Kubernetes Autoscaling: Build efficient, cost-optimized clusters with KEDA and Karpenter
暫譯: Kubernetes 自動擴展：使用 KEDA 和 Karpenter 建立高效且成本優化的叢集

Learn to scale workloads efficiently, reduce cloud costs, and optimize performance with real-world strategies for event-driven and infrastructure-level scaling

Key Features:

- Autoscale Kubernetes workloads and infrastructure using KEDA and Karpenter

- Improve performance, reduce cloud costs, and eliminate resource waste with smarter scaling

- Work with hands-on labs, real-world use cases, and step-by-step guidance from the creator of Karpenter Blueprints

- Free with your book: PDF Copy, AI Assistant, and Next-Gen Reader

Book Description:

Kubernetes is the backbone of modern containerized infrastructure, but scaling it efficiently remains a challenge. Kubernetes Autoscaling equips cloud professionals with this comprehensive guide to dynamically scaling applications and infrastructure using the powerful combination of Kubernetes Event-Driven Autoscaler (KEDA) and Karpenter, AWS's next-generation cluster autoscaler.

You'll begin with autoscaling fundamentals, move through HPA and VPA, and then get hands-on KEDA for event-driven workloads and Karpenter for data plane scaling. With the help of real-world use cases, best practices, and detailed patterns, you'll deploy resilient, scalable, and cost-effective Kubernetes clusters across production environments.

By the end of this book, you'll be able to implement practical autoscaling strategies to improve performance, reduce cloud costs, and eliminate over-provisioning.

What You Will Learn:

- Gain a solid foundation in Kubernetes autoscaling and its components

- Scale deployments, jobs, and StatefulSets using KEDA's CRDs

- Configure event-based scaling strategies using metrics and schedules

- Deploy and manage Karpenter for on-demand infrastructure provisioning

- Explore advanced node disruption and lifecycle techniques

- Combine KEDA and Karpenter to implement full-stack autoscaling

- Optimize costs using Spot Instances, scale-to-zero, and workload placement

- Apply real-world patterns and monitor autoscaling performance in production

Who this book is for:

This book is ideal for DevOps engineers, SREs, cloud architects, and Kubernetes professionals who want to optimize resource usage and improve scalability. A basic understanding of Kubernetes concepts and cloud environments, i.e., AWS, GCP, and Azure, is assumed.

Table of Contents

- Introduction to Kubernetes Autoscaling

- Workload Autoscaling Overview

- Workload Autoscaling with HPA and VPA

- Kubernetes Event-Driven Autoscaling (KEDA)

- KEDA in Action on AWS EKS

- Metrics, Monitoring, and Observability

- Data Plane Autoscaling Overview

- Getting Started with Karpenter

- Karpenter on AWS

- Karpenter Management Operations

- Practical Use Cases

- Patterns and Best Practices