Legacy Application Modernisation for a UK Not-For-Profit

Customer

A large UK not‑for‑profit union and trade association representing hundreds of member organisations, each with thousands of individual members. The organisation runs a buying consortium that handles high volumes every day across purchasing, inventory allocation and payment syndication.

Situation

Operations relied on a fragmented, 20‑year‑old set of desktop and client‑server applications. The systems needed a lot of manual intervention and could not scale with demand. Staffing costs and complexity kept rising. Several software and hardware components had reached end of life, which created real continuity risks.

Crisis point

When the client came to Arrk, suppliers were chasing payments and members were waiting on inventory. Only a few staff knew how to apply emergency fixes. The legacy setup was no longer sustainable.

Immediate stabilisation

Our first priority was to restore basic function. We temporarily downgraded selected software, operating systems and hardware to known‑stable versions. This returned the platform to a semi‑functional state and gave the client time to plan the modernisation.

Modernisation Objectives

Using Arrk’s Remarrk™ Application Modernisation Framework, we produced a practical roadmap focused on scalability, reliability, security and cost control. The plan moved the client away from a monolith and manual processes to an automated, cloud‑based platform that can grow with the business.

Modernising Legacy Components

Migration Challenges and How We Addressed Them

Older Java Versions and Coding Styles

We used AI‑assisted tools to update the codebase to supported Java versions and modern language features. This sped up refactoring and reduced manual rework. We also used AI to generate and update unit tests to improve coverage.

Monolith to Microservices

The legacy application was a monolith. Using domain‑driven design, we split the system into microservices, each aligned to a specific business area. This improved change isolation and made enhancements easier. AI‑assisted design reviews helped test service boundaries early.

Manual Deployments

We implemented an automated pipeline so builds, tests, security checks and deployments run consistently. This removed bottlenecks and reduced release risk.

Parallel Run & Cutover

Data discrepancies during like‑for‑like testing

Differences appeared during parallel runs due to inconsistent databases. We created a fresh copy of the live database and used it as the single comparison source for side‑by‑side validation.

Daily snapshots and a clean cutover

While both systems ran in parallel, we took a daily snapshot from the live database and loaded it into the new system for test runs. On the planned cutover date, we made the old system unavailable and directed all users to the new platform. Any issues were fixed forward in the new system rather than rolling back.

EmbArrk workshop

Efficient and Faster

Process Automation

Solution

Cloud platform: AWS

Architecture: Event‑driven and container‑based microservices

Compute and integration: AWS Lambda, AWS ECS (containers), API Gateway
Messaging and events: Amazon SQS, Amazon EventBridge
Storage and delivery: Amazon S3, Amazon CloudFront
Communications: Amazon SES

Application layers

Front end: React for a clearer, faster user experience
Back end: Refactored Java codebase using Spring and Spring Boot to integrate with AWS services

Engineering practices

AI‑assisted coding and testing to accelerate refactoring and improve coverage
CI/CD for automated builds, tests, security checks and deployments
Automated backups for SQL Server on AWS

The result is a stable, scalable system aligned with business logic and ready for future change.

EmbArrk workshop

Efficient and Faster

Process Automation

Outcomes

Ongoing Support & Cost Optimisation

To address concerns about cloud cost and security, Arrk provided its Commercial Support Flex Model. The service includes:

Lower monthly cloud infrastructure costs through right‑sizing and automation
High availability and predictable stability
End‑to‑end information security managed by a single team

Stabilised operations during an incident, followed by a planned modernisation
Reduced operational risk by replacing end‑of‑life components and removing key‑person dependencies
Faster change cycles with automated pipelines and microservices
Lower running costs and an improved security posture on AWS