When asked about system design in an interview, it often feels like stepping into a whole new realm of architecture, scalability, performance, and reliability. But system design doesn't have to be intimidating! It’s all about breaking down a problem, finding ways to make components work efficiently together, and ensuring that users get a seamless experience, whether there’s one user or a million.
I had my fair share of struggles with System Design when recently I started diving deep into this. The most basic and common one is where to start?.. What exactly does it encompass? How long does it take to complete it? Well, It is a vast topic but you don’t have to complete it. There is no such thing as to complete it. You learn something new daily.
In this blog post, we’ll explore the core concepts of system design, break down some key components, and provide a beginner-friendly blueprint to help you understand what’s behind the systems we interact with daily, like Google, Netflix, and Twitter.
We are not going to dive deep into anything here. As I mentioned, it is a beginner-friendly guide to kick-start your learning process.
What Is System Design?
System design is the process of defining the architecture, components, modules, interfaces, and data flow of a system to meet specified requirements. Whether it's building a small web app or designing a global-scale application, the principles of system design remain the same.
But why is it important? The reason lies in the need to handle scale, reliability, and performance. When a system grows from handling 10 users to 10 million, things get tricky. Without proper design, the system may crumble under load, leading to poor performance, unavailability, and downtime.
So, How do we handle it? How do we manage to keep our “system” robust when the load increases or when one part of it “goes down”? By simply focusing on the core concepts of system design. Whether you’re building a simple web app or a global-scale service like Netflix, the key principles remain the same.
Core Components of System Design
Let's break it down into bite-sized pieces:
DNS Resolution: Before any client (such as your browser or a mobile app) can communicate with a server, it needs to know where to send its request. That’s where DNS comes in. DNS stands for Domain Name System, and its job is to translate domain names (like www.google.com) into IP addresses that computers use to communicate.
How does it work? The diagram below illustrates the DNS process.
When you type a URL into your browser, your request goes through the following steps:
- Root Nameserver: The first stop.
- Top-Level Domain (TLD) Nameserver: For .com, .org, etc.
- Authoritative Nameserver: Knows exactly which IP address corresponds to the domain name.
Load Balancing: Once a client knows where to send its request, it’s time to distribute that request efficiently to avoid overloading a single server. Enter the Load Balancer.
Load balancers are responsible for distributing incoming network traffic across multiple backend servers, ensuring that no single server is overwhelmed.
Why does it matter? Without load balancing, a surge in traffic to one server can cause crashes, leading to an outage.
Here’s a simple visualization:
The load balancer uses algorithms like Round Robin, Least Connections, or IP Hashing to distribute traffic. It also monitors server health to ensure that only healthy servers receive traffic.
Caching: Caching is all about storing frequently used data closer to the user or system to reduce latency and improve performance.
Types of caching:
- In-memory Cache (Redis/Memcached): Store frequently accessed data in memory for faster retrieval.
- Distributed Cache: In large-scale systems, caching is often distributed to handle the load from different locations globally.
Fun fact: Using caching effectively can reduce the load on your databases by up to 80%!
Databases: When we talk about storing user data, we turn to databases. In system design, you need to decide between two broad categories:
- SQL Databases: Traditional relational databases like MySQL, PostgreSQL.
- NoSQL Databases: Document, key-value, or graph databases like MongoDB, Cassandra, etc.
The key difference lies in how data is structured. SQL databases are best when data relationships are important, while NoSQL is better for handling large volumes of unstructured or semi-structured data.
Microservices: In modern systems, we don’t build monolithic applications anymore. Instead, we break them down into microservices—small, independent services that communicate with each other through APIs.
Why microservices?
- Scalability: Each service can be scaled independently.
- Fault Isolation: If one service fails, the others can continue working.
- Flexibility: Different teams can work on different services without stepping on each other’s toes. Example: Imagine a shopping app with services for User Accounts, Shopping Cart, and Payment. Each of these services can be developed, deployed, and scaled independently.
Security: In the current day and age, we cannot imagine a system that does not focus on security. Incorporating security into the core of your system design ensures it is scalable and resilient against attacks. As systems grow in complexity, maintaining a balance between performance and security is crucial.
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Authentication and Authorization:- Ensuring users are who they claim to be and that they only access what they're allowed is the foundation of secure system design.
- OAuth 2.0 / JWT: Use token-based authentication and secure these tokens with encryption.
- Two-Factor Authentication (2FA): Implement 2FA for extra protection. Always validate tokens on every request to prevent session hijacking.
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Secure Communication:- Sensitive data must be protected as it travels across networks.
- TLS (Transport Layer Security): Encrypt all communications with HTTPS.
- End-to-End Encryption (E2EE): Use for highly sensitive applications like chat or financial services. Use the latest TLS versions and strong encryption protocols to avoid vulnerabilities.
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Rate Limiting and Throttling:- Protect your system from malicious users and bots by implementing rate limiting.
- API Gateway Throttling: Prevent DDoS attacks by limiting the number of requests.
- IP Blacklisting: Block malicious IPs to reduce risks. Deploy an API Gateway to monitor traffic and enforce rate limits dynamically.
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Data Encryption and Backups:- Data at rest should always be encrypted to avoid exposure in the event of a breach.
- Encryption at Rest: Store sensitive data using AES-256 encryption.
- Regular Backups: Always back up your data, ensuring it’s encrypted. Secure both hot (active) and cold (backup) storage with strong encryption.
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Input Validation & Sanitization:- Never trust user input. Always validate and sanitize input to protect against SQL Injection and XSS.
- Escaping Inputs: Use prepared statements or parameterized queries to avoid injection attacks. Use web frameworks that automatically escape user input to reduce manual errors.
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Secure Storage of Credentials:- Use secure methods to store passwords and other sensitive information.
- Hashing and Salting: Use hashing algorithms like bcrypt to store passwords securely.
- Secrets Management: Store API keys and credentials in a secure vault (e.g., AWS Secrets Manager). Avoid hardcoding secrets in your source code!
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Monitoring and Logging:- To maintain security post-deployment, constant monitoring,and logging are essential.
- Centralized Logging: Collect and monitor logs using systems like the ELK stack.
- Alerts: Set up automated alerts to notify the team of suspicious activity. Use Intrusion Detection Systems (IDS) to identify potential attacks early.
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Defense Against DDoS Attacks:- To maintain availability, protect your system against DDoS attacks.
- Load Balancers and CDNs: Use a Content Delivery Network (CDN) and load balancers to distribute traffic.
- Web Application Firewalls (WAFs): Use WAFs like Cloudflare to block malicious traffic. Proactively monitor for abnormal traffic spikes to detect DDoS attacks early.
Conclusion
System design isn’t as intimidating as it first seems. It’s all about understanding how the pieces fit together and optimizing for performance, scalability, and reliability. Whether you’re building a simple web app or a global-scale service like Netflix, the key principles remain the same. You should be confident of why you chose one system over other. There is rarely a right answer in system design. Yes, one design can be better than the other but the other design is not wrong!
One should be conscious about the tradeoffs one makes while designing a system so that he/she is aware of its limitations as well as power!
We have not covered everything on system design, but it is enough to give you a rough idea and help you start looking for the right resources to learn more.
Remember, the best way to learn system design is to practice! Start small, experiment, and soon enough, you’ll be designing systems that can handle millions of users.
Happy designing! 🚀
References
- System Design Primer
- If You want to learn more and dive deep, do check out How Netflix Works
- Martin Fowler - Microservices
- System Design Blue Print - The Ultimate Guide
- If you want to practice and learn how to design systems, must check out Google Maps System Design
- Alex Xu - System Design
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