Mastering System Design: From Basics to Cracking Interviews

This video introduces the importance of networking in system design, explaining how it enables scalability, reliability, and performance in large-scale systems. We cover key networking aspects like data exchange, load balancing, security, and efficiency, showing why a strong networking foundation is essential for designing robust and high-performance architectures.

"Understanding IP Addresses" explores the structure and function of IP addresses, including IPv4 and IPv6. It covers how IP addresses identify devices on a network, the role of subnets, and the difference between public and private IPs. This lecture provides essential knowledge for networking, system design, and troubleshooting connectivity issues.

This lecture covers the Domain Name Resolution process, explaining how domain names are translated into IP addresses through recursive and iterative queries. It explores caching mechanisms that improve efficiency and reduce latency. Finally, we discuss the importance of DNS in large-scale systems, including strategies for reliability, load balancing, and mitigating failures like DNS attacks or outages.

In this lecture, we’ll break down the Client-Server Model, a fundamental architecture powering modern computing. You'll learn how clients and servers communicate, the request-response cycle, and real-world applications like web browsing, APIs, and databases. We’ll also explore key concepts such as synchronous vs. asynchronous communication and stateless vs. stateful servers, helping you understand how different architectures impact system performance and scalability. By the end, you'll have a solid grasp of this model and its role in designing efficient and scalable systems.

In this lecture, we’ll explore the differences between Forward Proxies and Reverse Proxies, their roles in network architecture, and when to use each. A forward proxy sits between clients and the internet, providing anonymity, content filtering, caching, and bypassing restrictions. A reverse proxy sits in front of backend servers, handling load balancing, security, caching, and SSL termination. Understanding these proxies is crucial for enhancing security, performance, and scalability in modern systems. By the end, you’ll know how to leverage them effectively in real-world applications.

In this lecture, we introduce Load Balancing, a foundational concept in scalable system design. We begin by understanding the challenges of handling growing traffic with a single server and explore how load balancers help distribute requests across multiple servers to improve scalability, availability, and reliability. We examine the basic flow of traffic through a load balancer, discuss concepts such as redundancy, health checks, and failover at a high level, and see how load balancing helps systems remain responsive and resilient as demand increases. By the end of this lecture, you'll understand why load balancing is a critical building block of modern distributed systems and where it fits within the broader system design landscape.

In this lecture, we explore API Gateways, a crucial component in modern system architecture. You'll learn how an API Gateway acts as a reverse proxy, managing client requests, routing traffic to backend services, and enhancing security. We’ll cover key benefits like authentication, rate limiting, caching, load balancing, and request transformation, making API management more efficient and secure. By the end, you’ll understand when and why to use an API Gateway in a scalable system design.

In this lecture, we explore Content Delivery Networks (CDNs) and their role in improving performance and reducing latency in distributed systems. You'll learn how CDNs cache content closer to users, reduce server load, and enhance reliability. We’ll also discuss key CDN strategies, benefits, and real-world use cases in large-scale system architectures.

This lecture provides a high-level recap of key networking concepts covered in the course, emphasizing their importance in system design. It highlights topics such as IP addressing, DNS, proxies, load balancing, API gateways, and CDNs, summarizing their role in building scalable and efficient systems.

This section explores the essential communication protocols that power modern system design. You'll learn how data moves across networks, the differences between key protocols like TCP, UDP, HTTP, REST, WebSockets, gRPC, and GraphQL, and when to use each. Mastering these protocols is crucial for designing scalable, efficient, and reliable systems.

This lecture covers the two fundamental transport layer protocols: TCP and UDP. You'll learn how TCP ensures reliable, ordered communication, while UDP prioritizes speed with a connectionless approach. We'll explore their key differences, real-world use cases, and when to choose one over the other in system design.

In this lecture, we explored HTTP (HyperText Transfer Protocol), the foundation of web communication. We covered how HTTP works, its request-response cycle, and its stateless nature, which requires mechanisms like cookies, sessions, and tokens to maintain state. We also discussed HTTP methods (GET, POST, PUT, DELETE, PATCH) and status codes (2xx, 3xx, 4xx, 5xx), which help define interactions between clients and servers. Finally, we introduced HTTPS, the secure version of HTTP, which ensures data encryption, integrity, and authentication.

