Legacy system application modernization and cloud-native transformation

Service Capability

Application Modernization

Phased migration strategies for legacy enterprise systems — from monolith decomposition to cloud-native microservices re-architecture, without stopping feature delivery or accepting big-bang rewrite risk.

What we do

Modernising a legacy enterprise application is one of the highest-stakes technology decisions an organisation can make. The cost of getting it wrong — years of disruption, feature freeze, or a failed rewrite that delivers nothing — is enormous. Most failed modernisation programmes share the same root cause: attempting too much change at once.

We run structured, risk-managed modernisation programmes that deliver business value incrementally while the legacy system remains in production. Using the Strangler Fig pattern, domain-driven design, and event-driven decoupling, we carve new capabilities out of the monolith one bounded context at a time — rather than freezing development while a full replacement is built in parallel.

The goal is a codebase that can be deployed independently by multiple teams, scaled at the service level, and maintained without depending on individuals who understand its entire undocumented history — while the business continues to ship features throughout.

Problems we address

  • — A monolithic codebase has become so tightly coupled that a change in one area unpredictably breaks another, slowing releases to a crawl
  • — Individual components cannot be scaled independently — the entire application must be over-provisioned to handle peak demand in one area
  • — Operational costs are high because the application runs on vendor-proprietary infrastructure or hardware approaching end-of-life
  • — The technology stack is no longer supported, creating security risk and making it impossible to hire engineers who know it
  • — Two or three individuals hold undocumented knowledge about how the system works — and are approaching retirement
  • — A previous modernisation attempt failed or stalled, leaving a mix of old and new systems with unclear boundaries

Capabilities

Legacy Assessment & Dependency Mapping

Systematic code and architecture analysis to map internal dependencies, identify bounded contexts, surface undocumented integrations, and produce a risk-scored modernisation backlog. The foundation for every successful modernisation programme.

Strangler Fig Implementation

Incremental carve-out of new services alongside the existing monolith using routing, facade, and anticorruption layer patterns. The legacy system handles requests until the new service is proven in production, then traffic is redirected without a big-bang cutover.

Database Decomposition

Separating the shared database that monoliths typically use into service-owned schemas and data stores — one of the most technically complex aspects of modernisation — using schema extraction, dual-write patterns, and Flyway migration tooling.

API Layer Introduction

Adding an API layer between clients and the monolith as a first modernisation step — exposing capabilities as versioned REST or GraphQL endpoints without requiring changes to the underlying system, creating a stable integration surface for subsequent changes.

Event-Driven Decoupling

Using Kafka as an event backbone to decouple tightly integrated components — new services subscribe to events from the monolith rather than calling it directly, allowing independent deployment and evolution without tight coordination between teams.

Re-platforming to Containers

Containerising existing application components as a lower-risk first step — enabling Kubernetes deployment and CI/CD integration without requiring a full architectural re-design, while setting up the infrastructure needed for subsequent service extraction.

Our approach

No big bang — ever

A full rewrite of a production system is almost always the wrong choice. It freezes feature development, accumulates scope creep, underestimates the knowledge embedded in the existing system, and typically takes three to five times longer than estimated. We use the Strangler Fig pattern to deliver incremental, verifiable progress while the legacy system continues serving production traffic.

Prioritise by value and risk

Not every part of a legacy system needs to be modernised. We assess each domain by three dimensions: business value (how much does modernising this unblock?), technical risk (how dangerous is leaving it as-is?), and extraction complexity. The highest-value, lowest-complexity domains go first — building momentum and demonstrating value before tackling the harder parts.

Domain-driven design as the map

DDD provides the language and tooling for identifying service boundaries — bounded contexts, ubiquitous language, and context maps — that produce microservices with coherent responsibilities rather than arbitrary technical splits that create distributed monolith problems.

Feature flags for safe migration

We use feature flags to route a percentage of traffic to new services while the monolith continues handling the rest. This allows gradual confidence building, instant rollback if problems emerge, and data-driven comparison of old and new behaviour before final cutover.

