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Mastering Kong API Gateway

From Core Architecture to AI-Powered LLM Orchestration

Mastering Kong API Gateway
This book is 100% completeLast updated on 2026-07-20

Master Kong API Gateway with a practical guide that takes you from core architecture to advanced AI-powered API management. Learn to build secure, scalable platforms with production-ready examples, explore Kubernetes, decK and Terraform workflows, and discover how Kong AI Gateway enables intelligent LLM routing, semantic caching, guardrails and cost optimization across modern AI applications.

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About

About

About the Book

This book is your complete reference for mastering Kong API Gateway from the ground up. Whether you are deploying your first route, architecting a multi-region platform, or orchestrating traffic across dozens of LLM providers, this guide provides production-ready patterns, real configurations, and deep architectural understanding. You will learn how Kong works internally on OpenResty, how to deploy it in every supported mode, how to secure APIs at scale, how to run Kong as a Kubernetes ingress controller, and how to harness the AI Gateway for intelligent LLM routing, semantic caching, guardrails, and cost optimization. Every chapter delivers working examples in Docker, Kubernetes YAML, Helm charts, decK declarations, Terraform, and application code across Spring Boot, Node.js, Python, Go, .NET, gRPC, GraphQL, Kafka, LangChain, and LlamaIndex.

Author

About the Author

Steve Publications

Steve is a technology professional with over 20 years of experience in software development, server infrastructure, cybersecurity, vulnerability research and reverse engineering. He specializes in analyzing complex systems, identifying weaknesses and improving security.

Beyond his professional work, Steve collaborates with researchers and industry experts to create practical technical books covering software development, cybersecurity, cloud computing, DevOps, AI and enterprise technologies. His goal is to help IT professionals, students and enthusiasts develop practical skills through clear explanations, real-world examples and hands-on exercises.

At Steve Publications, we use AI to assist with translation, proofreading and editing but not to replace the research, technical expertise or hands-on experience behind our books. Some authors publish under pseudonyms for privacy or professional reasons.

Every book is written, reviewed and maintained by experienced professionals, supported by a private community of over 420 engineers and researchers. We prioritize technical accuracy, practical value and regularly updated content over mass-produced AI-generated text.

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Contents

Table of Contents

From Core Architecture to AI-Powered LLM Orchestration

Preface

  1. Who Should Read This Book
  2. How This Book Is Organized
  3. What Is Not in This Book
  4. Conventions Used in This Book
  5. OSS versus Enterprise Features
  6. Software Versions
  7. Feedback and Corrections

Introduction: Why Kong Matters

Chapter 1: Architecture and Core Concepts

  1. OpenResty and the Nginx + Lua Foundation
  2. The Kong Request Lifecycle
  3. Services, Routes, Upstreams, and Consumers
  4. Configuration Models: Database-Backed, DB-less, Hybrid
  5. The Plugin System Architecture

Chapter 2: Installation and Deployment

  1. Prerequisites and Environment Setup
  2. Docker and Docker Compose Deployments
  3. Database-Backed Mode with PostgreSQL
  4. DB-less Mode with YAML Configuration
  5. Hybrid Mode: Control Plane and Data Plane
  6. Kong Konnect Cloud Deployment
  7. Choosing Your Deployment Model
  8. Kong Manager: The Web UI for Kong Administration

Chapter 3: Routing, Services, and Traffic Management

  1. Defining Services and Routes
  2. Route Matching Strategies
  3. Upstreams and Load Balancing Algorithms
  4. Health Checks: Active and Passive
  5. Service Discovery Integration
  6. API Versioning Strategies

Chapter 4: Authentication and Authorization

  1. API Keys and Basic Authentication
  2. HMAC Authentication
  3. JWT Validation and Issuance
  4. OAuth 2.0 and OIDC Flows
  5. OpenID Connect with Keycloak
  6. LDAP and Active Directory Integration
  7. Access Control Lists (ACL)
  8. Custom Authentication with Lua Plugins

Chapter 5: Rate Limiting, Throttling, and Traffic Shaping

  1. Rate Limiting Algorithms: Local, Redis, Cluster, Sentinel
  2. Per-Consumer and Per-Route Limits
  3. Burst Handling and Token Bucket
  4. Load Shedding Strategies
  5. Rate Limit Response Headers

