Insights
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Legacy, Meet Cloud Native: Lessons from Blending COBOL, K8s, and ML
Introduction
When people talk about modernization, they often picture “lift and shift,” total rewrites, or big-bang digital transformation. But...
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Building a Smart Feedback Loop: Real-Time Inference on COBOL Logs
Introduction
Modern data pipelines don't stop at processing—they evolve. With our eks_cobol
system running legacy COBOL code on...

Predicting Legacy Failures: Training and Hosting ML Models in SageMaker
Introduction
Legacy systems are infamous for failing silently—or catastrophically—with no early warning signs. In our eks_cobol
...
Preparing COBOL Error Data for Machine Learning in SageMaker
Introduction
COBOL and machine learning may sound like opposites—one was born in the era of punch cards, the other in the age of GPU clusters....
Read moreWhen COBOL Fails: Real-Time Error Management with S3 and JSON
Introduction
In any system that processes large volumes of data, failure is inevitable. And when you're running legacy COBOL applications as part...
Read moreFrom Mainframe to Microservice: Modernizing COBOL Data Processing
Introduction
Legacy systems are the heartbeat of many enterprises, particularly in finance, government, and healthcare. At the center of those...
Read moreBridging Generations: Running COBOL on Kubernetes with EFS
Introduction
In 2025, COBOL is still a critical part of global enterprise operations. Despite being developed over 60 years ago, COBOL continues...
Read moreRevolutionizing Enterprise Data Processing: Modernizing Mainframe Workloads with AI & Kubernetes
Introduction
Large enterprises that continue to rely on mainframe systems encounter several significant challenges. The high...
Read moreThe Future of AI-Augmented Legacy Systems: What Enterprises Need to Know
Enterprises have relied on legacy IT infrastructures—including COBOL-based mainframes—for decades. These systems, while...
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