This lecture builds a strong foundation for understanding RESTful APIs, web security, and performance optimization, setting the stage for deeper discussions in future lessons.

In this lecture, we explore REST (Representational State Transfer)—a widely used architectural style for building scalable and stateless web APIs. We cover its core principles, constraints, and best practices for designing RESTful APIs. You'll learn about resources & endpoints, HTTP methods, JSON vs. XML, and real-world examples like the Twitter API and GitHub API. By the end of this lecture, you’ll have a strong foundation in RESTful API design and understand how to create efficient, scalable, and well-structured APIs.

In this lecture, we explore real-time communication and its importance in modern system design. We cover WebSockets, which provide a persistent, full-duplex connection for low-latency, bidirectional data exchange, and Long Polling, which simulates real-time updates using HTTP. We compare their use cases, advantages, and limitations, helping you decide when to use each approach. By the end of this lecture, you'll understand how to design efficient real-time systems and make informed architectural choices for applications like chat apps, stock market feeds, notifications, and IoT devices.

In this lecture, we explore gRPC and GraphQL, two modern alternatives to traditional REST APIs. We discuss their architectures, how they work, and their ideal use cases. gRPC offers high-performance, low-latency communication, making it perfect for microservices and real-time streaming, while GraphQL provides flexible data fetching, reducing over-fetching and under-fetching, making it ideal for frontend-driven applications. By the end of this lecture, you'll understand when and why to use each protocol and be prepared to justify your choices in system design interviews.

We covered essential communication and API protocols—TCP/UDP, HTTP, REST, WebSockets, gRPC, and GraphQL—laying the foundation for designing scalable systems.

Software architecture is the structure of a system, including its components and their interactions. It significantly impacts key factors like scalability, maintainability, and performance, all of which are crucial for system design. The architectural choices you make directly influence how the system behaves, affecting its ability to grow, adapt, and perform efficiently under load.

This lecture on Software Architecture Patterns & Styles explores the key architectural approaches used in modern software design. It covers a variety of architectural styles, including Monolithic, Layered (N-Tier), Client-Server, Microservices, and Event-Driven architectures. You'll learn about the pros and cons of each style, real-world applications, and the trade-offs involved in choosing one architecture over another. Additionally, the lecture highlights the factors influencing architecture selection, such as business needs, scalability, performance, and maintainability. This lecture equips you with the knowledge to evaluate and select the right architecture for different system requirements.

In this lecture, we explore Multi-Tier Architecture, a software design pattern that structures applications into distinct layers for improved scalability, maintainability, and security. We dive into 2-Tier, 3-Tier, and N-Tier architectures, highlighting their differences, use cases, and how they handle business logic, data storage, and user interaction. Key topics include latency considerations, scaling strategies, and the impact of adding more tiers to system performance. By the end of this lecture, you'll understand how multi-tier architectures enable scalable, reliable, and secure systems, and be ready to apply these concepts to real-world applications.

This lecture covers Microservices Architecture, where applications are built as independent services that can scale and deploy separately. We explore its differences from monolithic architecture, core components like API Gateway and Service Discovery, communication methods (REST, gRPC, Event-Driven), and challenges such as data consistency and debugging. Real-world examples from Netflix, Uber, and Amazon highlight the benefits of microservices, along with scaling strategies for robust systems.

In this lecture, we explore Event-Driven Architecture (EDA)—a powerful design approach for building scalable, asynchronous, and decoupled systems. We break down the key components of EDA, compare Pub-Sub vs. Event Streaming, and discuss architectural patterns like CQRS & Event Sourcing. You'll also learn about real-world use cases, challenges like eventual consistency & fault tolerance, and best practices to design reliable event-driven systems. By the end of this session, you'll have a solid understanding of when and how to apply EDA in modern system design.

A recap of key architectural patterns, their trade-offs, and best practices. Next, we move into Web Concepts in System Design, covering web fundamentals, session management, serialization, and security.

