Grokking the Principles and Practices of Advanced System Design
This course will get you grokking system design and ace the advanced system design interview in no time!
Advanced
158 Lessons
20h
Certificate of Completion
This course will get you grokking system design and ace the advanced system design interview in no time!
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This course includes
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111 Quizzes
This course includes
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111 Quizzes
Course Overview
What You'll Learn
Course Content
Course Overview
This course teaches you how large, real-world systems are built and operated to meet strict service-level agreements. You’ll learn the many building blocks of a modern system’s design by picking and combining the right pieces and understanding the trade-offs between them.
You’ll learn about some great systems from hyperscalers such as Google, Facebook, and Amazon. This course has hand-picked seminal work in system design that has stood the test of time and is grounded on strong principles. You will learn a...Show More
TAKEAWAY SKILLS
System Design
Prepare For Interview
What You'll Learn
Working knowledge of building large-scale systems
Ability to evaluate common system design trade-offs
Ability to map interview questions and on-job design tasks to well-known systems
Familiarity with the complexity of real-world systems behind a seemingly simple system
Understanding of large cloud service providers hosted in geographically dispersed data centers
What You'll Learn
Working knowledge of building large-scale systems
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Course Content
1
Prologue
This chapter sets the stage for the course, emphasizing learning from historical systems and balancing innovation with established design practices.
This chapter sets the stage for exploring distributed file systems, focusing on advancements in data management with systems like GFS, Colossus, and Tectonic.
This chapter covers the Google File System (GFS), focusing on efficient management of large data files with scalability, fault tolerance, and high throughput.
This chapter covers Colossus, which improves scalability and performance over GFS using a distributed metadata model for better data management and low latency.
This chapter discusses Tectonic File System, providing scalable storage with performance isolation and optimized resource management for diverse workloads.
This chapter covers Megastore, blending NoSQL scalability with relational features for high availability, ACID transactions, and optimized cloud performance.
This chapter covers Google Spanner, combining relational features with NoSQL scalability for strong consistency, high availability, and global data management.
This chapter introduces key-value stores, crucial for caching, NoSQL databases, and enhancing scalability and availability in modern distributed applications.
This chapter explores Memcache scaling strategies, addressing performance, consistency, and network efficiency challenges across various operational levels.
This chapter covers SILT, which optimizes key-value storage with a multi-store architecture, focusing on memory efficiency, low latency, and data management.
This chapter covers DynamoDB, a managed NoSQL service designed for high availability, strong durability, and scalability, meeting diverse data management needs.
This chapter covers Chubby, a distributed locking service that enhances coordination, availability, and fault tolerance in Google’s systems with robust design.
This chapter covers MapReduce, which simplifies processing large datasets with a user-friendly model that enables efficient parallelization and fault tolerance.
This chapter introduces Kafka, a powerful messaging system for real-time event streaming, known for high scalability, efficiency, and reliable data delivery.
Understanding Consensus: Two Generals, FLP, & Byzantine Generals
4 Lessons
This chapter explores consensus challenges in distributed systems, focusing on the Two Generals problem, FLP impossibility, and Byzantine Generals problem.
This chapter explains 2PC, a consensus protocol to ensure atomicity in distributed transactions by coordinating across nodes and handling failure challenges.
This chapter covers State Machine Replication, which ensures fault tolerance by using replicated state machines to maintain consistency despite failures.
This chapter covers Raft, a consensus algorithm ensuring consistency and fault tolerance through leader election, log replication, and cluster management.
This chapter concludes the course by emphasizing applying system design principles to real-world challenges while encouraging ongoing exploration and learning.
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