Table of Contents

  1. What is High-Level Design (HLD)?
  2. Key Principles of HLD
  3. Steps to Approach HLD in Interviews
  4. Core Components of HLD
  5. System Design Patterns
  6. Scalability, Reliability, and Performance
  7. Common HLD Examples
  8. Case Study: Designing a URL Shortener

1. What is High-Level Design (HLD)?

High-Level Design (HLD) is the process of designing the architecture of a system. It focuses on big-picture aspects, including:

  • System architecture: Breaking down the system into modules or components.
  • Communication flow: Defining how different components interact.
  • Scalability and reliability: Addressing how the system can handle growth and faults.
  • Key technologies and choices: Choosing databases, protocols, APIs, etc.

HLD does not dive into implementation-level details like code or APIs but provides a blueprint for the overall architecture.

2. Key Principles of HLD

  1. Scalability:

    • Design systems to handle increased workload (users, data, requests).
    • Techniques include sharding, caching, and horizontal scaling.

  2. Reliability:

    • Ensure systems remain operational even in failure scenarios.
    • Use techniques like replication, failover, and monitoring.

  3. Performance:

    • Minimize response time and maximize throughput.
    • Achieved using caching, load balancing, and efficient algorithms.

  4. Cost-Effectiveness:

    • Optimize resource utilization to reduce costs while maintaining performance.

  5. Security:

    • Ensure data integrity and protect against vulnerabilities.
    • Use encryption, authentication, and secure APIs.

3. Steps to Approach HLD in Interviews

  1. Understand the Requirements:

    • Clarify functional and non-functional requirements.
    • Ask about scale, expected users, and performance constraints.

  2. Define the System Interface:

    • Identify key APIs or user interactions.
    • Example: For a URL shortener, define createShortURL() and getLongURL().

  3. Identify Key Components:

    • Break the system into logical modules.
    • Example: For a social media app, components might include Authentication, Feed Service, and Media Storage.

  4. Sketch the High-Level Architecture:

    • Draw components, their interactions, and data flow.

  5. Discuss Data Storage:

    • Choose databases (SQL/NoSQL), storage formats, and indexing strategies.

  6. Plan for Scalability:

    • Add load balancers, caches, and distributed systems where necessary.

  7. Handle Failures and Reliability:

    • Add redundancy, backups, and monitoring systems.

4. Core Components of HLD

a) Load Balancers

  • Distribute incoming requests across multiple servers to ensure even load.

Example:

Client -> Load Balancer -> Web Servers

b) Application Servers

  • Handle business logic and user requests.

c) Database Layer

  • Store and retrieve data efficiently.
  • Use SQL databases (e.g., MySQL) for relational data and NoSQL databases (e.g., MongoDB, Cassandra) for unstructured data.

d) Caching Layer

  • Reduce latency and database load by storing frequently accessed data.
  • Tools: Redis, Memcached.

Example:

Request -> Cache -> Database

e) CDNs (Content Delivery Networks)

  • Serve static assets (e.g., images, videos) from edge servers closer to users.

f) Message Queues

  • Enable asynchronous processing (e.g., RabbitMQ, Kafka).

g) APIs and Gateways

  • Expose system functionality to external systems.

5. System Design Patterns

a) Microservices Architecture

  • Break the system into small, independent services.
  • Each service handles a specific functionality.

Example:

Authentication Service | User Service | Notification Service

b) Event-Driven Architecture

  • Use events to trigger actions in the system.
  • Example: User signup triggers a welcome email.

c) Master-Slave Architecture

  • Master handles writes, slaves handle reads for database scalability.

Example:

Master DB -> Slave DB 1, Slave DB 2

d) Distributed Systems

  • Spread data and processing across multiple servers.
  • Techniques: Partitioning, replication.

6. Scalability, Reliability, and Performance

Scalability Techniques:

  1. Vertical Scaling:

    • Add resources to a single server.

  2. Horizontal Scaling:

    • Add more servers to the system.

Reliability Techniques:

  1. Replication:

    • Duplicate data across servers to handle failures.

  2. Failover:

    • Switch to a backup server during failures.

  3. Monitoring:

    • Tools: Prometheus, Grafana.

Performance Optimization:

  1. Caching:

    • Store frequently accessed data in memory.

  2. Indexing:

    • Optimize database queries by indexing.

7. Common HLD Examples

  1. Designing a Social Media App:

    • Components: Authentication, Feed Service, Notification Service, Media Storage.
    • Challenges: Scalability, real-time updates, and media storage.

  2. Designing an E-Commerce Platform:

    • Components: Product Service, Order Service, Payment Gateway, Inventory.
    • Challenges: Handling traffic spikes, secure payments.

8. Case Study: Designing a URL Shortener

Functional Requirements:

  1. Shorten a given URL.
  2. Redirect to the original URL when a short URL is accessed.
  3. Handle high read and write traffic.

Non-Functional Requirements:

  1. Highly available.
  2. Low latency.

Architecture:

  • API Layer:

    • Endpoints for creating and retrieving short URLs.

  • Application Layer:

    • Handle logic for encoding and decoding URLs.

  • Database:

    • Store mappings between long URLs and short URLs.
    • Use NoSQL for high write throughput (e.g., DynamoDB).

  • Caching:

    • Cache popular URLs in Redis.

Example Data Flow:

  1. Shorten URL:

    • API receives a long URL.
    • Application generates a unique ID and encodes it.
    • Mapping stored in the database.

  2. Redirect to Long URL:

    • API receives the short URL.
    • Application decodes the ID and retrieves the long URL from the cache or database.

Code Example:

import hashlib

def shorten_url(long_url):
    # Create a hash of the long URL
    short_hash = hashlib.md5(long_url.encode()).hexdigest()[:6]
    # Store mapping in database (pseudo-code)
    database[short_hash] = long_url
    return f"short.ly/{short_hash}"

def get_long_url(short_hash):
    # Retrieve the long URL from the database
    return database.get(short_hash, "URL not found")

# Usage
short_url = shorten_url("https://example.com")
print(short_url)  # Output: short.ly/abc123

long_url = get_long_url("abc123")
print(long_url)  # Output: https://example.com