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Technical Service

Modernize your legacy system without stopping production.

Module-by-module decomposition using the strangler fig pattern. Your system stays live, your team ships features, and the monolith shrinks sprint by sprint.

Zero Downtime
Production stays live
No big-bang cutovers
Incremental
Strangler fig pattern
Module-by-module extraction
Deployable
At every phase
Working system throughout
Reversible
Built-in rollback
Each step can be undone

Legacy Assessment & Roadmapping

Systematic evaluation of your codebase — dependency mapping, complexity scoring, and a prioritized modernization roadmap that sequences extraction by risk and business value.

Monolith-to-Microservices Decomposition

Domain-driven decomposition that identifies service boundaries within your monolith. We extract modules into independently deployable services with well-defined contracts.

Strangler Fig Migration

Incremental replacement where new functionality routes through modern services while legacy handles the rest. The monolith shrinks as services grow — no cutover required.

API-First Modernization

Wrap legacy systems with modern REST or GraphQL APIs. External consumers get a clean interface immediately while internal modernization proceeds at its own pace.

Database Migration & Modernization

Schema decomposition, data migration strategies, and the transition from shared databases to service-owned data stores — without data loss or extended maintenance windows.

Cloud-Native Transformation

Containerization, orchestration, and infrastructure as code for modernized services. Each extracted module gets its own deployment pipeline and scaling configuration.

Modernization Approach

The Monolith Shrinks Sprint by Sprint

Each phase extracts modules independently while production stays live. Click any phase to see what gets extracted and the system state at that point.

LegacyModern
70%30%
Production Live — All Phases

Sample modernization phases — your actual module extraction sequence is determined during the assessment based on your codebase.

Our Implementation Process

1
Weeks 1–2

Legacy Assessment

Codebase analysis, dependency mapping, and complexity scoring. We identify module boundaries, coupling hotspots, and the extraction sequence that minimizes risk while maximizing early value.

Dependency map, complexity scores, prioritized extraction backlog
2
Weeks 2–3

Architecture Design

Target architecture definition, service boundary design, and migration strategy per module. Each module gets an assigned approach: extract, wrap, replatform, or retire.

Target architecture, per-module migration strategy, ADRs
3
Weeks 3–5

Foundation Layer

Set up the infrastructure for the modern architecture: service mesh, API gateway, CI/CD pipelines, observability, and the routing layer that enables strangler fig traffic shifting.

Infrastructure ready, routing layer deployed, first service template
4
Ongoing

Incremental Extraction

Extract modules one by one. Each extraction follows the same cadence: build the service, validate in parallel with legacy, shift traffic, confirm, decommission the legacy module.

One service extracted per sprint cycle, regression-tested
5
Final 2 weeks

Validation & Handover

Performance validation, load testing, runbook creation, and knowledge transfer. Your team inherits a documented, observable system with clear ownership per service.

Performance benchmarks, runbooks, team onboarding complete

Ship Features While You Modernize

New functionality goes through modern services from day one. Your roadmap does not pause while legacy transforms — the business keeps moving forward.

Reduce Blast Radius of Failures

Independent services mean a failure in one module does not cascade across the entire system. Each service has its own deployment, scaling, and recovery — no more system-wide outages from a single bad deploy.

Teams Can Move Independently

Decoupled services with clear contracts mean teams own their domain end-to-end. No more waiting for other teams to finish before you can deploy. Faster iteration, less coordination overhead.

Scale What Needs Scaling

Independent services scale independently. When one part of the system gets load, scale that service without scaling (and paying for) everything else.

Engagement Models

Frequently Asked Questions

How do you keep production running during modernization?

We use the strangler fig pattern: new services run alongside the legacy system. Traffic routes to the new service for modernized functionality and to the legacy system for everything else. At no point is the entire system cut over at once — each module migrates independently with its own validation window and rollback path.

How long does a full modernization take?

It depends on the size and complexity of the monolith. A typical mid-market system with 4–6 priority modules takes 16–24 weeks for the initial extraction phase. Larger estates with dozens of modules run as ongoing engagements over 6–12 months. The assessment (3 weeks) produces a realistic timeline based on your specific codebase.

Can you just wrap our legacy system with APIs instead of rewriting it?

Yes — API-first modernization is one of our core approaches. We place a modern API layer in front of legacy functionality so external consumers (and new internal services) interact through clean REST or GraphQL interfaces. This buys time for deeper modernization while delivering immediate integration value.

Do we need to modernize everything at once?

No. The assessment identifies which modules to extract first based on business value, risk, and coupling. Many organizations modernize their highest-value, lowest-risk modules first to demonstrate value, then continue with a sustained modernization cadence. Some legacy modules may never need modernization if they are stable, low-maintenance, and decoupled.

What happens to our existing data during modernization?

Each module extraction includes a data migration strategy. We decompose shared databases into service-owned stores using techniques like change data capture, dual-write with reconciliation, or event-sourced synchronization. Data integrity is validated at every step — no extended maintenance windows, no data loss.

What if the modernization needs to be paused or reprioritized?

Because each module is extracted independently, the system is in a valid, deployable state at the end of every extraction cycle. You can pause between modules, reprioritize the extraction order, or reduce team size without leaving the system in a broken intermediate state. This is the fundamental advantage of incremental over big-bang.

Ready to modernize without the rewrite risk?

Book a 30-minute call. We will discuss your legacy system, identify the highest-value extraction targets, and outline what an incremental modernization engagement looks like for your architecture.