Monoliths Might Scale Better Than Microservices — The Truth Nobody Tells You

Well-designed monolith often scales better, is faster, cheaper, easier

Modern engineering culture worships microservices.
Diagrams, Kubernetes clusters, API gateways, sidecars, service meshes…
It feels like if you are not deploying 50 microservices, you are not “scaling”.

But in the real world?
Most applications do not need microservices.
In fact, a well-designed monolith often scales better, is faster, cheaper, easier to debug, and far more stable.

Let’s go deeper — with a real analogy, and C# examples — to understand why.

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The Real-World Analogy: One Restaurant vs 12 Tiny Stalls

Imagine you run a restaurant.

Monolith = One big restaurant

• One kitchen

• One chef team

• One billing counter

• One cleaning team

• One inventory room

All staff coordinate easily. Information flows instantly. Customers get food fast.

Now imagine this is the same restaurant re-designed as microservices.

Microservices = 12 food stalls

• Rice stall

• Curry stall

• Chapati stall

• Dessert stall

• Billing stall

• Token stall

• Inventory stall

Each stall has its own:

• Staff

• Billing pattern

• Queue

• Workflow

• Communication challenges

A customer wants a full meal?
They must visit all stalls and coordinate everything through tokens, scanners, and loudspeakers (APIs).

It looks scalable from outside, but it actually increases:

• Wait time

• Coordination failures

• Running cost

• Latency between stalls

• Integration headaches

This is exactly what microservices do when applied prematurely.

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Why Monoliths Often Scale Better

Because internal calls are faster than network calls

Inside a monolith:
A method calls another method in memory → nanoseconds.

In microservices:
Service A → network → gateway → load balancer → service B → deserialize → process → serialize → response.

Each call costs:

• Network latency

• Serialization/deserialization

• Timeout handling

• Retries

• Load balancing

• Logging

• Distributed tracing

A single user action may trigger 12 network hops.

In a monolith, the same action is just function calls.

C# Example: Simple monolith call

public class OrderService
{
    private readonly PaymentService _payment;

    public OrderService(PaymentService payment)
    {
        _payment = payment;
    }

    public string PlaceOrder()
    {
        var result = _payment.Process(”12345”);
        return “Order Completed: “ + result;
    }
}

Everything happens in-memory.
Fast, reliable, simple.

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C# Example: Same thing in Microservices (Costly Network Call)

public class OrderService
{
    private readonly HttpClient _http;

    public OrderService(HttpClient http)
    {
        _http = http;
    }

    public async Task<string> PlaceOrderAsync()
    {
        var response = await _http.GetAsync(
            “https://paymentservice/api/pay/12345”
        );

        var result = await response.Content.ReadAsStringAsync();
        return “Order Completed: “ + result;
    }
}

Now you must handle:

• timeout

• retries

• circuit breakers

• API versioning

• scaling across clusters

• authentication tokens

• distributed logs

• tracing (Zipkin, Jaeger)

And this is just one call.

Multiply this by 50 services.
Now it’s a nightmare.

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Monoliths Scale Really Well When Designed Correctly

Horizontal Scaling

Monoliths can run on multiple instances behind a load balancer.

Example:

App Server 1
App Server 2
App Server 3

They share:

• the same codebase

• the same behavior

• the same deployment

This is much simpler than managing 50 microservices, each with its own deployment pipeline.

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C# Scaling Example: Using Task-Based Concurrency

Monoliths can scale internally using .NET’s concurrency features.

public async Task ProcessOrdersAsync(IEnumerable<Order> orders)
{
    var tasks = orders.Select(order =>
        Task.Run(() => ProcessSingleOrder(order))
    );

    await Task.WhenAll(tasks);
}

This uses:

• multi-threading

• async operations

• parallel workloads

No network calls. No queues. No distributed sync.

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Why Startups & Mid-Sized Companies Should Prefer Monoliths

Less Infrastructure

Microservices demand:

• Gateway

• Docker

• Kubernetes

• Service mesh

• API version manager

• CI/CD per service

• Observability suite

• Message queues

Monolith?

• One application

• One build pipeline

• One deployment

Clean. Simple. Inexpensive.

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You Still Can Add Modules Inside a Monolith (Best of Both Worlds)

The monolith doesn’t need to be spaghetti code.
You can structure it using modules:

/Modules
   /Orders
   /Billing
   /Inventory
   /Payments

With domain boundaries using Clean Architecture.

C# Example:

public interface IPaymentProcessor
{
    string Pay(int amount);
}

public class RazorPayProcessor : IPaymentProcessor
{
    public string Pay(int amount) => $”Paid {amount} via RazorPay”;
}

public class PaymentModule
{
    private readonly IPaymentProcessor _processor;

    public PaymentModule(IPaymentProcessor processor)
    {
        _processor = processor;
    }

    public string HandlePayment(int amount) => _processor.Pay(amount);
}

You continue to maintain boundaries inside a single codebase.
This is modular monolith architecture — the best of both worlds.

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When Should You Actually Move to Microservices?

Only after the monolith hits these limits:

• Deployment of one module breaks another

• Teams are large (80+ developers across multiple domains)

• Individual modules require different scaling patterns

• Certain modules need independent release cycles

• You need polyglot technologies

• Cloud billing demands cost separation

• You reached true business complexity

At this stage, microservices make sense.

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Microservices Are Not Bad — Just Not Meant for Everything

Microservices solve problems of:

• huge organizations

• massive traffic

• distributed teams

• domain specialization

• independent deployments

But for 80% of products, monoliths:

• scale better

• cost less

• reduce latency

• avoid complexities

• ease debugging

• improve developer productivity

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Final Thought

Monoliths are not old-fashioned.
They are underrated.

Modern systems must be built based on business needs — not fashion trends.

If your app is still growing, still evolving, still experimenting…
then a monolith is your best companion.

Because nothing scales better than simplicity.