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

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

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Bol

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

Amazon

Pagina's: 420, Paperback, Packt Publishing


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Merk Packt Publishing
EAN
  • 9781836643838
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