Delivery process

  1. 1

    Legacy assessment

    Code analysis, architecture documentation, dependency mapping, and technical debt quantification. Produces a risk-scored modernisation backlog and recommended sequencing.

  2. 2

    Bounded context mapping

    Domain-driven design workshops with business and engineering stakeholders to identify natural service boundaries, data ownership, and team alignment for the target architecture.

  3. 3

    Prioritisation & roadmap

    Sequence the modernisation roadmap by value, risk, and dependency order. Define first service extraction target and success criteria before any code is written.

  4. 4

    Incremental service extraction

    Build and deploy new services domain by domain using Strangler Fig. Each service goes through shadow mode, canary, and gradual traffic shift before legacy component is decommissioned.

  5. 5

    Legacy decommission

    Systematic retirement of legacy components as their replacements are proven in production. Data migration, integration cleanup, and infrastructure decommission with documented rollback plans.

Technologies

Languages & Frameworks

JavaSpring BootQuarkus.NET

Event-Driven

Apache KafkaApache CamelAWS EventBridge

Container & Platform

DockerKubernetesHelm

Database Migration

FlywayLiquibaseAWS DMS

Feature Management

LaunchDarklyUnleash

Patterns & Design

DDDStrangler FigCQRSEvent Sourcing

Industries served

Financial Services Healthcare Manufacturing

Related case studies

Financial Services

Banking Platform Modernization

Strangler Fig migration from a 12-year-old Java monolith to a microservices architecture — 18 services extracted over 24 months with no feature freeze and 99.97% production availability maintained throughout.

Frequently asked questions

Almost always incremental. Big bang rewrites consistently underestimate the knowledge encoded in existing systems, overestimate how well requirements can be documented upfront, and accumulate new technical debt while the rewrite is in progress. The Strangler Fig approach — replacing components incrementally while the legacy system continues running — has a substantially better track record. The only cases where a full rewrite makes sense are when the existing codebase is genuinely unmodifiable (e.g., no source code available, or running on hardware that can't be maintained) and the new system is genuinely better understood than the old one.
A meaningful first service extraction can typically be delivered within three to four months of starting. A full modernisation programme for a large monolith — covering all domains — typically takes two to four years when run as an incremental programme alongside normal feature delivery. This is substantially longer than most initial estimates, but substantially less risky than the alternative. We present a phased roadmap with defined milestones so progress is visible and the programme can be re-evaluated at each phase boundary.
The first extraction target should be a domain that is high in business value (unblocking a specific capability or team velocity problem), relatively low in integration complexity (few dependencies on other monolith components), and well-understood by at least some of your engineers. Starting with the hardest domain first — typically the core transaction engine — is a common mistake that leads to stalled programmes. Early wins build team confidence with the Strangler Fig approach and produce measurable evidence that the strategy is working, which makes subsequent funding and stakeholder support easier to maintain.
We use several mechanisms to reduce migration risk. Feature flags allow traffic to be shifted incrementally and reversed instantly if problems emerge. Shadow mode runs the new service in parallel with the monolith, comparing outputs before any traffic is redirected. Canary deployments route a small percentage of live traffic to the new service before full rollout. Each stage has defined rollback procedures and acceptance criteria. The key point is that at no stage is the system in a state where a rollback requires reverting database changes — we design around that constraint from the start.
Modernisation typically increases costs in the short term — you're running both the legacy system and the new services simultaneously during migration. The medium and long-term benefits are lower infrastructure costs from cloud-native autoscaling (replacing over-provisioned on-premise hardware), reduced vendor licence fees for proprietary middleware, lower maintenance costs from improved code quality and test coverage, and faster feature delivery that generates business value. We model these costs and benefits explicitly during the assessment phase so you have a realistic business case for the programme.

Start your modernisation journey

Whether you're dealing with a slowing monolith, an aging technology stack, or a previous modernisation attempt that stalled, our team can help you build a risk-managed path forward.

Talk to our modernisation team View case studies