Monolith vs microservices comparison - Scaling Approaches Compared

Scalability Analysis - Monolith vs microservices comparison

Growth Table: Monolith vs Microservices

Users	Monolith	Microservices
100 users	Single app server handles all logic; simple deployment	Multiple small services; overhead of inter-service calls
10K users	App server CPU/memory stressed; DB load increases; deployment slower	Services can be scaled independently; network latency starts to matter
1M users	Single DB becomes bottleneck; app server overloaded; hard to deploy fast	Services scaled horizontally; DB sharding or replicas per service; complex orchestration
100M users	Monolith likely fails; scaling limited; high downtime risk	Highly scalable; services distributed globally; complex monitoring and tracing needed

First Bottleneck

For monoliths, the database is usually the first bottleneck because all logic and data access happen in one place, causing heavy load and contention.

For microservices, the network and inter-service communication become bottlenecks as the number of services and calls grow, increasing latency and complexity.

Scaling Solutions

• Monolith: Vertical scaling (bigger servers), database read replicas, caching layers, and eventually splitting into microservices.
• Microservices: Horizontal scaling of individual services, database sharding per service, asynchronous messaging, API gateways, and service mesh for communication management.

Cost Analysis

At 1M users, assuming 1 request per second per user:

• Requests per second: 1,000,000
• Monolith: Requires very powerful servers and large DB clusters; high risk of downtime.
• Microservices: Distributed load across many smaller servers; network bandwidth and inter-service calls increase costs.
• Storage: Microservices may duplicate some data per service, increasing storage needs.

Interview Tip

Start by explaining the differences in architecture and scaling points. Discuss bottlenecks clearly for each approach. Then propose specific scaling solutions matching those bottlenecks. Use real numbers to show understanding of limits.

Self Check

Your database handles 1000 QPS. Traffic grows 10x. What do you do first?

Answer: Add read replicas to distribute read load and implement caching to reduce DB hits before considering more complex solutions.

Key Result

Monoliths scale vertically but hit database bottlenecks early; microservices scale horizontally with complexity in communication and orchestration.

Practice

1. Which of the following best describes a monolithic architecture?

easy

A. Many small independent services communicating over a network

B. A database optimized for distributed transactions

C. A cloud service that automatically scales resources

D. A single large application where all components are tightly integrated

Solution

1. Step 1: Understand monolithic architecture

   A monolithic architecture means all parts of the application are combined into one single unit.

2. Step 2: Compare with other options

   Many small independent services communicating over a network describes microservices, C cloud scaling, and D databases, not monoliths.

3. Final Answer:

   A single large application where all components are tightly integrated -> Option D

4. Quick Check:

   Monolith = single big app [OK]

Hint: Monolith = one big app, microservices = many small apps [OK]

Common Mistakes:

• Confusing microservices with monolith
• Thinking monolith means cloud scaling
• Mixing database types with architecture

2. Which syntax correctly describes a microservice in a system design diagram?

easy

A. Multiple boxes each labeled with a specific service name

B. A single box labeled 'App' containing all modules

C. A database icon connected to a single app box

D. A cloud icon with no internal components

Solution

1. Step 1: Identify microservice representation

   Microservices are shown as multiple small boxes, each representing a service.

2. Step 2: Eliminate incorrect options

   A single box labeled 'App' containing all modules shows a monolith, C shows database relation, D is too vague.

3. Final Answer:

   Multiple boxes each labeled with a specific service name -> Option A

4. Quick Check:

   Microservices = many small boxes [OK]

Hint: Microservices = many small boxes, monolith = one big box [OK]

Common Mistakes:

• Choosing single box for microservices
• Confusing database icons with services
• Ignoring service labels

3. Given a system with a monolithic app and a microservices app, which scenario shows better scaling for microservices?

medium

A. Scaling the entire monolith when only one feature needs more resources

B. Scaling only the specific microservice that handles the busy feature

C. Scaling the database only in the monolith

D. Scaling the user interface layer in the monolith

Solution

1. Step 1: Understand scaling in monolith vs microservices

   Monolith requires scaling the whole app, microservices allow scaling individual services.

2. Step 2: Identify the efficient scaling method

   Scaling only the busy microservice is more efficient and flexible than scaling the entire monolith.

3. Final Answer:

   Scaling only the specific microservice that handles the busy feature -> Option B

4. Quick Check:

   Microservices scale individual parts [OK]

Hint: Microservices scale parts; monolith scales whole app [OK]

Common Mistakes:

• Thinking monolith scales parts independently
• Confusing database scaling with app scaling
• Ignoring microservice granularity

4. A team tries to split a monolithic app into microservices but faces frequent communication failures. What is the most likely cause?

medium

A. They deployed all microservices on the same server

B. They used a single database for all microservices

C. They did not implement proper API contracts between services

D. They kept all code in one repository

Solution

1. Step 1: Identify communication needs in microservices

   Microservices communicate over APIs; clear contracts are essential to avoid failures.

2. Step 2: Analyze other options

   Using a single database or same server is possible but less likely to cause communication failures; code repo does not affect runtime communication.

3. Final Answer:

   They did not implement proper API contracts between services -> Option C

4. Quick Check:

   API contracts prevent communication failures [OK]

Hint: API contracts are key for microservice communication [OK]

Common Mistakes:

• Blaming database sharing for communication errors
• Assuming deployment location causes failures
• Confusing code repo structure with runtime issues

5. A startup plans to build a new product with a small team and expects rapid changes. Which architecture is best and why?

hard

A. Monolith, because it is simpler to develop and deploy quickly

B. Microservices, because it allows independent scaling from day one

C. Monolith, because it supports multiple databases easily

D. Microservices, because it requires fewer resources initially

Solution

1. Step 1: Consider team size and speed needs

   A small team with rapid changes benefits from simpler, faster development and deployment.

2. Step 2: Evaluate architecture fit

   Monolith is simpler to build and deploy quickly; microservices add complexity and overhead not ideal for small teams initially.

3. Final Answer:

   Monolith, because it is simpler to develop and deploy quickly -> Option A

4. Quick Check:

   Small team + fast changes = monolith [OK]

Hint: Small teams start monolith for speed, microservices add complexity [OK]

Common Mistakes:

• Choosing microservices for small teams without need
• Assuming microservices always scale better initially
• Ignoring development speed and team skills