Books

Master distributed systems through visual diagrams — from clock drift and CAP to Paxos, Raft, and distributed transactions, explained with clear illustrations instead of dense academic papers.

PySpark from page one. Ten chapters that take a Python user who knows pandas and turn them into someone who can write, read, and debug production PySpark, without a three-chapter detour through distributed-computing theory.

Artificial Intelligence has become the new global power race. Nations are competing for data, infrastructure, and algorithmic dominance that will define the future world order.

Design resilient, production-ready microservices architectures with confidence. Learn how API gateways, service meshes, and observability tools work together to build scalable and secure distributed systems.

Architecture. Teams. Business. Aligned. Finally, a guide that connects the dots. From Team Topologies to Flexible Project Management, learn how to build systems that align with your business goals instead of fighting against them. Stop estimating and start engineering your path to confidence.

By the time you finish this book, you should be able to make your systems observable across microservices, AI workloads, security monitoring, and hybrid cloud infrastructure. This book will help you learn how to effectively instrument, generate, collect, and export telemetry data (metrics, logs, and traces) to analyze your software’s performance and behavior.

The Scaling Playbook From WordPress to 1 million orders. One company's 5-year journey through every scaling decision, mistake, and hard-won principle. No code. No fluff. Just architecture thinking.

JSON succeeded not because it was better--XML had schemas, namespaces, and 10 years of tooling, but because it understood modularity in ways XML never could. This book deconstructs how a deliberately incomplete format defeated a comprehensive standard, then shows you the production patterns (JSON Schema, JSONB, MessagePack, versioning strategies) that make JSON systems scale from prototype to billions of requests.

Master AI Agents from Architecture to ProductionBuild autonomous agent systems that actually work in production. This comprehensive guide takes you from understanding ReAct patterns to orchestrating multi-agent systems at scale. What You'll Master:✅ Agent architectures: When to use agents vs RAG vs fine-tuning✅ Reasoning patterns: ReAct, Chain-of-Thought, Plan-and-Execute✅ Multi-agent orchestration with proper coordination protocols✅ Production deployment with error handling, monitoring, cost optimization✅ Tool calling, memory systems, and context management Who This Is For: Software engineers building LLM applications, backend engineers adding agentic capabilities, senior engineers preparing for AI agent interviews at top companies. What Makes This Different: 100+ production-focused scenarios with real architectural trade-offs. Real-world examples from companies shipping agent systems . Stop building chatbots. Start building agents that take action.

Master Generative AI from Theory to ProductionYou don't learn Gen AI from tutorials — you learn from solving real problems. How does ChatGPT handle context and avoid hallucinations? How does Perplexity build RAG at scale? How does GitHub Copilot generate accurate code? System Design Mastery - Generative AI teaches through real-world scenarios and production patterns. 116 scenario-driven case studies covering:✅ RAG with vector databases and hybrid search✅ Prompt engineering with Chain-of-Thought reasoning✅ Document processing with multi-format parsing✅ Multi-modal AI with vision and audio✅ Production deployment with monitoring and cost optimization Every scenario includes: production problem, architectural approaches, Gen AI patterns, decision frameworks, tool implementations, and interview-ready explanations. Learn through case studies from OpenAI, Anthropic, Google, Meta, and top AI-companies. Your journey from developer to Gen AI architect begins here — with scenarios you'll face and tools you can deploy.

Master Data and ML Systems at ScaleYou don't master data platforms from textbooks — you master from solving real problems at petabyte scale.System Design Mastery - Data Analytics and Machine Learning teaches through production scenarios and case studies. 100 scenario-driven case studies covering:✅ Lakehouse architecture with Delta Lake, Iceberg, Hudi✅ Real-time pipelines with Kafka, Spark, Flink✅ Feature stores with Feast for training-serving consistency✅ MLOps platforms with MLflow, SageMaker, Airflow✅ Data quality frameworks with Great Expectations✅ Multi-region data sync and model serving at scale Every scenario includes: production challenge, architectural trade-offs, data/ML patterns, decision frameworks, and interview-ready explanations. Learn through real-world case studies from Netflix, Uber, Airbnb, Spotify's petabyte-scale data and ML architectures. Your journey from data engineer to architect begins here — with scenarios you'll face and systems you can build.

Master System Design from Theory to ProductionYou don't learn system design from textbooks — you learn from solving real problems. How does Netflix handle video streaming at scale? How does Uber route millions of rides? How does Slack deliver messages instantly? System Design Mastery – Foundation Track teaches through real-world scenarios and case studies. 124 scenario-driven case studies covering:✅ Database design, sharding, replication✅ Caching with Redis configuration✅ Microservices with Spring Boot & Kubernetes✅ Message queues with Kafka✅ Load balancing with NGINX✅ Monitoring with Prometheus Every scenario includes: production problem, architectural approaches, design patterns, decision frameworks, tool configurations, and interview-ready explanations. Learn through real-world case studies — from Google, Amazon, Meta, Netflix, and top tech companies. Your journey from developer to designers begins here — with scenarios you'll face and tools you can deploy.

For decades, the heroes of software were those who could write the fastest, cleanest code. They were the masters of syntax, the brilliant ten-percenters who could conjure complex logic out of thin air.But the world has changed. Our systems no longer run on single machines; they are vast, interconnected digital ecosystems that power payments, health care, and communication for billions. The best code snippet in the world is useless if the system that hosts it buckles under a traffic surge, leaks customer data, or costs five times more to run than it generates in revenue.This is a book about the product decisions that shape architecture. It’s about the trade-offs that keep a startup alive in an emerging market and what differentiates a global platform from a local application. It’s for the next generation of leaders who understand that in the modern digital economy, the system is the product. Read it, and start building systems that don’t just execute commands, but think.

In this book, you'll see that the book is designed with one main idea. It aims to give you the skills, confidence and understanding you need to build and deliver real Backend systems. Each chapter is designed to teach you everything you need to know to get hands-on with writing, configuring, deploying and troubleshooting your own projects. Right at the start, we got stuck into designing APIs and building backend systems. We didn't just stick to the basics, though. We went beyond that pretty quickly and started using modern protocols like gRPC and the key contract-first methods that are now the norm for scalable backend systems.