Kubernetes Autoscaling Build efficient, cost-optimized clusters with KEDA and Karpenter

[book24h]

Free Download Kubernetes Autoscaling: Build efficient, cost-optimized clusters with KEDA and Karpenter
English | 2025 | ISBN: 1836643837 | 421 pages | True PDF,EPUB | 22.94 MB
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
  

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.

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