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FinTech
Amazon S3, Amazon Lambda, AWS EventBridge, AmazonRDS, Amazon ECS, Amazon VPC
Modernized mainframe batch workloads into a scalable cloud-native platform with enhanced speed and operational visibility.
A Fintech Client is a leading data and analytics organization providing credit information and decisioning services across India. The organization processes large-scale batch workloads to support regulatory reporting, analytics, and mission-critical data operations. These workloads historically ran on IBM Mainframe systems to process millions of records within defined batch windows.
Reduction in Operational Costs
Millions of Records Processed
Cloud-Native Foundation
The existing IBM Mainframe-based batch processing platform struggled with high costs, long execution windows, limited scalability, and a rigid monolithic architecture that restricted modernization, automation, and operational visibility.
• Migrated legacy IBM Mainframe batch jobs to AWS
• Containerized batch workloads using Amazon ECS for scalable execution
• Used Amazon S3 for durable and cost-effective storage of batch inputs and outputs
• Implemented AWS Lambda for event-driven orchestration, validations, and post-processing
• Enabled parallel execution to significantly reduce batch processing time
• Integrated monitoring, logging, and alerting using native AWS services
• Designed fault-tolerant workflows with automated retries and error handling
• Applied AWS security best practices to ensure compliance and data integrity
Attained 80% reduction in operational costs, faster batch execution, elastic scalability for millions of records, and improved monitoring through a cloud-native, future-ready batch processing platform.
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