Monolith to microservices migration

Your team ships services without waiting for everyone else.

We run the strangler fig decomposition. Your first service is live in 12 weeks with zero downtime. Your team keeps building while we extract, containerize, and wire up Kubernetes on AWS or GCP.

Get Your Free Migration Plan

0

Downtime events across all migrations

12

Weeks to first live service

7x

Faster release velocity

How the Strangler Fig Works

API Gateway

Legacy

Monolith

decomposing...

Auth
Service

Order
Service

User
Service

Payment
Service

Notif
Service

New services form around the monolith. Traffic shifts to each one. The monolith shrinks until it is gone.

Cloud migration Google CloudDockerKubernetesStrangler FigDomain-Driven DesignCI/CD

What a monolith costs every quarter

One service fails.
Your entire platform goes down.

Monolith: any failure affects everything

EVERYTHING

DOWN

Auth • Orders • Users
Payments • Reports

Blast radius: 100% of your platform

One bad deploy takes every user, every feature, and every revenue stream down at the same time.

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: failures stay contained

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 keeps running. Users complete orders. Notifications fire. Search works.

Deploy one service without touching any other
Scale payment independently of auth during peak checkout
Each team owns its service and ships on its own schedule

How the migration runs

Independent service deployments start in week 12. Sometimes sooner.

This is not a full rewrite. We extract one service at a time, validate it under real traffic, then move to the next. Your monolith keeps running throughout.

1

Weeks 1 to 2

Monolith Audit and Domain Mapping

No code changes in this phase. We analyze the codebase, build a coupling heat map, and identify natural service boundaries. You get a clear picture of what you have before we touch anything.

2

Weeks 3 to 4

Architecture Design and Extraction Plan

We define the API contracts for each service, design the API Gateway, and set the extraction order from lowest coupling to highest. You approve the plan before any extraction begins.

3

Weeks 5 to 8

First Services Extracted and Running

The first 2 to 3 services run independently behind the API Gateway. The monolith still handles everything else. No user sees any disruption.

4

Weeks 9 to 10

Kubernetes, Docker, and CI/CD Pipelines

Every service runs in Docker. Kubernetes handles orchestration. Each service has its own deployment pipeline with rolling updates and automatic rollback on failure.

5

Weeks 11 to 12

Full Traffic Cutover and Monolith Retirement

All traffic routes to the extracted services. The monolith is retired. We hand over dashboards, runbooks, and the full deployment infrastructure.

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.
All of them move in the right direction.

Dimension

Your Monolith Today

During Migration

After Migration

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 QA cycles. Every team must deploy at the same time.

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 its service. They test, deploy, and operate it on their own schedule. Releases never require cross-team sign-off.

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.

Per-service dashboards, distributed tracing, and service-level SLOs. You see exactly which service is slow and exactly 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

"When something slows down, we now see exactly which service caused it. Before, we spent two days narrowing that down."

Engineering Manager, B2B SaaS Platform

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

Client proof

7x faster releases. Zero downtime events. A full migration in 12 weeks.

Case Study · Platform team reviewing migration completion dashboard

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

Migration complete

Client

B2B SaaS Platform

AWS EKS · Docker · Kubernetes

The Problem

Deploy cycles ran every 3 weeks. A 2-day code freeze preceded every release. One broken deployment took the entire platform offline. The team needed independent deployments without a full rewrite.

The Result

0x

faster release cycles after extracting 6 services to Kubernetes on AWS EKS with automated CI/CD and 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.

Every service deploys on its own schedule. The team ships features without a release freeze. Zero-downtime deployments eliminated the risk that blocked Friday releases for 3 years.

7x

Release velocity

0

Downtime events during migration

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 start this way. We never propose it.

How we do it

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 we extract every service. Incremental. Validated. You can reverse any step.

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 does not change its coupling.

Kubernetes adds complexity without fixing the blast radius or release problem.

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.

What buyers ask first

The questions engineering leaders ask before starting a migration.

Risk, timeline, and team disruption are the real concerns. Every answer below is direct.

What does this migration cost?

We audit your codebase first. The cost depends on what we find.

The first sprint produces a domain boundary map, an extraction sequence, and a line-item cost estimate. You review and approve it before any extraction work begins.

Which service do you extract first from a monolith?

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.

What if the monolith has no tests? Does that block migration?

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.

Do you need production access to plan the migration?

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.

How long does a full monolith to microservices migration take?

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.

How do you handle the shared database during a microservices migration?

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.

Is this the right move for your team?

Check the situations that match yours.

Not every monolith needs microservices. We tell you honestly when it does and when it does not.

Your fit scoreSelect all that apply

Not sure whether you need microservices or just better modular code? Describe your codebase and we will give you a straight answer.

Deployment is risky and teams fear releasing on Fridays

When one deploy takes everything down, the problem is coupling, not process. This is the core sign.

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 code boundaries, code review, and branch policies fix most problems teams blame on architecture.

Start here

Tell us about your monolith. We send a full migration plan in 3 days.

No commitment. No sales call. 34 monoliths migrated. Zero downtime across every project. You get a domain boundary map and extraction sequence within 3 business days of your first call.

01

Submit your brief

Tell us your language, team size, approximate codebase size, and the deployment pain your team is experiencing.

02

Call with a migration architect within 48 hours

We ask about your codebase, database structure, and where the biggest deployment friction lives.

03

Full migration plan in 3 days

Extraction sequence, domain boundary map, per-service timeline, and a full project cost breakdown.

04

Work begins within 1 week of sign-off

Codebase analysis, coupling heat map, and API contracts. Your first service extraction starts immediately after.

Form

Zero commitment. No sales pressure. · Architect call in 48 hours · Full plan in 3 days

48 hours

Architect call

3 days

Migration plan

34+

Monoliths migrated

0

Downtime events