Architecture Decision Tool
Monolith vs Microservices 모놀리식 vs 마이크로서비스
Answer 9 questions about your project. Get a data-driven recommendation with migration paths and confidence scoring.
Project Questionnaire
0 / 9 answered
Q1
What is your current (or projected) engineering team size?
Larger teams benefit from independent deployment ownership
Q2
What is your product stage?
Early stages benefit from iteration speed; mature products from reliability
Q3
How frequently do you deploy to production?
High deployment frequency requires independent service pipelines
Q4
How complex is your business domain?
Complex domains with clear boundaries are ideal microservice candidates
Q5
What are your scaling requirements?
Independent component scaling justifies the microservices overhead
Q6
How is your engineering organization structured?
Conway's Law: your architecture will mirror your communication structure
Q7
What is the overall technical expertise level of your team?
Microservices add operational complexity; senior teams manage it better
Q8
What are your infrastructure budget constraints?
Microservices require significantly higher infra and tooling investment
Q9
Do you have an existing codebase or are you starting fresh?
Migrating from a monolith to microservices is costly; greenfield is easier
Live Score
Monolith
—
vs
Microservices
—
Monolith
Neutral
Microservices
0 of 9 questions answered
Comparison Table
Architecture Comparison
12 criteria
| Criterion |
Monolith
|
Microservices
|
Modular Monolith
|
|---|---|---|---|
|
Development Speed (early)
iteration velocity in first 6 months
|
✓ | ✗ | ✓ |
|
Independent Deployability
deploy one component without touching others
|
✗ | ✓ | ~ |
|
Granular Scaling
scale individual hot paths independently
|
✗ | ✓ | ✗ |
|
Fault Isolation
one failure doesn't cascade to the whole system
|
✗ | ✓ | ~ |
|
Operational Simplicity
low infra overhead, easier local dev
|
✓ | ✗ | ✓ |
|
Technology Heterogeneity
use different languages / DBs per component
|
✗ | ✓ | ✗ |
|
Data Consistency
strong ACID transactions across domains
|
✓ | ✗ | ✓ |
|
Team Autonomy
teams ship without coordinating deployments
|
✗ | ✓ | ~ |
|
Debugging & Tracing
follow a request through the system easily
|
✓ | ✗ | ✓ |
|
Infra Cost (at low scale)
monthly cloud bill for a small product
|
✓ | ✗ | ✓ |
|
Organizational Scaling
support growing to 100+ engineers without bottlenecks
|
✗ | ✓ | ~ |
|
Refactoring / Code Sharing
reuse code across features without API contracts
|
✓ | ✗ | ✓ |
✓ Strong advantage
~ Partial / with effort
✗ Weak / not applicable
Famous Examples
Real-World Decisions
what the industry chose — and why
Chose Monolith / Modular Monolith
MONOLITH
Basecamp (37signals)
Intentionally kept a Rails monolith. Small team, high developer productivity, rejected microservices complexity. Powers a profitable multi-million user product.
MONOLITH
Stack Overflow
Runs on a few powerful servers with a .NET monolith. Handles millions of requests/day with extreme efficiency. Proof that hardware can outperform distributed complexity.
REVERTED TO MONO
Segment
Migrated from monolith → 140 microservices → back to a monolith ("Centrifuge"). Found the overhead of 140 services worse than the original problem. Classic over-engineering case.
REVERTED TO MONO
Prime Video (Amazon)
Their video monitoring tool was microservices-first. Migrating to a monolith reduced infrastructure cost by 90% and improved performance. Made waves in 2023.
MODULAR MONO
Shopify
A famously large Rails monolith ("Shopify Core"). Instead of microservices, they invested in component isolation within the monolith and strict module boundaries.
Chose Microservices
MICROSERVICES
Netflix
Pioneered microservices after a 2008 database corruption took them offline. Moved 100% to AWS with 700+ services. Invented Hystrix, Eureka, Zuul — the microservices toolchain.
MICROSERVICES
Amazon
Jeff Bezos' "Two-Pizza Teams" mandate in 2002 forced service boundaries. Each team owns their API. Enabled AWS itself — S3, EC2, etc. are each independent services.
MICROSERVICES
Uber
Scaled from a monolith to 2,200+ microservices to support global operations. Different teams own ride-hailing, payments, maps, surge pricing, etc. independently.
MIGRATED FROM MONO
Twitter / X
Started as a Ruby on Rails monolith ("the Fail Whale" era). Migrated critical paths (timelines, tweets) to JVM microservices to handle 500M tweets/day at scale.
MICROSERVICES
Spotify
Organized around "squads" owning their own services (playlists, search, recommendations, payments). Each squad deploys independently — enabling 10+ releases per day per squad.