8,52 €
8,52 €
inkl. MwSt.
Sofort per Download lieferbar
0 °P sammeln
8,52 €
Als Download kaufen
8,52 €
inkl. MwSt.
Sofort per Download lieferbar
0 °P sammeln
Jetzt verschenken
Alle Infos zum eBook verschenken
8,52 €
inkl. MwSt.
Sofort per Download lieferbar
Alle Infos zum eBook verschenken
0 °P sammeln
Andere Kunden interessierten sich auch für
![Kube-batch Scheduling on Kubernetes (eBook, ePUB)]( "Kube-batch Scheduling on Kubernetes (eBook, ePUB)")
Kube-batch Scheduling on Kubernetes (eBook, ePUB)8,52 €![Effective Multi-Cluster Batch Scheduling with Armada (eBook, ePUB)]( "Effective Multi-Cluster Batch Scheduling with Armada (eBook, ePUB)")
Effective Multi-Cluster Batch Scheduling with Armada (eBook, ePUB)8,46 €![Serverless Cron Scheduling with Render (eBook, ePUB)]( "Serverless Cron Scheduling with Render (eBook, ePUB)")
Serverless Cron Scheduling with Render (eBook, ePUB)8,48 €![Efficient Project Scheduling with GanttProject (eBook, ePUB)]( "Efficient Project Scheduling with GanttProject (eBook, ePUB)")
Efficient Project Scheduling with GanttProject (eBook, ePUB)8,47 €![Virtual Clusters with Kubernetes (eBook, ePUB)]( "Virtual Clusters with Kubernetes (eBook, ePUB)")
Virtual Clusters with Kubernetes (eBook, ePUB)8,43 €![OpenCost for Kubernetes Cost Analysis (eBook, ePUB)]( "OpenCost for Kubernetes Cost Analysis (eBook, ePUB)")
OpenCost for Kubernetes Cost Analysis (eBook, ePUB)8,52 €![Implementing MetalLB for Kubernetes Clusters (eBook, ePUB)]( "Implementing MetalLB for Kubernetes Clusters (eBook, ePUB)")
Implementing MetalLB for Kubernetes Clusters (eBook, ePUB)8,48 €
"Volcano Scheduling on Kubernetes"
"Volcano Scheduling on Kubernetes" offers an in-depth exploration of advanced Kubernetes scheduling paradigms, tailored for engineers and architects managing complex, large-scale workloads. The book begins with a comprehensive overview of native Kubernetes scheduling-detailing core architecture, lifecycle events, constraints, extensibility points, and the inherent limits of default schedulers for handling batch, AI, and high-performance computing (HPC) workloads. Readers gain critical insight into why specialized scheduling solutions are essential for modern multi-tenant and high-throughput environments.
The narrative then delves into the motivation, architecture, and operational model of Volcano, the leading batch scheduler for Kubernetes. Chapters meticulously unpack the components of Volcano-from controllers and custom resource definitions (CRDs) to plugin-driven scheduling pipelines-while contrasting Volcano's gang, queue, and cohort scheduling models with the vanilla Kubernetes approach. Through deployment guides and best practices, readers are equipped with actionable strategies for installing, configuring, and extending Volcano to meet diverse application needs, whether leveraging GPUs, FPGAs, or orchestrating complex multi-stage workflows.
Advanced topics such as gang scheduling, resource fairness, hierarchical multi-queue management, and topology-aware optimizations are explored alongside hands-on scenarios for AI/ML, analytics, and HPC workloads. The book further addresses performance tuning, federated scheduling, secure multi-tenancy, and operational excellence-including observability, failure handling, and compliance. Concluding with discussions on emerging trends, API evolution, and community roadmaps, "Volcano Scheduling on Kubernetes" is an indispensable guide for building robust, scalable, and future-ready Kubernetes-based compute platforms.
"Volcano Scheduling on Kubernetes" offers an in-depth exploration of advanced Kubernetes scheduling paradigms, tailored for engineers and architects managing complex, large-scale workloads. The book begins with a comprehensive overview of native Kubernetes scheduling-detailing core architecture, lifecycle events, constraints, extensibility points, and the inherent limits of default schedulers for handling batch, AI, and high-performance computing (HPC) workloads. Readers gain critical insight into why specialized scheduling solutions are essential for modern multi-tenant and high-throughput environments.
The narrative then delves into the motivation, architecture, and operational model of Volcano, the leading batch scheduler for Kubernetes. Chapters meticulously unpack the components of Volcano-from controllers and custom resource definitions (CRDs) to plugin-driven scheduling pipelines-while contrasting Volcano's gang, queue, and cohort scheduling models with the vanilla Kubernetes approach. Through deployment guides and best practices, readers are equipped with actionable strategies for installing, configuring, and extending Volcano to meet diverse application needs, whether leveraging GPUs, FPGAs, or orchestrating complex multi-stage workflows.
Advanced topics such as gang scheduling, resource fairness, hierarchical multi-queue management, and topology-aware optimizations are explored alongside hands-on scenarios for AI/ML, analytics, and HPC workloads. The book further addresses performance tuning, federated scheduling, secure multi-tenancy, and operational excellence-including observability, failure handling, and compliance. Concluding with discussions on emerging trends, API evolution, and community roadmaps, "Volcano Scheduling on Kubernetes" is an indispensable guide for building robust, scalable, and future-ready Kubernetes-based compute platforms.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.