To excel in system design, one of the most crucial aspects is to develop a deep understanding of fundamental system design concepts such as Load Balancing, Caching, Partitioning, Replication, Databases, and Proxies.
This course will cover key concepts that can make a significant difference in your ability to tackle system design problems. These concepts range from understanding the intricacies of API Gateway and mastering Load Balancing techniques to grasping the importance of CDNs and appreciating the role of Caching in modern distributed systems. By the end of this course, you’ll have a comprehensive understanding of these essential ideas and the confidence to apply them in your next interview.
When discussing system design interviews, it's important to note that they are inherently unstructured. During the interview, it can be challenging to maintain focus and ensure all crucial elements of the design are addressed. This course aims to guide you in answering any system design interview question by ensuring you do not miss discussing any critical aspect.
Let's get started! 🚀
The repository is organized into topic-specific files, each covering a concept in detail. Below is the complete syllabus:
| No | Topic |
|---|---|
| 1 | Introduction to System Design |
| 2 | Introduction to Load Balancing |
| 3 | Load Balancing Algorithms |
| 4 | Uses of Load Balancing |
| 5 | Load Balancer Types |
| 6 | Stateless vs. Stateful Load Balancing |
| 7 | High Availability and Fault Tolerance |
| 8 | Scalability and Performance |
| 9 | Challenges of Load Balancers |
| 10 | Introduction to API Gateway |
| 11 | Usage of API Gateway |
| 12 | Advantages and Disadvantages of API Gateway |
| 13 | Scalability |
| 14 | Availability |
| 15 | Latency and Performance |
| 16 | Concurrency and Coordination |
| 17 | Monitoring and Observability |
| 18 | Resilience and Error Handling |
| 19 | Fault Tolerance vs. High Availability |
| 20 | HTTP vs. HTTPS |
| 21 | TCP vs. UDP |
| 22 | HTTP Versions (1.0, 1.1, 2.0, 3.0) |
| 23 | URL vs. URI vs. URN |
| 24 | Introduction to DNS |
| 25 | DNS Resolution Process |
| 26 | DNS Load Balancing and High Availability |
| 27 | Introduction to Caching |
| 28 | Why is Caching Important? |
| 29 | Types of Caching |
| 30 | Cache Replacement Policies |
| 31 | Cache Invalidation |
| 32 | Cache Read Strategies |
| 33 | Cache Coherence and Consistency Models |
| 34 | Caching Challenges |
| 35 | Cache Performance Metrics |
| 36 | Content Delivery Networks (CDN) |
| 37 | Origin Server vs. Edge Server |
| 38 | CDN Architecture |
| 39 | Push CDN vs. Pull CDN |
| 40 | Introduction to Data Partitioning |
| 41 | Partitioning Methods |
| 42 | Data Sharding Techniques |
| 43 | Benefits of Data Partitioning |
| 44 | Common Problems Associated with Data Partitioning |
| 45 | What is a Proxy Server? |
| 46 | Uses of Proxy Servers |
| 47 | VPN vs. Proxy Server |
| 48 | What is Redundancy? |
| 49 | What is Replication? |
| 50 | Data Backup vs. Disaster Recovery |
| 51 | Introduction to CAP Theorem |
| 52 | Components of CAP Theorem |
| 53 | Trade-offs in CAP Theorem |
| 54 | Examples of CAP Theorem in Practice |
| 55 | Beyond CAP Theorem |
| 56 | System Design Trade-offs in Interviews |
| 57 | Introduction to Databases |
| 58 | SQL Databases |
| 59 | NoSQL Databases |
| 60 | SQL vs. NoSQL |
| 61 | ACID vs. BASE Properties |
| 62 | Real-World Examples and Case Studies |
| 63 | SQL Normalization and Denormalization |
| 64 | In-Memory Database vs. On-Disk Database |
| 65 | Data Replication vs. Data Mirroring |
| 66 | Database Federation |
| 67 | What are Indexes? |
| 68 | Types of Indexes |
| 69 | Introduction to Bloom Filters |
| 70 | How Bloom Filters Work |
| 71 | Benefits & Limitations of Bloom Filters |
| 72 | Variants and Extensions of Bloom Filters |
| 73 | Applications of Bloom Filters |
| 74 | Difference Between Long-Polling, WebSockets, and SSE |
| 75 | What is Quorum? |
| 76 | What is Heartbeat? |
| 77 | What is Checksum? |
| 78 | Uses of Checksum |
| 79 | Leader and Follower Pattern |
| 80 | Introduction to Messaging Systems |
| 81 | Introduction to Kafka |
| 82 | Messaging Patterns |
| 83 | Popular Messaging Queue Systems |
| 84 | RabbitMQ vs. Kafka vs. ActiveMQ |
| 85 | Scalability and Performance |
| 86 | What is a Distributed File System? |
| 87 | Architecture of a Distributed File System |
| 88 | Batch Processing vs. Stream Processing |
| 89 | XML vs. JSON |
| 90 | Synchronous vs. Asynchronous Communication |
| 91 | Push vs. Pull Notification Systems |
| 92 | Microservices vs. Serverless Architecture |
| 93 | Message Queues vs. Service Bus |
| 94 | Stateful vs. Stateless Architecture |
| 95 | Event-Driven vs. Polling Architecture |
- Browse the topic-specific Markdown files for detailed notes.
- Use the table above to navigate and track your progress.
- Each file covers one topic for easy reference.
Contributions are welcome! Feel free to fork the repository and make improvements. Open an issue if you encounter any problems or want to suggest enhancements.
This project is licensed under the MIT License. See the LICENSE.md file for details.
If you have any questions or suggestions, feel free to reach out via GitHub issues or discussions.
Happy Learning! 🚀