Introduction to Modern System Design

System design turns requirements into decisions about components, interfaces, and data. This course develops that reasoning through reusable building blocks, complete design problems, and revisions based on what a first design gets wrong.

Understanding System Design

System Design is the process of defining components and their integration, APIs, and data models to build large-scale systems that meet a specified set of functional and non-functional requirements.

System design draws on computer networking, parallel computing, and distributed systems. Distributing work can increase capacity, but scalability depends on how the components divide and coordinate that work. The design must account for this coordination as well as the performance and reliability requirements.

Introduction to Modern System Design figure 1

System design aims to build systems that are reliable, effective, and maintainable.

Reliable systems handle faults, failures, and errors gracefully.
Effective systems meet user needs and business requirements.
Maintainable systems are flexible, scalable, and easy to extend with new features.

Modern System Design using building blocks

We use common design elements, such as load balancers, as basic building blocks. This approach introduces modularity and allows us to:

Discuss the specific design challenges of each building block in detail.
Focus on problem-specific logic by referencing these blocks rather than redesigning them from scratch.

The course organizes this material around 16 building blocks.

Modern systems are designed using fundamental building blocks

About this System Design course

This course teaches you to design systems that scale with user growth, remain available during faults, and meet performance goals. Real-world system building is an iterative process: you start with a baseline design, measure performance, and refine it.

For each design problem, connect the requirements to the choices you make. Use the examples to understand why a component belongs in a design and when a different choice would be more appropriate.

Memorizing a complete solution can help you recognize a familiar problem, but it does not explain how to respond when the requirements change. We therefore work from the requirements and justify the design step by step. Technical constraints inform the answer; choosing between workable alternatives still requires judgment.

An illustration of a drafting board, reference book, and pencil. — Every choice has a reason

The case studies explain choices such as which database, caching strategy, or load balancing technique to use. Each explanation considers both the benefit and the cost of the choice.

The problems cover scalability, availability, maintainability, consistency, and fault tolerance across familiar and newer applications. Read the assumptions alongside each solution: they define its scope and explain why its choices may differ from those in another case.

An open sketchbook sits among three differently shaped architectural models, suggesting several possible approaches to a problem. — Explore the design space

Iterative process: Real systems improve through iteration. We often start simple, identify bottlenecks, and refine the design. While time constraints can limit this process, we recommend two iterations:

First iteration: Dedicate about 80 percent of the time to creating the initial design.
Second iteration: Focus on improvements and refinements.

Alternatively, you can adjust the design as new insights emerge. Discovering new details is inevitable as you spend more time on a problem.

Two offset tracing sheets and a pencil show an initial sketch becoming a more deliberate drawing. — Refine the blueprint

Some problems guide you through the design; others ask you to make a decision before reading the reference explanation. Use the written questions and quizzes to test your reasoning, then compare the assumptions and tradeoffs behind your answer.

An open notebook, pencil, cup, and growing plant form a quiet study scene. — Make room for practice

Check your understanding with the following exercise.

Why should a system design be revised after its first version?

Your response

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Who should take this System Design course?

The course serves several kinds of learners:

Interview preparation: Practice clarifying requirements, estimating a workload, and explaining design decisions. Begin with the interview preparation lesson to plan a session.
Software developers: This course is primarily for back-end developers, principal engineers, and solution architects who handle user data. However, full-stack and front-end developers will also benefit from understanding the broader architecture. Additionally, Site Reliability Engineers (SREs) will learn to identify the root causes of complex production issues.
Managers: Product and engineering managers must understand System Design to steer the development of scalable, performant systems.
Learners: Anyone interested in how large applications are built and changed can use these cases to study the decisions behind the software. This architectural context also helps when using AI tools to generate implementation code.

Prerequisites for this System Design course

If you are new to this material, start with Foundations of System Design. Before the larger case studies, be comfortable tracing a network request, distinguishing a process from a thread, and explaining storage, caching, replication, and common failure modes. You do not need to have operated a global service; use the building-block lessons to strengthen specific gaps.

How to use the first design

Before reading a refinement, write down which requirement the current design fails to meet and which component you would change. Then compare your reasoning with the reference. If you chose a different component, check whether you also assumed a different workload or failure tolerance. This makes the course’s iterative method a concrete practice routine.