Strategic Transformation // Verified

Core Banking: Legacy
Extraction.

De-coupling monolithic mainframe logic into an event-driven AWS microservices mesh to eliminate scaling bottlenecks and accelerate product release cycles by 5x.

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Outcome_TelemetryINFRASTRUCTURE_VERIFIED
60%
OpEx Reduction
Mainframe Costs
Zero
Service Downtime
STRANGLER_FIG
5x
Release Velocity
ROI: 14 Months

Trusted by Leading Fortune 500 Innovators

/// Strategic Context

The Mission: Structural Agility.

Vertical
Retail Banking

Global core banking system processing 10M+ daily transactions on high-cost legacy hardware.

Engagement
Managed Pod

Cloud Architect + Cloud-Native Engineers + DevSecOps Specialist embedded for the full BOT lifecycle.

Objective
Legacy De-coupling

Migrating mission-critical accounting and ledger logic to the cloud without impacting 24/7 availability.

Technology
Event-Driven Mesh

AWS EKS, Kafka-based CDC (Change Data Capture), and Transactional Outbox patterns.

/// The Situation

The Reality Gap: Monolithic Decay.

The client’s core banking logic was trapped within a 20-year-old mainframe. New feature deployment cycles took 6+ months due to the high risk of 'ripple-effect' failures in the brittle COBOL codebase. Scaling for peak holiday traffic required preemptive hardware over-provisioning, costing millions in idle OpEx.

The risk was competitive: digital-only neobanks were out-innovating the client in weeks. The enterprise required a surgical extraction—moving logic to AWS microservices while keeping the mainframe operational as the 'temporary source of truth' during the transition.

Big Bang Failure
A total switch-over was deemed too high-risk by the Board; any downtime would result in severe regulatory fines.
Mainframe Lock-in
MIPS-based pricing from legacy vendors was cannibalizing the technology budget for future AI initiatives.
Talent Scarcity
The aging COBOL workforce was retiring, leaving a widening gap in the ability to maintain the core system.
/// Architecture

The Operational Gates

01
Real-Time CDC Bridge
Implemented Change Data Capture (CDC) to stream mainframe database updates into a Kafka backbone, creating a real-time data shadow in AWS.
Data_Synchronization
MechanismCDC_Stream
ConsistencySub_Second
Tech_StackKafka_Connect
02
Strangler Fig Extraction
Surrounded the legacy core with a 'Proxy Layer' that routed specific functions (e.g., balance inquiries) to new AWS microservices while legacy calls remained on the mainframe.
Logic_Migration
PatternStrangler_Fig
ComputeAWS_EKS
OrchestrationIstio_Service_Mesh
03
Event-Driven Ledger Parity
Utilized Transactional Outbox patterns to ensure that the new AWS ledger and the legacy mainframe remained in 100% parity during the phased rollout.
Ledger_Integrity
AuditAUDIT_TRAIL
PatternOutbox_Pattern
ReliabilityZERO_DOWNTIME
/// The Architecture Shift

The Structural Evolution.

Dimension
Mainframe Monolith
Event-Driven Cloud
Scale Model

Vertical / Static

Expensive, long-term hardware commitments with limited burst capacity.

Horizontal / Elastic

Auto-scaling K8s pods that respond to real-time traffic spikes in milliseconds.

Deployment

Quarterly Releases

Manual, high-risk code freezes required for mainframe updates.

Daily CI/CD

Automated pipelines allow for safe, independent microservice updates multiple times a day.

Data Flow

Batch Processing

End-of-day reconciliation caused delays in real-time customer data updates.

Event Streams

Transactions trigger real-time event notifications across the entire banking ecosystem.

/// The Secret Sauce

Implementation Highlights.

EVENT_DRIVEN

Transactional Outbox Pattern

Ensured atomic updates between microservices and legacy databases to prevent data drift during the multi-year migration window.

Impact // Technical
100% Data Consistency
SOC2_READY

Cloud-Native Governance

Embedded automated IAM policies and encryption at rest/transit to meet Tier-1 banking security requirements on AWS.

