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Monolith To Microservices Migration Company

Monolith to microservices migration consulting.
Ship independently.

Strangler fig decomposition. Docker containerization. Kubernetes on Amazon Web Services or Google Cloud Platform. Zero-downtime extraction of services from your existing monolith. Your engineers deploy one service without touching everything else.

0
Downtime migrations
12
Weeks average first service
7x
Release velocity lift

The Strangler Fig Pattern

API Gateway
Legacy
Monolith
decomposing...
Auth
Service
Order
Service
User
Service
Payment
Service
Notif
Service

Services wrap around the monolith. Traffic routes away. Monolith shrinks.

Cloud migrationGoogle CloudDockerKubernetesStrangler FigDomain-Driven DesignCI/CD

Cinema band · Engineering team mapping service boundaries on large monitor

Diverse engineering team in side profile reviewing a microservices decomposition architecture diagram on a large monitor in a modern studio, cool slate-blue tones, natural overhead light

Architecture before engineering

Every extraction starts with a domain boundary map. No service is pulled out until we can draw the seams with confidence.

Replace with engineering team reviewing service boundary diagram, natural overhead light, side profiles · 1600×533

The real cost of a monolith

One service fails.
In a monolith, everything fails.

Monolith deployment failure
EVERYTHING
DOWN
Auth • Orders • Users
Payments • Reports

Blast radius: 100%

One broken deployment brings every user, every feature, every revenue stream offline simultaneously

Pain · On-call engineer staring at production alert at night

Calm Latina engineer at a laptop showing a clean modular VS Code codebase with a green passing build in the terminal, warm amber evening office light, side angle

Replace with on-call engineer at laptop with production alert, screen glow, dark room, side angle · 800×300

Microservices fault isolation
Payment
Service
AFFECTED
Auth
OK
Orders
OK
Users
OK
Notif
OK
Search
OK
Report
OK

Blast radius: 1 of 7 services

The payment service is degraded. Every other service continues running. Users complete orders. Notifications fire. Search works.

  • Deploy one service without touching the others
  • Scale payment processing independently of user authentication
  • Different teams own different services and deploy on their own schedule
Migration process

From monolith audit to independent service deployments in 12 weeks.

The strangler fig migration does not require a big-bang rewrite. Each phase extracts one bounded context, validates it, and routes traffic away from the monolith incrementally.

1
Weeks 1 to 2
Monolith Audit and Domain Mapping
Codebase analysis, coupling heat map, domain boundary identification using domain-driven design. No code changes yet.
2
Weeks 3 to 4
Strangler Fig Architecture Design
Service boundaries documented. API contracts defined. API Gateway designed. Extraction sequence prioritized by business value and coupling complexity.
3
Weeks 5 to 8
Service Extraction and API Gateway
First 2 to 3 bounded contexts extracted as independent services. API Gateway routes traffic. Monolith still handles remaining domains during transition.
4
Weeks 9 to 10
Kubernetes Orchestration and CI/CD
Services containerized with Docker. Kubernetes cluster configured. Helm charts per service. GitHub Actions or GitLab CI pipelines with rolling deployments and automated rollback.
5
Weeks 11 to 12
Traffic Migration and Monolith Sunset
All traffic routed through API Gateway to extracted services. Monolith decommissioned or reduced to a thin adapter. Observability dashboards handed over.

Deliverable: Domain Boundary Map

coupling-heatmap.analysis
Monolith Coupling Analysis
Payment
High coupling
Auth
Medium
Notify
Low: extract first
Total bounded contexts identified: 7 · Recommended extraction sequence: Notify → User → Auth → Order → Payment

Deliverable: Architecture Document

strangler-fig.architecture
API Contract Registry
POST /api/notify/sendv1 Defined
GET /api/user/:idv1 Defined
POST /api/auth/tokenDraft

Deliverable: Live Services via API Gateway

api-gateway.routingTraffic split active
/notify/*notify-service:3001EXTRACTED
/user/*user-service:3002EXTRACTED
/* (remaining)monolith:8080STILL LIVE

Deliverable: Kubernetes Cluster + CI/CD

k8s-cluster.deployments
notify-svc
3/3 replicas
user-svc
2/2 replicas
auth-svc
Deploying...
CI/CD
Pipeline green
Rolling update strategy · Automated rollback on failure · HPA enabled

Deliverable: Full Microservices Architecture

migration-complete.statusMonolith sunset
100%
Traffic on services
7
Services running
0
Monolith instances
Migration complete. Handoff docs, runbooks, and Helm chart repository transferred.
Before and after the migration

Six dimensions.
Every one transformed.

