Solution
Legacy System Modernization
An incremental, risk-managed programme for replacing aging systems — keeping production running throughout, using patterns that have proven to work at enterprise scale.
The problem
The cost of staying still
Most organisations with legacy systems face a version of the same dilemma. The systems are expensive to operate, slow to change, and staffed by engineers who understand the codebase primarily because they've been there for years. New features take months. Incidents are hard to diagnose. Recruitment is difficult because the technology stack is unattractive to engineers who have options.
But big-bang rewrites rarely succeed. The scope is underestimated, the delivery timeline extends, the old system continues to evolve while the new one is being built, and eventually the organisation either cancels the programme or goes live with something that doesn't fully replicate what the old system did — because the old system's behaviour was never fully documented.
The right answer isn't a full rewrite or staying static. It's a structured, incremental modernisation that replaces specific parts of the system progressively — keeping the old system running as each piece is replaced, until eventually the old system has no remaining function and can be decommissioned cleanly.
Our approach
Incremental modernisation patterns
Three proven architectural patterns that make incremental migration tractable at enterprise scale.
Strangler Fig
New functionality is built as separate services alongside the legacy system. Traffic is gradually shifted to the new services, capability by capability, until the legacy system handles no remaining requests and can be retired. The metaphor holds: the new system grows around the old one until nothing of the old remains.
Best for
Monolith decomposition where service boundaries can be drawn around business capabilities
Domain Decomposition
The legacy system's business logic is mapped to discrete domains using Domain-Driven Design. Each domain is then re-implemented as an independent service with its own data store and API, replacing the legacy module responsible for that domain. Dependencies between domains are made explicit through defined integration contracts.
Best for
Large monoliths where shared database coupling is the primary complication
Event Sourcing
State changes are captured as an immutable sequence of events rather than overwriting current state. The event log becomes the authoritative record, and the new system's read model is built from replaying those events. This enables incremental migration while maintaining consistency between old and new systems during the transition period.
Best for
Systems where audit requirements are strict and state transitions are complex
Deliverables
What we deliver
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Legacy assessment and dependency map
A documented view of the existing system's components, data flows, integration points, and technical risks — produced by reading code, interviewing engineers, and analysing runtime behaviour.
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Modernisation roadmap with ROI framing
A sequenced plan for replacing system components, with estimates for delivery effort and a framework for quantifying the operational cost savings and risk reduction from each phase.
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Incremental migration execution
Engineering delivery of replacement services, including API design, data model design, integration with the legacy system during the transition period, and cutover management.
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Data migration
Migration strategy, transformation logic, reconciliation tooling, and validation processes to move data from legacy schemas to new data models without loss or corruption.
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Decommission planning
When each legacy component is fully replaced, a structured plan for shutting it down — including dependency verification, data archiving, and licence/infrastructure cost recovery.
Context
Services and industries
Services involved
Industries
Common questions
Frequently asked questions
The assessment considers three factors: the system's size and complexity, the degree of shared coupling (particularly shared database patterns), and the organisation's risk tolerance. Full rewrites can be appropriate for small systems with well-understood scope, limited integration points, and a fixed operating window. For anything with a large undocumented codebase, shared state across components, or integrations with other production systems, incremental migration is almost always the safer path. We make this recommendation based on evidence from the assessment — not a default preference.
The specific approach depends on the migration pattern being used, but the common principle is a defined synchronisation mechanism during the transition window. For strangler fig migrations, we typically use a routing layer (often an API gateway or reverse proxy) that directs traffic to either the old or new system for each capability, with defined synchronisation points for shared state. For event-sourcing migrations, the event log serves as the single source of truth that both systems read from and write to. The transition window is bounded — we don't run parallel systems indefinitely.
This is a legitimate concern and worth addressing directly. AlgoDomain's engagement model involves working alongside the existing team, not replacing them. Engineers who understand the legacy system are valuable assets during modernisation — they are the best source of knowledge about undocumented system behaviour. We structure the programme so that knowledge transfer happens during delivery, and existing engineers become owners of the new components as they're built. Staffing decisions are your organisation's to make; our job is to structure the technical programme to make transition viable.
The assessment phase typically takes four to eight weeks. The modernisation itself is measured in phases, each delivering a specific set of replaced capabilities to production. Individual phases typically run three to six months. Full decommissioning of a complex legacy system across multiple phases usually spans two to four years — though each phase delivers operational benefit as it completes, rather than value being deferred until the end of the programme.
This is common, not exceptional — and the assessment phase is designed for exactly this scenario. We use a combination of static code analysis, runtime tracing, database schema inspection, integration log analysis, and structured interviews with whoever currently operates the system. The goal of the assessment is to produce the documentation that should have existed but doesn't. Some unknowns remain; the migration plan accounts for them by treating high-uncertainty components as higher-risk phases that are de-risked with additional testing gates.
Ready to start the modernisation conversation?
We can begin with a no-commitment assessment conversation — describing the system and its constraints is often enough to determine whether an incremental approach is viable and what the first phase would look like.