Why Microservices are a Scam

Microservices are a scam. They’re not an architecture—they’re a marketing ploy to sell you more servers, more complexity, and more consulting services.

The Microservices Lie

What They Tell You

  • “Scalable and maintainable”
  • “Independent deployment”
  • “Technology diversity”
  • “Fault isolation”
  • “Team autonomy”

What You Actually Get

  • Distributed monolith: All services depend on each other
  • Deployment hell: Coordinating releases across services
  • Technology chaos: Different languages, frameworks, databases
  • Failure cascade: One service failure breaks everything
  • Team confusion: Nobody knows how anything works

The Complexity Explosion

Monolithic Application

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# Simple, clear, maintainable
def process_order(order):
    validate_order(order)
    charge_payment(order)
    update_inventory(order)
    send_confirmation(order)
    return order

Microservices “Architecture”

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# Order Service
POST /orders
GET /orders/{id}
PUT /orders/{id}

# Payment Service
POST /payments
GET /payments/{id}

# Inventory Service
POST /inventory
GET /inventory/{id}

# Notification Service
POST /notifications
GET /notifications/{id}

Simple function becomes 4 services, 8 endpoints, and infinite complexity.

The Network Dependency Hell

The Fallacy of Independence

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# This is what microservices actually do
def process_order(order):
    # Call payment service
    payment = requests.post('http://payment-service/charge', json=order)
    if payment.status_code != 200:
        return error("Payment failed")

    # Call inventory service
    inventory = requests.post('http://inventory-service/update', json=order)
    if inventory.status_code != 200:
        # Rollback payment
        requests.post('http://payment-service/refund', json=order)
        return error("Inventory failed")

    # Call notification service
    notification = requests.post('http://notification-service/send', json=order)
    if notification.status_code != 200:
        # Rollback everything
        requests.post('http://payment-service/refund', json=order)
        requests.post('http://inventory-service/rollback', json=order)
        return error("Notification failed")

    return order

This is not “independent services”—this is a distributed monolith.

The Performance Disaster

Network Overhead

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# Monolithic: One function call
result = process_order(order)  # 1ms

# Microservices: Multiple network calls
payment = requests.post('http://payment-service/charge')     # 50ms
inventory = requests.post('http://inventory-service/update') # 50ms
notification = requests.post('http://notification-service/send') # 50ms
# Total: 150ms (150x slower)

Microservices are 100x slower than monolithic applications.

The Latency Problem

  • Network latency: Every call goes over the network
  • Serialization overhead: JSON parsing adds milliseconds
  • Connection pooling: Managing connections is expensive
  • Load balancing: Extra hop adds latency

The Debugging Nightmare

Monolithic Debugging

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# Simple debugging
def process_order(order):
    try:
        validate_order(order)  # Line 10
        charge_payment(order)  # Line 11
        update_inventory(order) # Line 12
        send_confirmation(order) # Line 13
    except Exception as e:
        print(f"Error at line {e.line}: {e.message}")

Microservices Debugging

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# Debugging microservices
curl -X POST http://payment-service/charge
# Error: 500 Internal Server Error
# No stack trace, no line numbers, no context

# Check payment service logs
kubectl logs payment-service-pod
# Error: Database connection failed
# No context about which order failed

# Check database logs
kubectl logs database-pod
# Error: Connection pool exhausted
# No context about which service caused it

Debugging microservices is impossible.

The Deployment Hell

Monolithic Deployment

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# Simple deployment
git push origin main
# Application automatically deploys
# One service, one deployment, one rollback

Microservices Deployment

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# This is what microservices deployment looks like
apiVersion: apps/v1
kind: Deployment
metadata:
  name: payment-service
spec:
  replicas: 3
  selector:
    matchLabels:
      app: payment-service
  template:
    metadata:
      labels:
        app: payment-service
    spec:
      containers:
        - name: payment-service
          image: payment-service:v1.2.3
          ports:
            - containerPort: 8080
          env:
            - name: DATABASE_URL
              value: "postgresql://user:pass@db:5432/payments"
            - name: REDIS_URL
              value: "redis://redis:6379"
            - name: NOTIFICATION_SERVICE_URL
              value: "http://notification-service:8080"

Simple deployment becomes a Kubernetes nightmare.

The Data Consistency Problem

ACID Transactions

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# Monolithic: ACID transactions work
def process_order(order):
    with transaction():
        charge_payment(order)
        update_inventory(order)
        send_confirmation(order)
    # All or nothing

Microservices: No ACID

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# Microservices: No transactions
def process_order(order):
    charge_payment(order)      # Committed
    update_inventory(order)    # Committed
    send_confirmation(order)   # Failed
    # Data is inconsistent forever

Microservices can’t maintain data consistency.

The Real Problem: Vendor Lock-In

The Cloud Provider Trap

Microservices require:

  • Kubernetes: Complex orchestration
  • Service mesh: Istio, Linkerd, Consul
  • API gateway: Kong, Ambassador, AWS API Gateway
  • Monitoring: Prometheus, Grafana, Jaeger
  • Logging: ELK stack, Fluentd, CloudWatch

All of this locks you into specific cloud providers.

The Alternative: Modular Monoliths

What You Actually Need

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# Modular monolith: Best of both worlds
class OrderService:
    def process_order(self, order):
        self.payment_service.charge(order)
        self.inventory_service.update(order)
        self.notification_service.send(order)

class PaymentService:
    def charge(self, order):
        # Payment logic here

class InventoryService:
    def update(self, order):
        # Inventory logic here

Simple, fast, maintainable, and actually works.

The Bottom Line

Microservices are a scam because they:

  1. Add complexity: Simple problems become complex
  2. Reduce performance: Network overhead kills speed
  3. Break debugging: Can’t figure out what went wrong
  4. Create dependencies: Services depend on each other
  5. Require infrastructure: Kubernetes, service mesh, monitoring
  6. Lock you in: Vendor lock-in to cloud providers

Stop using microservices. Use modular monoliths.

Your applications will be faster, simpler, and easier to maintain.