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Full Description
Master autoscaling in Kubernetes using KEDA and Karpenter. Learn to scale workloads efficiently, reduce cloud costs, and optimize performance with real-world strategies for event-driven and infrastructure-level scaling
Key Features
Learn how to autoscale Kubernetes workloads and infrastructure using KEDA and Karpenter
Improve performance, reduce cloud costs, and eliminate resource waste with smarter scaling
Through hands-on labs, real-world use cases, and step-by-step implementation guidance
Book DescriptionKubernetes is the backbone of modern containerized infrastructure—but scaling it efficiently remains a challenge. Kubernetes Autoscaling equips cloud professionals with a comprehensive guide to dynamically scaling applications and infrastructure using the powerful combination of KEDA (Kubernetes Event-Driven Autoscaler) and Karpenter, AWS's next-generation cluster autoscaler.
This hands-on book helps DevOps engineers, SREs, and architects understand and implement practical autoscaling strategies to improve performance, reduce cloud costs, and eliminate over-provisioning. You'll begin with autoscaling fundamentals, explore HPA and VPA, then dive deep into KEDA for event-driven workloads and Karpenter for data plane scaling. Real-world use cases, best practices, and detailed patterns ensure readers can deploy resilient, scalable, and cost-effective Kubernetes clusters across production environments.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 forThis 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 (AWS/GCP/Azure) is assumed.
Contents
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