Dimension
Your Monolith Today
During Migration
After Redefine
Deployment Risk
Every deploy touches everything. Full regression required. Teams afraid to release on Fridays.
Extracted services deploy independently. Monolith still handles unextracted domains.
Each service deploys alone. Automated testing gates each pipeline. Rolling updates with instant rollback.
Release Cadence
1 to 2 releases per month. Long quality assurance cycles. Deploys coordinated across all teams simultaneously.
Extracted services release on own schedule. Monolith releases remain coordinated.
Multiple deploys per day per service. Teams release when their feature is ready, not when everyone is ready.
Fault Isolation
One failed deploy: full outage. Payment bug takes Auth offline. Blast radius is always 100%.
Extracted services fail independently. Monolith failures still cascade internally.
Payment service incident affects payment. Auth, Orders, Users, and Notifications continue serving users.
Scaling
Scale the entire monolith to handle a spike in one feature. Expensive and blunt.
Extracted services scale independently. Monolith still scales as a unit.
Payment service scales during checkout peaks. Auth scales during login bursts. Zero wasted compute.
Team Autonomy
All teams deploy together. One team's delay blocks everyone. Code conflicts across all boundaries.
Extracted service teams are autonomous. Remaining teams still coupled to monolith schedule.
Each team owns a service. They test, deploy, and operate it independently. No cross-team coordination for a release.
Observability
One log stream for everything. Error attribution unclear. Latency profiling across 400K lines of code.
Extracted services have isolated metrics. Monolith remains a single-stream diagnostic challenge.
Service-level service level objectives, distributed tracing, per-service dashboards. You know exactly which service is slow and why.

Value · Engineer reviewing distributed tracing dashboard after migration

Calm South Asian backend engineer reviewing a distributed tracing dashboard of microservice spans after migration on a monitor, deep teal and brass tones, side angle

"Now when something is slow, we can see exactly which service is responsible. We used to spend two days narrowing that down."

Replace with engineer reviewing distributed tracing dashboard, monitor glow, side angle · 1200×400

Client proof

Monolith to microservices. Zero downtime. Faster releases.

Case Study · Platform team reviewing migration completion dashboard

Diverse engineering team in profile watching all-green microservices deployment success indicators after migration, golden-olive and bronze studio tones

Replace with engineering team viewing migration success, screen glow · 1200×400

Migration complete
Client

SaaS Platform, B2B Enterprise

SaaS Product · Amazon Web Services EKS · Docker

The Problem

The existing monolithic application caused slow-release cycles, frequent outages, and limited scalability. Deployment processes were tightly coupled and risky, making it difficult to introduce new features or scale reliably as usage increased.

The Result
0x

faster release cycles after microservices extraction, Kubernetes on Amazon Web Services EKS, and automated CI/CD with zero-downtime rolling deployments

Week 0, starting state
Monolithic application on a single deployment unit
All features, authentication, orders, payments, notifications, reporting, deployed together. Any change required full regression. Release window: once every 3 weeks with a 2-day freeze before.
Week 3, architecture approved
Domain boundaries documented. API contracts defined.
6 bounded contexts identified. Extraction sequence agreed: Notifications first (lowest coupling), then Auth, then Orders. API Gateway design finalized.
Week 7, first service live
Notification service running independently in production
Zero downtime cutover. Notification service deployed on Kubernetes and handling 100% of notification traffic. Monolith notification module disabled. First team ships independently.
Week 12, migration complete
All services extracted. Monolith decommissioned.
Docker containers for all 6 services. Kubernetes on Amazon Web Services EKS. CI/CD pipelines with automated testing, rolling updates, and rollback. All services deploying independently.
Post-migration
Faster releases. Improved uptime. Greater resilience.
Zero-downtime deployments reduced operational risk. Cloud-native architecture positioned the platform for scalable growth and continued feature development at pace.
7x
Release velocity
0
Downtime events
6
Services extracted
Migration approach matters

Three approaches.
One is right.

High risk

Big Bang Rewrite

Stop the world. Rewrite everything in parallel. Launch on a date.

Monolith runs while you rewrite everything. Feature parity risk is enormous.
Launch day is all-or-nothing. No rollback path once you cut over.
Business builds on the old system for 12 to 18 months while engineers build the new one.

Most failed enterprise migrations use this approach. Redefine does not propose it.

Redefine approach

Strangler Fig Pattern

Extract one service at a time. Route traffic incrementally. Monolith shrinks.

Zero downtime. Monolith stays live throughout. Rollback is always available.
First service delivers value in week 7. You don't wait 18 months for the benefit.
Domain boundaries validated against real traffic before the next extraction begins.

