-time shipment data processing and client reporting. Auto-scaling enabled dynamic adjustments to meet variable workloads, improving cost efficiency.
- Amazon S3: Implemented to store large amounts of unstructured data such as financial records. The scalable nature of S3 ensured the ability to store growing amounts of data without concerns about storage limits.
- AWS Lambda: Used for serverless processing of data pipelines. Lambda automatically triggered the ingestion, transformation, and analysis of real-time financial data streams, enabling faster data delivery without the need to manage servers.
- Amazon RDS: Migrated core databases to Amazon RDS, leveraging its automated scaling, patching, and backups to maintain critical financial data with high availability and compliance. PostgreSQL was used for different workloads, depending on the analytics and reporting needs.
- Amazon CloudWatch: Configured to monitor AWS resources' performance, providing real-time insights into system health, with proactive alerts ensuring minimal downtime and continuous data availability.
- Amazon SNS: Utilized real-time notifications to clients about critical financial updates, regulatory changes, and market shifts, ensuring clients were always informed.
- Amazon SageMaker: Deployed machine learning and predictive analytics to generate advanced insights on market trends, portfolio performance, and risk management. SageMaker’s built-in algorithms enabled the use of AI/ML to better serve clients with actionable financial intelligence.
Key Outcomes
- Scalability: The platform dynamically scaled with business growth.
- Cost Savings: Transitioning to AWS eliminated the need for costly on-premise infrastructure and reduced overhead through serverless computing and auto-scaling services.
- Real-time Insights: Real-time data processing and analytics provide clients with up-to-date information.
- Compliance and Security: AWS’s built-in security features, including encryption and compliance tools, ensured compliance with the strict regulatory requirements of the financial services sector.