Monolithic Architecture Is Not Outdated

The word "monolith" has gained a negative connotation among developers. But this is unfair. Most successful products started as monoliths — and many remain so. Shopify, Stack Overflow, Basecamp — monolithic applications serving millions of users. The key question is not "monolith or microservices?" but "which architecture fits your current scale and team?"

Monolith Benefits for Small Teams

  • Simple deployment: one artifact, one deploy command, one server. No container orchestration, no service registry

  • Easy debugging: call stacks span the entire codebase, IDE breakpoints work without additional setup

  • Transactions without pain: ACID transactions cover the entire application. No eventual consistency issues between services

  • Simple refactoring: rename a class or change an API — one PR, the IDE finds all references

  • Lower operational costs: one database, one logging setup, one monitoring system

  • Fast development at the start: a new feature does not require a new repo, CI/CD pipeline, Docker image, and API contract

When Microservices Make Sense

Microservices solve specific scaling problems that simply do not exist in small projects. The transition is justified when:

  • Different scaling requirements: the image processing module needs 100× more CPU than the CRUD module. Scaling the entire monolith for one component is expensive

  • Independent team deployments: 5+ teams constantly conflict on merges. Each team must be able to deploy independently

  • Different technology stacks: ML module in Python, core logic in Go, legacy component in Java — isolation is needed

  • Regulatory isolation: the payment module must comply with PCI DSS separately from the rest of the system

  • Fault isolation: a recommendations module failure must not bring down the entire application

Modular Monolith: The Middle Ground

A modular monolith is an architectural approach where a monolithic application's code is organized into clearly delineated modules with explicit public APIs between them. Benefits:

  • Preserves the deployment simplicity of a monolith

  • Enforces domain boundaries — prevents "spaghetti code"

  • Easy to migrate to microservices: when a module is ready — it is simply extracted

  • Laravel with Domain-Driven Design or Bounded Contexts is a classic example

For most projects, the modular monolith is the optimal starting architecture.

DevOps Requirements for Microservices

Microservices significantly increase operational complexity. You will need:

  • Containerization: Docker for each service

  • Orchestration: Kubernetes or Docker Swarm

  • Service discovery: Consul or Kubernetes built-in

  • API Gateway: Kong, AWS API Gateway, Nginx

  • Distributed tracing: Jaeger, Zipkin, or OpenTelemetry

  • Centralized logging: ELK Stack or Grafana Loki

  • Circuit breaker: Hystrix or Resilience4j

  • CI/CD per service: a separate pipeline for each

This requires a minimum of 2–3 full-time DevOps engineers or significant spend on managed services (AWS ECS, GCP Cloud Run).

Cost Comparison

  • Monolith, single server: $50–200/month (DigitalOcean/Hetzner)

  • Monolith, high availability: $300–800/month (2 servers + load balancer + managed DB)

  • Microservices, minimum: $500–1,500/month (K8s cluster + 5–10 services + managed DB per service)

  • Microservices, production: $2,000–10,000+/month for serious workloads

Plus DevOps time: setting up a K8s cluster from scratch takes 2–4 weeks for a qualified engineer.

Database per Service

The canonical microservices principle: each service owns its database. This adds:

  • No JOINs across services — only API calls or event sourcing

  • Eventual consistency instead of ACID — more complex business scenarios

  • Saga pattern for distributed transactions

  • Higher cost for managed databases (each one billed separately)

Real Examples of Premature Optimization Failures

  • Case 1: a startup with 500 users spent 6 months building a microservices architecture instead of finding product-market fit. Shut down a year later due to resource drain

  • Case 2: a team of 3 developers maintaining 12 microservices. 40% of time goes to DevOps instead of features

  • Case 3: Amazon, Netflix, Uber moved to microservices when they had hundreds of developers and billions of requests — not the other way around

Decision Rule

  • Team fewer than 10 developers → monolith (modular)

  • No DevOps engineers → monolith

  • Startup or MVP → always monolith first

  • Different scaling requirements for specific components → extract only those components into services

  • Team of 20+ developers, mature product → microservices can be considered

IT Master designs architecture that fits your current scale and grows with your business — without premature complexity.