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Mainframe Modernization Without the Mayhem: How One Global Bank Cut Costs by 90% with Ververica

Steve Tyler Free Content

Mainframe Modernization Without the Mayhem: How One Global Bank Cut Costs by 90% with Ververica

Summary

A top-tier global bank used Ververica’s Unified Streaming Data Platform to offload selected, high-volume workloads from an IBM mainframe to a modern, cloud-native streaming architecture. The move took around three weeks and delivered dramatic results: a 90% reduction in mainframe processing costs (saving over $1m annually) and a 60% reduction in job runtime. The bank now streams millions of events per second with sub-second latency, turning batch jobs that once ran for eight hours into processes finishing in under three.

The solution combined Change Data Capture (CDC) and JDBC connectors to extract transactional data from VSAM/mainframe sources, refactored critical COBOL logic into Java, and routed processed streams to Azure Blob Storage and Kafka. Apache Flink (via Ververica) provided stateful, exactly-once, low-latency processing at scale, with plans to adopt Apache Paimon for lakehouse analytics. Security and compliance controls (encryption, RBAC, SSO/LDAP, auditing, data masking) were highlighted as part of the enterprise-grade setup.

Source

Source: https://www.cmswire.com/customer-experience/mainframe-modernization-without-the-mayhem-how-one-global-bank-cut-costs-by-90-with-ververica/

Key Points

  • Selective mainframe offloading — not rip-and-replace — allowed the bank to preserve critical legacy systems while modernising time-sensitive workloads.
  • 90% cut in mainframe processing costs (over $1m saved annually) and 60% faster job runtimes after migration to Ververica’s streaming platform.
  • CDC and JDBC connectors extracted transactional data from VSAM/mainframe sources into event streams processed by Apache Flink for sub-second latency.
  • Refactoring key COBOL logic into Java made business rules maintainable, testable and easier to evolve in a modern stack.
  • Architecture integrates with Kafka, Azure Blob Storage and plans for Apache Paimon — enabling durable storage, event-driven workflows and lakehouse analytics.
  • Ververica/Flink provides exactly-once semantics, checkpointing and stateful processing to preserve data integrity and mainframe-grade reliability.
  • Enterprise security features included end-to-end encryption, RBAC, LDAP/SSO integration, audit logs and data-masking to meet regulatory needs.
  • Success metrics: reduced MIPS consumption, sub-second latency, improved throughput, faster time-to-market and continuous fraud detection.

Why should I read this?

Short version: if you’re stuck with costly mainframe cycles but can’t risk a full rip‑and‑replace, this is the playbook you want. It shows a quick, low‑risk route to big savings, real‑time processing and better fraud detection — without torching the systems that still work. We’ve saved you the slog: three weeks to proof, huge cost wins, and a sensible hybrid architecture to copy.

Context and Relevance

Banks and other regulated organisations face rising customer expectations, regulatory pressure and competition from nimble fintechs. Mainframes remain reliable for core transactional integrity but falter on latency, agility and cost. This case demonstrates a pragmatic industry trend: selective modernisation via streaming and cloud‑native platforms that offload event‑driven workloads, lower total cost of ownership and enable real‑time services. The approach is relevant to any organisation that needs mainframe reliability but wants fintech‑style responsiveness.

Author / Voice

Punchy, action‑focused: Ben Gamble (Field CTO, Ververica) frames this as a practical, technically sound pattern for immediate impact — especially useful for technical leaders weighing cost, risk and speed in legacy modernisation projects.