This is how Redefine extracts every service. Incremental. Validated. Reversible.

Not a migration

Lift-and-Shift

Take the monolith, containerize it, run it on Kubernetes. Call it done.

The monolith is still a monolith. Docker doesn't change the coupling. Kubernetes doesn't change the blast radius.
You now have container overhead and Kubernetes complexity on top of the same architectural problems.
Release velocity does not improve. Teams still cannot deploy independently. Fault isolation: unchanged.

Often sold as "cloud migration." Does not solve the deployment and coupling problems of a monolith.

Questions

What engineering teams ask before committing to a migration.

Migration risk, timeline, and team impact are the real blockers. Direct answers below.

Monolith to microservices migration pricing

Architecture sprint first. Cost of migration is determined by what we find in the monolith audit.

The Sprint 1 deliverable is the domain boundary map, extraction sequence, and a project cost model. You approve before extraction begins.

We extract the service with the lowest coupling score first, meaning the one with the fewest inbound dependencies from the rest of the monolith. This is a notification, reporting, or email service. Low coupling means low extraction risk, which means the first service goes live fast and proves the pattern works before you extract anything more complex. We then move toward higher-coupling domains (authentication, orders, payments) once the team has extraction confidence and the API Gateway is stable.
No. Most monoliths we migrate have sparse or no test coverage. The strangler fig pattern does not require the monolith to have tests. The approach is: run both the monolith and the extracted service in parallel, compare outputs under real traffic (shadow mode), and validate correctness before cutting over. We also write integration tests for each extracted service as part of the extraction sprint, so by the end of the migration, the new architecture has the test coverage the monolith never did.
For the initial proposal, no. We need the codebase and any architecture documentation you have. For the audit sprint, we need read access to the code repository and the ability to run the application locally. We do not need production access to plan the migration. During extraction, we work in a staging environment that mirrors production until a service is ready for traffic. Production access for deployment is handled with your team's infrastructure engineers, not directly by us.
3 to 6 bounded contexts in 12 to 16 weeks. 6 to 10 bounded contexts in 20 to 28 weeks. The variance comes from coupling complexity, shared database extent, and whether the monolith has any existing API surface we can use. We scope this in the audit sprint and give you a week-by-week breakdown before extraction begins. The first service is live in week 6 to 8 regardless of total project length.
The shared database is the hardest part of every migration and the part most agencies skip. Each extracted service gets its own database, a database-per-service pattern. The transition is done with the strangler fig applied to data: the extracted service writes to its own database while synchronization pipelines keep it in sync with the monolith's shared database during the transition window. Once the service is fully routing traffic and the monolith modules are disabled, the sync is decommissioned and the old tables are archived. This requires careful planning and is covered in the architecture document produced in Sprint 1.
Right match?

Select what describes your current situation.

Not every monolith needs microservices. We are direct about when the investment is worth it and when it is not.

Match score0 of 6 selected

Not sure whether you need microservices or just better modular code? Describe your architecture and we will give you a direct opinion.

Deployment is risky and teams fear releasing on Fridays

Tightly coupled deployments with wide blast radius are the core indicator.

Multiple teams are blocked by a shared codebase and shared release schedule

Team autonomy is the primary benefit microservices deliver beyond technical architecture.

One or two features cause disproportionate load that you cannot scale independently

Independent scaling requires independent services. A monolith scales as a unit.

The monolith has 5 or more years of accumulated coupling and no clear module boundaries

This is where the strangler fig pays for itself. Incremental extraction versus full rewrite.

Probably not the right investment if:

Your team has fewer than 5 engineers total

Microservices add operational overhead that small teams often cannot absorb. Modular monolith may be the better answer.

Your monolith is under 2 years old and problems are organizational, not architectural

Better module boundaries, code review practices, and branch policies often solve what teams attribute to the architecture.

Start here

Describe your monolith. Get a migration plan.

No commitment. No pitch. Our monolith to microservices migration consulting delivers a domain boundary analysis and extraction sequence in 3 business days.

01

Submit your brief

Describe the language, team size, approximate lines of code, and the coupling pain you are experiencing.

02

Architecture call within 48 hours

With a migration architect. We ask about the codebase, database structure, and deployment pain.

03

Migration proposal in 3 days

Extraction sequence, domain boundary map, timeline per service, and sprint-level cost estimate.

04

Audit sprint within 1 week of sign-off

Codebase analysis, coupling heat map, and API contract design. First service extraction follows.

Form
48 hours
Architecture call
3 days
Migration plan
34+
Monoliths migrated
0
Downtime events

Get on a call with us to see how we can help you

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