In this lecture, we’ll introduce the foundational principles of web applications and how they function in modern system design. We’ll explore key topics such as the client-server model, the request-response cycle, and the distinction between stateless and stateful interactions. Additionally, we’ll discuss why scalability, security, and performance are critical in web-based architectures. This lecture sets the stage for deeper discussions on managing state, data serialization, and web security in upcoming sessions.

This lecture explores how web applications manage user state despite HTTP being stateless. We cover key session management techniques, including server-side sessions, cookies, and token-based authentication (JWTs). You'll learn about security risks like session hijacking and CSRF, along with best practices for scaling session management using distributed storage solutions like Redis and Memcached. By the end, you'll have a solid understanding of how to implement secure and scalable session management in modern web applications.

Serialization is a crucial process in system design, enabling efficient data exchange between applications and storage systems. This lecture covers the fundamentals of serialization, explores common formats like JSON, XML, and Protobuf, and discusses their trade-offs in terms of readability, efficiency, and compatibility. You'll also learn how serialization is used in APIs, caching, and databases, along with its impact on performance factors like bandwidth, CPU, and memory usage. By the end, you'll understand how to choose the right serialization format based on system requirements.

In this lecture, we explored Cross-Origin Resource Sharing (CORS) and its role in web security. We started with the Same-Origin Policy (SOP) and why browsers restrict cross-origin requests. Then, we covered how CORS works, including preflight requests and CORS headers. We discussed handling CORS in REST & GraphQL APIs, common misconfigurations that lead to security risks, and mitigation strategies like Reverse Proxies and API Gateways. Finally, we looked at alternatives to CORS, such as backend proxying. With this knowledge, you can now configure CORS securely in modern web applications!

This section covered essential Web Concepts in System Design, including how web applications work, managing state with sessions, serialization for data exchange, and CORS for secure cross-origin requests. We explored best practices, security risks, and real-world applications of these concepts. With this foundation, we're now ready to move into our next topic: Scalability in System Design!

Learn what scalability truly means in system design and why it’s critical for building reliable, high-performance applications. This lecture covers the types of scalability (vertical vs. horizontal), real-world reasons systems need to scale, and common challenges such as latency, bottlenecks, cost, and downtime. A perfect starting point to understand how systems grow and what it takes to keep them efficient under load.

Dive deep into the core strategies for scaling systems: vertical, horizontal, and diagonal. Understand how each method works, their trade-offs in terms of cost, complexity, and performance, and when to choose the right approach based on your system’s needs and growth patterns.

In this lecture, we explore the fundamentals of load balancing—why it's essential for performance, reliability, and scalability in modern systems. You'll learn about different types of load balancers (Layer 4 vs. Layer 7), popular algorithms (Round Robin, Least Connections, etc.), and how load balancing fits into distributed architectures. We'll also cover real-world use cases and challenges like session persistence and health checks.

Learn how modern systems scale dynamically with autoscaling to handle changing workloads efficiently. This lecture covers how autoscaling works, solutions from AWS, Azure, and GCP, monitoring strategies, and cost optimization techniques—all essential for building scalable, cloud-native architectures.

This slide recaps key topics from the section, including scalability fundamentals, scaling strategies, load balancing techniques, and autoscaling best practices across cloud providers. It sets the stage for the next section on Database and Storage in system design.

In this lecture, we explore the critical role of storage in system design. You'll learn about different data types (structured vs. unstructured), categories of storage (database, object, file, block), and key storage properties like durability, availability, and consistency. We dive into trade-offs in storage design, including the CAP theorem and its real-world implications. The session wraps up with practical examples from e-commerce, streaming, and log aggregation systems—setting the stage for deeper dives into SQL and NoSQL in the next lecture.

This lecture explores the two primary types of database models: Relational (SQL) and Non-Relational (NoSQL). It covers how databases work, key concepts like ACID vs. BASE, and the differences in structure, use cases, and scaling strategies. You'll learn about various NoSQL types (Document, Key-Value, Columnar, Graph), understand the CAP theorem, and discover how to choose the right model for different real-world scenarios. The lecture also introduces the concept of polyglot persistence in modern architectures.

