Anti-patterns to avoid in LLD - Scalability & System Analysis

Scalability Analysis - Anti-patterns to avoid

Growth Table: What Changes at Each Scale

Users	Common Anti-patterns	Impact	Signs to Watch
100 users	Monolithic design, no caching, tight coupling	System works but slow response under load	Slow page loads, high CPU spikes
10,000 users	Single database instance, no load balancing, synchronous calls	Database overload, server crashes, slow API responses	Timeouts, increased error rates
1,000,000 users	No sharding, no horizontal scaling, ignoring eventual consistency	Database bottleneck, network congestion, data loss risk	High latency, frequent downtime
100,000,000 users	Ignoring microservices, no CDN, no caching layers	Massive delays, huge infrastructure costs, poor user experience	System outages, slow global access

First Bottleneck: What Breaks and Why

At small scale, the database is the first to struggle because it handles all requests directly without caching or replicas.

As users grow, the application server CPU and memory become overloaded due to synchronous processing and lack of load balancing.

At large scale, network bandwidth and data storage become bottlenecks if data partitioning and CDNs are not used.

Scaling Solutions to Avoid Anti-patterns

• Horizontal scaling: Add more servers to distribute load and avoid single points of failure.
• Caching: Use caches to reduce database hits and speed up responses.
• Database sharding: Split data across multiple databases to handle large volumes.
• Load balancing: Distribute incoming traffic evenly across servers.
• Use CDNs: Deliver static content closer to users to reduce latency.
• Microservices: Break monoliths into smaller services for better maintainability and scaling.

Back-of-Envelope Cost Analysis

• At 10,000 users, expect ~1000 QPS (queries per second).
• Database storage grows with user data; plan for GBs to TBs depending on data size.
• Network bandwidth needs increase; 1 Gbps can handle ~125 MB/s, plan accordingly.
• Adding caching reduces database load by up to 70%, saving costs.
• Horizontal scaling increases server costs linearly but improves availability.

Interview Tip: Structuring Scalability Discussion

Start by identifying current system limits and bottlenecks.

Discuss how load increases affect each component.

Explain anti-patterns and why they cause problems at scale.

Propose clear, practical solutions matching the bottleneck.

Use real numbers to justify your approach.

Self Check Question

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

Answer: Add read replicas and implement caching to reduce direct database load before scaling vertically or sharding.

Key Result

Avoiding anti-patterns like monolithic design, no caching, and single database instances is crucial. The database is usually the first bottleneck as traffic grows. Solutions include horizontal scaling, caching, sharding, and load balancing to maintain performance and reliability.

Practice

1. Which of the following best describes the God Object anti-pattern in system design?

easy

A. Separating data storage and business logic into different layers.

B. A system design where components are loosely connected and communicate via events.

C. A single component that handles too many responsibilities, making the system hard to maintain.

D. Using multiple small services to handle different tasks independently.

Solution

1. Step 1: Understand the God Object concept and compare options

   The God Object anti-pattern occurs when one component or class takes on too many responsibilities, leading to complex, hard-to-maintain code. A single component that handles too many responsibilities, making the system hard to maintain. matches this description exactly, while others describe good design practices.

2. Final Answer:

   A single component that handles too many responsibilities, making the system hard to maintain. -> Option C

3. Quick Check:

   God Object = Single overloaded component [OK]

Hint: God Object means one part does too much [OK]

Common Mistakes:

• Confusing God Object with microservices
• Thinking God Object is a good modular design
• Mixing God Object with event-driven architecture

2. Which of the following is an example of a hardcoding anti-pattern in system design?

easy

A. Storing configuration values directly inside the source code.

B. Using environment variables for configuration.

C. Separating configuration into external files.

D. Using feature flags to toggle functionality.

Solution

1. Step 1: Identify what hardcoding means and match options

   Hardcoding means embedding fixed values directly in the code, making changes difficult and error-prone. Storing configuration values directly inside the source code. shows storing config inside code, which is hardcoding. Others are best practices.

2. Final Answer:

   Storing configuration values directly inside the source code. -> Option A

3. Quick Check:

   Hardcoding = fixed values in code [OK]

Hint: Hardcoding means fixed values inside code [OK]

Common Mistakes:

• Confusing hardcoding with using environment variables
• Thinking external config files are hardcoding
• Mixing feature flags with hardcoding

3. Consider a system where all modules directly access a single shared database without any abstraction layer. What is the main anti-pattern here?

medium

A. Tight Coupling

B. God Object

C. Spaghetti Architecture

D. Event-Driven Design

Solution

1. Step 1: Analyze direct database access and identify the anti-pattern

   When modules directly access the database without abstraction, they become tightly coupled to the database schema. Tight Coupling means components depend heavily on each other, reducing flexibility and increasing maintenance difficulty.

2. Final Answer:

   Tight Coupling -> Option A

3. Quick Check:

   Direct DB access = Tight Coupling [OK]

Hint: Direct DB access causes tight coupling [OK]

Common Mistakes:

• Confusing tight coupling with God Object
• Thinking event-driven design fits here
• Mixing spaghetti architecture with tight coupling

4. You find a system where many components are tightly interconnected with complex dependencies, making it hard to change one without breaking others. What anti-pattern is this, and how can you fix it?

medium

A. God Object; merge all components into one big class.

B. Spaghetti Architecture; refactor to modular design with clear interfaces.

C. Hardcoding; move all values into source code.

D. Tight Coupling; remove all interfaces and use direct calls.

Solution

1. Step 1: Identify the anti-pattern from description and determine the fix

   Complex interdependencies causing fragility is typical of Spaghetti Architecture. Refactoring to modular design with clear interfaces reduces dependencies and improves maintainability.

2. Final Answer:

   Spaghetti Architecture; refactor to modular design with clear interfaces. -> Option B

3. Quick Check:

   Spaghetti Architecture = tangled dependencies [OK]

Hint: Tangled dependencies = spaghetti; modularize [OK]

Common Mistakes:

• Thinking God Object means merging components
• Confusing hardcoding with architecture issues
• Believing removing interfaces reduces coupling

5. A startup built a monolithic system with many hardcoded values and a God Object managing most logic. They want to scale and maintain it easily. What is the best approach to fix these anti-patterns?

hard

A. Ignore scalability and focus only on adding new features.

B. Keep the monolith but add more hardcoded values for speed.

C. Merge all logic into one bigger God Object for simplicity.

D. Refactor into microservices, externalize configuration, and split responsibilities into smaller components.

Solution

1. Step 1: Identify problems in current system and choose best solution to fix anti-patterns

   Monolith with hardcoded values and God Object causes poor scalability and maintainability. Refactoring into microservices splits responsibilities, externalizing config removes hardcoding, improving scalability and maintainability.

2. Final Answer:

   Refactor into microservices, externalize configuration, and split responsibilities into smaller components. -> Option D

3. Quick Check:

   Microservices + external config fix anti-patterns [OK]

Hint: Split monolith, externalize config, avoid God Object [OK]

Common Mistakes:

• Thinking bigger God Object improves simplicity
• Adding more hardcoding for speed
• Ignoring scalability needs