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Apache APISIX: From API Gateway to AI Gateway

This book is 100% completeLast updated on 2026-07-20

Apache APISIX is redefining what an API gateway can do in the age of AI. This hands-on guide takes you from the fundamentals to production-ready deployments, showing you how to build secure, scalable, and intelligent gateways for APIs, microservices and AI applications. With practical examples, you will gain the skills to confidently deploy, manage and optimize modern API infrastructure.

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About

About

About the Book

Apache APISIX has evolved from a high-performance API gateway into a comprehensive platform for managing APIs, microservices, and AI workloads at scale. This book takes you from zero knowledge to production mastery, covering architecture, routing, security, observability, Kubernetes integration, and the powerful new AI Gateway capabilities for multi-LLM orchestration. Every chapter includes runnable, production-ready examples in YAML, JSON, Docker, Kubernetes, Python, Go, Java, and TypeScript. Whether you are a developer building your first route, a platform engineer designing a multi-cluster gateway, or an AI engineer routing traffic across dozens of models, this book gives you the depth and practical guidance to do it right.

Author

About the Author

Steve Publications

Steve is a technology professional with more than 20 years of experience in software development, server infrastructure, cybersecurity, vulnerability research and reverse engineering. Throughout his career, he has designed, secured, analyzed and tested complex software and infrastructure, with a particular focus on understanding how systems fail and how they can be made more secure.

Outside of work, Steve enjoys sharing knowledge with the technology community. He collaborates with researchers, industry experts and technology professionals to write practical books covering software development, cybersecurity, cloud computing, networking, DevOps, artificial intelligence and enterprise technologies. His books focus on practical learning through clear explanations, real-world examples and hands-on exercises. With more than two decades of industry experience, his goal is to help IT professionals, students and technology enthusiasts build useful skills and stay current in a rapidly changing industry.

We believe readers deserve to know how our books are created. Most of our authors are not native English speakers, so we use AI to help translate, proofread manuscripts, fix grammar, improve sentence structure and make technical explanations easier to read. AI is used as an editing tool only. It does not replace the research, technical knowledge or hands-on experience behind our books. Some of our authors also prefer to remain anonymous for privacy or professional reasons. In those cases, we publish their work under a different name. The author's name may be different, but the quality of the content and our review process remain the same.

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Contents

Table of Contents

The Complete Guide to Building Scalable API Gateways and AI Infrastructure

Introduction

  1. Why This Book Exists
  2. What You Will Learn
  3. How This Book Is Structured
  4. A Note on Versions and Accuracy

Chapter 1: What Is Apache APISIX and Why It Matters

  1. The API Gateway Problem: Why You Need One
  2. Enter Apache APISIX: A Modern Approach
  3. Core Design Principles That Set It Apart
  4. How APISIX Compares to Other API Gateways
  5. Where APISIX Fits in Your Architecture
  6. How This Book Is Organized

Chapter 2: Architecture Deep Dive

  1. The Nginx Foundation: Lua and OpenResty
  2. Control Plane vs Data Plane Separation
  3. Configuration Storage and Dynamic Updates
  4. The Request Processing Pipeline
  5. Plugin Execution Model and Phases

Chapter 3: Installation and Getting Started

  1. Docker and Docker Compose Setup
  2. Helm Chart Deployment on Kubernetes
  3. Source Build and Binary Installation
  4. Verifying Your Installation and Health Checks
  5. Initial Configuration and Admin API Access

Chapter 4: Core Concepts: Routes, Upstreams, Services, and Consumers

  1. Routes: Matching and Directing Traffic
  2. Upstreams: Defining Your Backend Servers
  3. Services: Abstracting Route and Upstream Relationships
  4. Consumers: Identity and Access Management
  5. Putting It Together: A Complete API Flow
  6. Client Code Examples: Calling APISIX-Protected APIs

Chapter 5: Routing, Load Balancing, and Traffic Management

  1. Advanced Route Matching and Priority
  2. Load Balancing Algorithms: Round Robin, Least Connections, and More
  3. Weighted Routing and Traffic Splitting
  4. Canary Deployments and Progressive Delivery
  5. Fault Injection and Chaos Testing with APISIX

Chapter 6: Authentication, Authorization, and Security

  1. Authentication Plugins: Keys, JWT, OAuth2, mTLS, and More
  2. Authorization and Access Control Patterns
  3. Rate Limiting and Quotas: Protecting Your Backends
  4. Web Application Firewall and Request Validation
  5. TLS Termination, mTLS, and Certificate Management

Chapter 7: The Plugin Ecosystem: Extending APISIX

  1. How Plugins Work: Phases, Hooks, and Execution Order
  2. Built-in Plugins: A Curated Guide to the Essentials
  3. Third-Party and Community Plugins
  4. Writing Custom Lua Plugins
  5. Plugin Performance Considerations and Best Practices

Chapter 8: Observability, Logging, and Monitoring

  1. Access Logs, Error Logs, and Structured Logging
  2. Prometheus Metrics and Export Configuration
  3. Distributed Tracing with Jaeger, Zipkin, and OpenTelemetry
  4. Grafana Dashboards and Alerting Setup
  5. AI Observability: Tracking Token Usage, Latency, and Costs

Chapter 9: Kubernetes Integration and Ingress Controller

  1. Deploying APISIX with Helm on Kubernetes
  2. The APISIX Ingress Controller: Architecture and Setup
  3. Custom Resources: ApisixRoute, ApisixUpstream, and More
  4. Managing TLS, Secrets, and ConfigMaps
  5. Multi-Tenancy and Namespace Isolation

Chapter 10: Apache APISIX AI Gateway: LLM Routing Fundamentals

  1. Why You Need an AI Gateway for LLM Traffic
  2. The APISIX AI Gateway Architecture
  3. OpenAI-Compatible Protocol and Provider Abstraction
  4. Multi-LLM Routing: Sending Requests to Different Models
  5. Provider Failover and High Availability for AI Workloads

Chapter 11: Advanced AI Gateway Patterns and Optimization

  1. Cost-Aware and Latency-Aware Intelligent Routing
  2. Load Balancing Across LLM Providers and Models
  3. Prompt and Response Transformation Pipelines
  4. Streaming Responses and SSE Support
  5. Token Usage Tracking, Budgeting, and Cost Attribution
  6. AI Caching Strategies: Exact Match and Semantic Cache
  7. Guardrails, Content Filtering, and Safety Plugins

Chapter 12: Performance, Scalability, and High Availability

  1. Performance Benchmarks and Capacity Planning
  2. Tuning Nginx and Lua for Maximum Throughput
  3. Horizontal Scaling and Cluster Topology
  4. High Availability Patterns and Failover Strategies
  5. Disaster Recovery and Backup Procedures
  6. Capstone Project: End-to-End AI-Powered Microservice Platform on Kubernetes

Chapter 13: Production Operations: Testing, CI/CD, Troubleshooting, and Best Practices

  1. Testing Strategies: Unit, Integration, and E2E Tests for APISIX Configs
  2. CI/CD Pipelines for API Gateway Configuration
  3. Common Pitfalls and Anti-Patterns to Avoid
  4. Troubleshooting Guide: Diagnosing Real Production Issues
  5. Security Hardening Checklist and Compliance Considerations
  6. Real-World Deployment Case Studies

Conclusion: The Future of API and AI Gateways

  1. The Convergence of API and AI Gateways
  2. Trends to Watch
  3. What You Should Take Away
  4. Final Thoughts

References

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