In this lecture, we dive into advanced database strategies that power scalable, resilient systems. You'll learn about vertical vs. horizontal scaling, replication models like leader-follower and read replicas, various sharding strategies including consistent hashing, and the concept of polyglot persistence. These techniques are essential for designing high-performance systems that handle large-scale data and traffic efficiently.

In this lecture, we explore object storage—a scalable and distributed storage architecture ideal for handling unstructured data like images, videos, and backups. You'll learn the core concepts of objects, buckets, and metadata, how object storage compares to file and block storage, and when to use it. We also cover popular platforms like Amazon S3, Google Cloud Storage, and Azure Blob, along with key performance and cost considerations. Perfect for understanding how modern systems manage massive volumes of data efficiently.

This lecture covers the basics of file systems and how distributed storage works. We explore how data is managed across nodes, the role of replication for fault tolerance, and key trade-offs like latency and complexity in large-scale storage solutions.

In this lecture, we explored what Big Data is and why it matters in modern system design. We introduced the 6 V’s — Volume, Velocity, Variety, Veracity, Value, and Variability — as key characteristics that define big data.

We discussed why traditional storage systems fail at big data scale and how distributed storage solutions like HDFS, Amazon S3, and Delta Lake address those challenges.

You also learned about common big data workloads, such as logs, clickstreams, IoT data, and machine learning pipelines — and how they require robust, scalable processing.

Finally, we introduced the two main paradigms for handling big data: Batch Processing and Stream Processing, giving you a foundation to choose the right strategy for different use cases.

This sets the stage for designing efficient, large-scale data systems in the real world.

This section explored key storage types, database models, and big data fundamentals. You now know when to use SQL, NoSQL, object storage, and distributed systems for scale and performance.

In this lecture, we lay the foundation for understanding performance in system design. You’ll learn the key dimensions of performance — speed, efficiency, and scalability — and explore the crucial differences between latency and throughput. We’ll cover how to define and measure performance using SLAs, SLOs, and percentiles, and why tail latency matters. You’ll also get an overview of performance testing types and real-time monitoring tools, setting the stage for building systems that are fast, resilient, and user-friendly.

In this lecture, we dive into caching — one of the most effective techniques for improving system performance. You'll learn why caching matters, the different types of caches (client-side, server-side, CDN, database), common caching strategies like write-through and lazy loading, eviction policies such as LRU and LFU, and how tools like Redis bring caching to life in real-world architectures. By the end, you’ll understand how to use caching to reduce latency, ease system load, and scale efficiently.

This lecture explores how messaging queues help build scalable, decoupled systems by enabling asynchronous communication between services. We cover when to use queues, how popular brokers like RabbitMQ and Kafka work, and the trade-offs between different delivery guarantees. Real-world use cases and best practices help solidify your understanding of designing robust, event-driven architectures.

In this lecture, we explore the key concepts of concurrency and parallelism, and their significance in system design. We’ll define concurrency as the ability to manage multiple tasks at once, even on a single CPU core, and parallelism as the simultaneous execution of tasks across multiple cores. You'll learn the difference between processes and threads, and understand thread pools and worker models for efficient task management. The lecture also covers asynchronous processing, concurrency in web servers, and addresses common pitfalls like race conditions and deadlocks. Finally, we'll discuss best practices and real-world examples to help you design scalable and efficient systems.

This lecture covers Database Performance Optimization Techniques, focusing on key strategies for improving database efficiency and scalability. Topics include replication, sharding, and partitioning for distributing and scaling data, the CAP Theorem for understanding trade-offs in distributed systems, and indexing to speed up queries. It also explores normalization vs. denormalization based on workload types, and additional techniques such as connection pooling, query optimization, materialized views, and batching/pagination to further enhance database performance.

This slide summarizes the key topics covered in Section 8: System Performance, including system performance fundamentals, caching, messaging, concurrency, and database optimization techniques.