Chapter 6: Plugins Ecosystem

  1. Plugin Phases and the Request Lifecycle
  2. Built-in Plugins Overview
  3. Configuring and Chaining Plugins
  4. Plugin Priority and Execution Order
  5. Writing Custom Lua Plugins
  6. Third-Party Plugins from Kong Hub

Chapter 7: Security, TLS, and API Governance

  1. Mutual TLS (mTLS) Configuration
  2. Certificate Management and Auto-Renewal
  3. IP Restriction and Geo-Blocking
  4. Bot Detection and Abuse Prevention
  5. Request/Response Body Filtering
  6. CORS, CSRF, and Cross-Origin Security
  7. Vulnerability Scanning Integration

Chapter 8: Observability, Logging, Monitoring, and Analytics

  1. Access Logs and Structured Logging
  2. Prometheus Metrics and Grafana Dashboards
  3. Distributed Tracing with OpenTelemetry
  4. Log Streaming to ELK, Splunk, Datadog
  5. Kong Analytics and Konnect Insights
  6. Custom Metrics with Plugins

Chapter 9: Kubernetes Integration

  1. Kong Ingress Controller Architecture
  2. Helm Chart Installation and Configuration
  3. Ingress Resources and Annotations
  4. Kong Gateway API Implementation
  5. Plugin Configuration via Custom Resources
  6. Multi-Cluster and Edge Deployment Patterns

Chapter 10: Automation, CI/CD, and GitOps

  1. The Admin API Reference
  2. decK Configuration Management
  3. Declarative Config and Version Control
  4. Terraform Provider for Kong
  5. CI/CD Pipeline Patterns

Chapter 11: Performance Tuning, Scalability, and High Availability

  1. OpenResty and Nginx Tuning Parameters
  2. Connection Pooling and Keep-Alive Optimization
  3. Horizontal Scaling Strategies
  4. High Availability Architecture

Chapter 12: Kong AI Gateway and LLM Orchestration

  1. The AI Gateway Problem
  2. Getting Started with AI Gateway
  3. Intelligent Model Routing Strategies (Enterprise)
  4. Multi-Provider Orchestration
  5. Fallback and Retry Mechanisms
  6. Prompt Transformation and Template Management
  7. Response Caching for AI Workloads (Enterprise)
  8. Guardrails, Safety, and Content Moderation
  9. Token Tracking and Cost Optimization
  10. AI Observability and Governance

Chapter 13: AI Integrations and Framework Patterns

  1. OpenAI and Azure OpenAI Integration
  2. Anthropic Claude Integration
  3. Google Gemini Integration
  4. AWS Bedrock Model Access
  5. Self-Hosted Models: Ollama, vLLM, Hugging Face
  6. LangChain Orchestration with Kong
  7. LlamaIndex and RAG Patterns
  8. Streaming Responses and SSE

Chapter 14: Production Patterns, Migrations, and Troubleshooting

  1. Application Integration Patterns
  2. gRPC and GraphQL Gateway Patterns
  3. Kafka Event Streaming with Kong
  4. Common Failure Modes and Troubleshooting
  5. Upgrade Strategies and Version Migration
  6. Real-World Migration Case Study: From Nginx Ingress to Kong
  7. Configuration Auditing and Compliance
  8. Production Checklist

Conclusion: The Future of API Infrastructure

  1. Key Takeaways
  2. Emerging Trends in API Architecture
  3. Where Kong Is Heading
  4. Final Recommendations

References

  1. Core Kong Documentation
  2. Kong Manager and RBAC
  3. AI Gateway and AI Plugins
  4. Installation and Deployment
  5. Kubernetes Integration
  6. Automation and Configuration Management
  7. Observability and Monitoring
  8. Underlying Technologies
  9. Community and Support

Index

  1. A
  2. B
  3. C
  4. D
  5. E
  6. F
  7. G
  8. H
  9. I
  10. K
  11. L
  12. M
  13. N
  14. O
  15. P
  16. R
  17. S
  18. T
  19. U
  20. V
  21. W

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