Fundamentals of Distributed Systems

Description

What you’ll learn

Understand what makes systems distributed, why they exist, and the trade-offs between scalability, consistency, and availability.
Learn how services communicate reliably across unreliable networks using HTTP/s, RPCs, message queues, and APIs.
Learn how services coordinate reliably and how heartbeats, leader election, and gossip protocols keep systems alive.
Discover how systems achieve scalability through partitioning (range, hash, consistent hashing) and replication (single-leader, multi-leader and leaderless).
Understand how data stays consistent across nodes using 2-Phase Commit (2PC), Saga Pattern, and the Outbox Pattern — and when each should be used.
Explore how real-world systems scale using load balancers, CDNs, API gateways, microservices, and queues power massive applications like Netflix & Amazon
Learn to design systems that survive downstream failures and become resilient using timeouts, retries with jitter, circuit breakers, and how to survive upstream
Learn to design systems that survive upstream failures using load shedding , load leveling and rate limiting and isolate issues with bulkhead pattern
See how logs, metrics, and traces work together to help you detect, debug, and improve distributed systems in production.
Build the mindset to design scalable, resilient architectures, reason about trade-offs, and make confident design decisions.

السلام عليكم ورحمة الله وبركاته ,,
اللهم اجعله عملًا متقبلًا , واللهم اجعله علمًا ينتفع به وعلمنا ما ينفعنا واستعملنا ولا تستبدلنا

If you’ve been reading about distributed systems, watching talks, or hearing buzzwords like replication, partitioning, or consistency — but still feel there’s a missing link between the theory and how real systems actually work… this course is for you, Insha’Allah.

Whether you’re a backend developer who wants to understand scalability, a software engineer preparing for system design interviews, or someone who simply wants to know how Netflix, Amazon, and Google keep their systems running reliably at scale — this course will guide you step-by-step through the core building blocks of distributed systems.

There are no abstract “theoretical” lectures here — no equations, no complicated math. Just clear, real-world explanations with visual diagrams, analogies, and patterns that you can apply directly in your work.

So get ready for a new kind of adventure — one that will make you see systems differently and able to design and build large scale distributed systems!

Course Overview

This course aims not just to help you understand distributed systems, but to help you learn how to design and build large scale distributed systems.

You’ll learn to reason about failure, latency, availability, and data consistency — the same way large-scale systems do.

By the end, you’ll be able to look at any architecture and understand:

How it scales.
How it stays consistent.
And how it survives failure.

More importantly, you’ll learn the mindset behind designing robust, fault-tolerant, and resilient systems.

Course Structure

The course is structured to be hands-on and story-driven — we’ll go from small to big, from simple to complex:

Foundations: Understand what makes a system distributed, and why we need one.
Communication: Learn how services talk to each other reliably with TCP , TLS/SSL , HTTP/s, DNS and APIs.
Coordination: Learn how services coordinate their tasks reliably with each other and how heartbeats, leader election, and gossip protocols keep systems alive.
Data Partitioning & Replication: Dive into the heart of scalability — with real examples of how data is distributed across nodes.
Consistency Models: Strong, eventual, causal — all explained simply and practically.
Resiliency Patterns: Explore retries, circuit breakers, timeouts, rate limiting, bulkhead to isolate failure, and how real systems stay alive during failure.
Load Management: Learn about load shedding, backpressure, and autoscaling to protect your systems under pressure.
Observability: Understand how logs, metrics, and traces help teams detect and fix issues in distributed environments.

Every concept connects to real-world systems — from AWS S3 and Kafka to Netflix’s microservices and Amazon’s DynamoDB.

What You’ll Get

Visual diagrams and animations to understand system interactions.
Real-world examples from popular distributed systems.
Code snippets and conceptual demos to make things concrete.
Lifetime access and future updates as new topics are added.
PDF summaries for quick revision of each major topic.

Who this course is for:

Software Engineers working with microservices who often face issues like slow communication, data sync problems, or unclear service boundaries — and want to finally understand why these things happen and how to fix them.
Software Engineers preparing for System Design Interviews.
Developers who want to understand the “why” behind distributed systems.
Developers who’ve used distributed tools (Kafka, Redis, Nginx, AWS S3, etc.) but want to understand how they work underneath.
Anyone curious about how large-scale systems stay online, consistent, and resilient.
Students and professionals transitioning into distributed system design who want to bridge the gap between theory and real-world application.