In this lecture, we explore the fundamentals of System Reliability, a critical aspect of system design that ensures systems remain available, resilient, and trustworthy. We cover essential metrics like MTBF (Mean Time Between Failures), MTTR (Mean Time To Recovery), and SLAs (Service Level Agreements), which help quantify and manage reliability. The lecture also discusses the importance of designing systems that anticipate failure and includes strategies for achieving high availability and fault tolerance, especially in distributed and cloud-native environments. Finally, we introduce key concepts like redundancy, health checks, circuit breakers, and the "design for failure" mindset, setting the stage for deeper exploration of reliability in future lectures.

This lecture explores how to build resilient systems that remain operational during failures. You'll learn key concepts like high availability, fault tolerance, and failover strategies. We cover redundancy techniques (N+1, active-active vs. active-passive), graceful degradation, and real-world high availability patterns including load balancers and replication. The session also delves into health monitoring and self-healing systems, equipping you with practical design principles to ensure uptime and service continuity in modern distributed architectures.

This lecture covers the importance of backup and recovery in system design, focusing on how to protect data and ensure business continuity in case of failures. We explore various backup types (full, incremental, and differential), recovery models (cold, warm, hot), and key metrics like RTO and RPO. Best practices for automating, securing, and testing backups are highlighted, along with the 3-2-1 backup rule. By the end, you'll understand how to build resilient systems that can recover quickly and cost-effectively.

Disaster Recovery in Practice focuses on the strategies and best practices for designing robust disaster recovery plans for mission-critical applications. This lecture covers key concepts like failover mechanisms, geo-redundancy, and quorum-based design, highlighting the importance of combining backup and failover for true system resilience. Through a real-world case study, we explore the challenges of maintaining continuity during regional outages, cyber-attacks, and hardware failures. The lecture also emphasizes the need for automated recovery testing and regular DR drills to ensure your system can recover seamlessly when disaster strikes.

In this video, we recap the key concepts covered in the section on System Reliability and Disaster Recovery. We review the importance of building resilient systems through strategies like high availability, fault tolerance, and effective disaster recovery plans. Key topics include backup types, failover mechanisms, and geo-redundancy, with a focus on the trade-offs, best practices, and testing for ensuring system uptime and recovery. This video provides a comprehensive overview, preparing you for designing systems that are both reliable and resilient.

In this lecture, we explore the essential principles of security in distributed systems, focusing on the foundational concepts that ensure the confidentiality, integrity, and availability of your system. We cover key topics such as the CIA triad, threat modeling, common attack vectors, and best practices for secure system design. By the end of the lecture, you'll understand how to embed security throughout the software development lifecycle and be equipped with practical strategies for designing secure systems.

This lecture dives into the core concepts of authentication and authorization in system design. You'll learn how systems verify user identity (authentication) and control access to resources (authorization). We explore common methods like Basic Auth, OAuth2, OpenID Connect, and JWTs, and compare session-based vs. token-based authentication. We also cover access control models (RBAC, ABAC, DAC, MAC) and discuss how Single Sign-On (SSO) and identity federation enhance usability and security across platforms.

In this lecture, we explore how to safeguard data through encryption, hashing, and secure protocols. You’ll learn the difference between data at rest and in transit, understand symmetric vs. asymmetric encryption, dive into TLS/SSL, and see how Public Key Infrastructure (PKI) builds digital trust. We also cover best practices for password storage (hashing + salting) and secure API communication using HTTPS, JWT, OAuth, and mTLS. By the end, you'll be equipped with essential tools and techniques to protect sensitive data and ensure secure interactions across your systems.

This lecture covers the Zero Trust Security Model, which operates on the principle of ‘Never trust, always verify’. It emphasizes continuous authentication and authorization for every request, regardless of its source, ensuring no user, device, or request is inherently trusted. The model is implemented through microservices using mutual TLS, strict access controls, and continuous verification across both internal and external networks. The lecture highlights how Zero Trust enhances security by minimizing unauthorized access, data breaches, and lateral movement, applicable to both on-premise and cloud environments.

This section covered key security concepts in distributed systems, including data protection, authentication, and network security. We explored best practices for securing cloud environments, microservices, and APIs, setting the foundation for building secure and resilient systems.