Impact // Security
Zero Audit Findings
K8S_OPTIMIZED

Self-Healing Clusters

Implemented automated node recycling and circuit breakers to ensure the new core never experienced a systemic failure.

Impact // Reliability
99.999% Uptime
/// Proprietary Assets

Accelerated by Coretus Kernels™.

Mainframe Bridge Kernel

Pre-built connectors for extracting COBOL-defined data structures into JSON event schemas.

FinOps Guardrails Kernel

Automated resource right-sizing to ensure the cloud core remains 60% cheaper than legacy MIPS.

SRE Telemetry Mesh

Real-time visibility into the 'Strangler Fig' proxy performance to detect latency spikes before customers do.

Ledger Parity Kernel

Reusable validation logic to ensure zero-cent variance between legacy and cloud ledgers.

Extraction_Timeline
45% Faster
Standard Migration24 Months
Coretus BOT13 Months
By deploying our Mainframe Bridge Kernel, we bypassed 6 months of manual data mapping, focusing 100% on logic modernization.
/// Verification

The Performance Delta.

METRIC: COST

Infrastructure Spend

Moving from mainframe licensing to AWS consumption-based pricing yielded immediate OpEx savings.

Legacy MIPS$$$$$
AWS Core60% Lower
↓ 60% OpEx Reduction
METRIC: VELOCITY

Time-to-Market

Microservices allowed product teams to deploy new savings products without mainframe code freezes.

Legacy6 Months
Cloud4 Weeks
↑ 5x Faster Releases
METRIC: RELIABILITY

Migration Downtime

The 'Strangler Fig' pattern ensured that not a single customer session was lost during the extraction.

Target< 0.1%
ActualZero
100% Zero-Downtime
Outcome Status: Performance & Continuity Verified
/// Governance

Operational Integrity.

01
Data Sovereignty
Multi-region AWS residency ensures all banking data remains within regulatory boundaries.
Status: AUDIT_READY
02
Encryption Standards
Hardware-security-module (HSM) based key management for all PII and transaction records.
Status: SOC2_READY
03
SRE Guardrails
Automated failover and self-healing clusters maintain 99.999% availability benchmarks.
Status: K8S_OPTIMIZED
04
Full Knowledge Transfer
Our BOT model ensures the client's internal team is trained to own the AWS core upon completion.
Status: 100% OWNED
Discuss Core Migration
“
Coretus didn't just 'move us to the cloud' — they surgically extracted our core logic while the heart was still beating. We avoided the 'Big Bang' failure everyone feared and achieved a zero-downtime transition that our internal teams now fully own.

Simon Grieg

Chief Technology Officer

/// Structural Synergy

Related Architectural Modernizations.

Art Market Intelligence
90%
Research Efficiency

Art Investment: 100% Fully Automated Intelligence.

The Reality Gap

Human fatigue led to missed undervalued lots during high-volume auction cycles on platforms like Drouot.

The Outcome

Architected independent microservices for secure OAuth2 authentication and anti-bot resilient scraping to extract structured artwork metadata.

INTELLIGENCE_VERIFIED
Explore
Digital Health / B2C
60%
Planning Efficiency

Personalized Nutrition: 60% Faster Meal Planning.

The Reality Gap

Fragmented user journeys created high friction, causing users to drop off after 7 days of manual logging.

The Outcome

Architected the backend into independent services for meal logic, grocery automation, and user profiles to ensure 99.9% availability.

BIO_INTEGRITY_VERIFIED
Explore
Digital Health & Wellness
60%
Time Reduction

Nutrition Planning: 60% Faster AI Automation.

The Reality Gap

Manual meal logging took users an average of 45 minutes daily, resulting in 70% drop-off within the first 14 days.

The Outcome

Engineered functional layers (recommendations, geolocation, auth) as independent services to ensure horizontal scalability.

ECOLOGY_READY
Explore

Kill Technical Debt with Precision.

Stop letting the mainframe throttle your innovation. We engineer event-driven extractions for zero-downtime cloud migrations—securing your core while eliminating legacy OpEx.

Zero-Downtime Strangler Pattern

FinOps Cost Optimization

Full BOT IP Transfer

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