Kafka Mastery: Building StreamSocial

A 60-Day Intensive Course in Event-Driven Systems

Why This Course?

Picture this: You post a tweet. Within milliseconds, it appears on your followers’ feeds, triggers real-time notifications, updates analytics dashboards, gets indexed for search, and feeds into recommendation algorithms. Behind this seemingly simple action lies a symphony of distributed systems orchestrating billions of events per day.

Most Kafka courses teach you the basics: producers, consumers, topics. Then you’re left wondering, “How do I actually build something real?” This course bridges that gap. You’ll build StreamSocial—a production-grade social media platform processing millions of events per second, just like Twitter, LinkedIn, or TikTok do today.

Every single day, you’ll write code. No theory-heavy lectures. No death by PowerPoint. Just you, your IDE, and real systems coming to life.

What You’ll Build

StreamSocial: A complete event-driven social media platform featuring:

• Real-time Feed Generation: Posts appear instantly across millions of timelines

• Event Sourcing Architecture: Every action captured as immutable events

• Stream Processing Pipelines: Real-time analytics, trending topics, content moderation

• Multi-Region Deployment: Active-active replication across data centers

• Exactly-Once Semantics: No lost posts, no duplicate notifications

• Dynamic Scaling: Handle traffic spikes from 1K to 10M requests/second

• Complete Observability: Metrics, traces, and logs for every event

By Day 60, you’ll have a portfolio project that demonstrates mastery of distributed systems—something that makes hiring managers lean forward during interviews.

Who Should Take This Course?

This course is designed for:

• Fresh CS Grads: Transform theoretical knowledge into production skills

• Software Engineers: Level up from CRUD applications to event-driven architectures

• Backend Developers: Learn how platforms like Netflix and Uber actually work

• Architects: Design systems that scale without rewriting everything

• DevOps/SRE: Understand the applications you’re keeping alive at 3 AM

• Data Engineers: See how streaming systems feed your data lakes

• Product Managers: Make informed technical decisions about trade-offs

• Technical Writers: Document systems you truly understand

Prerequisites: Basic programming knowledge (any language), familiarity with APIs, and comfort with the command line. We’ll teach you everything else.

What Makes This Course Different?

1. Daily Coding—No Exceptions

Every single day includes a hands-on coding exercise. No filler content. No “reading days.” You build muscle memory by writing code every day.

2. Production-Grade From Day One

We don’t build toy examples. From Day 1, you’re writing code that could run in production. Error handling, monitoring, testing—it’s all there.

3. Real Numbers, Real Trade-offs

We don’t say “it scales.” We show you the math: “With 100M users, 50 posts/day, and 200 followers average, you’ll process 2.3 billion events daily. Here’s how much that costs on AWS.”

4. Failure-Driven Learning

Each week, we deliberately break something, then fix it. Kafka cluster crashes? Consumers lag? Disk fills up? You’ll debug real issues, not theoretical ones.

5. Evolution, Not Revolution

Watch your code evolve from a simple producer-consumer to a multi-region, exactly-once, GDPR-compliant platform. You’ll understand why complexity exists.

Key Topics Covered

Distributed Systems Fundamentals

• Consensus algorithms and leader election

• CAP theorem in practice (with actual examples)

• Clock synchronization and event ordering

• Partitioning strategies for billion-user systems

Kafka Deep Dive

• Internal architecture: logs, segments, indexes

• Zero-copy transfers and page cache optimization

• Replication protocols and ISR management

• Consumer group coordination and rebalancing

• Exactly-once semantics implementation

Stream Processing

• Kafka Streams API from basics to advanced

• Stateful processing with RocksDB

• Windowing, aggregations, and joins

• Event time vs. processing time

• Late event handling strategies

Production Operations

• Multi-region active-active replication

• Disaster recovery and data loss prevention

• Performance tuning and capacity planning

• Security: encryption, authentication, authorization

• Cost optimization at scale

Advanced Patterns

• CQRS and Event Sourcing

• Saga pattern for distributed transactions

• Change Data Capture (CDC)

• Schema evolution with backward/forward compatibility

• Polyglot persistence integration

Prerequisites

Must Have:

• Programming experience in Java, Python, or Go (we provide code in all three)

• Understanding of HTTP APIs and JSON

• Command-line comfort (cd, ls, running scripts)

• Docker basics (we’ll teach Kafka-specific Docker usage)

Nice to Have (we’ll teach you):

• Basic SQL knowledge

• Familiarity with microservices concepts

• Cloud platform experience (AWS/GCP/Azure)

Setup Required:

• Laptop with 16GB RAM (8GB minimum)

• Docker Desktop installed

• IDE of choice (IntelliJ, VS Code, or PyCharm)

Course Structure

Phase 1: Foundations (Days 1-15)

Build your first event-driven system. Learn Kafka fundamentals by implementing a basic social feed.

Phase 2: Scale (Days 16-30)

Handle 10,000x more traffic. Add partitioning, consumer groups, and horizontal scaling.

Phase 3: Reliability (Days 31-45)

Make it bulletproof. Implement exactly-once semantics, replication, and failure recovery.

Phase 4: Production (Days 46-60)

Deploy to production. Add monitoring, security, multi-region support, and cost optimization.