9798270994747 - kubernetes scheduling: the complete guide: master pod scheduling, resource allocation, and custom schedulers. node affinity, taints, topology awareness, and gpu scheduling for modern workloads di draycott, sofia (4 risultati)
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 32,82
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 29,81
EUR 5,85 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 32,81
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Master Kubernetes pod placement with clear, proven practices that deliver predictable performance in real clusters.Scheduling decisions shape reliability, cost, and latency. Many teams struggle with vague rules, uneven spreading, storage surprises, or GPU contention that shows up only under… load.This guide turns the scheduler into a tool you can reason about. It explains how requests, policies, and plugins interact, then gives you repeatable labs and copy-ready manifests so you can apply the lessons in production.understand kube scheduler flow, queueing, filtering, scoring, bindingshape outcomes with profiles, extension points, and plugin weightsset requests and limits that align with qos and stable eviction behaviorsize node allocatable and pod overhead for realistic densityuse node labels, node affinity, and inter pod rules without deadlocksapply taints and tolerations for pool isolation and safe admissionspread with podtopologyspread, maxskew, and default policiesdesign pdbs, priorities, and preemption paths that prevent starvationrun storage aware scheduling with waitforfirstconsumer and csi capacityschedule gpus with device plugins, nvidia operator, mig, and time slicingadopt dra with resourceclass and resourceclaims for accelerator controltune numa policies, cpu manager, memory manager, and topology manageroperate multiple schedulers, avoid risky extenders, add safe pluginsuse the descheduler with budgets and limits to fix drift safelymonitor the metrics that matter and build practical dashboardstroubleshoot incidents like ip exhaustion, pvc flapping, and skew driftrun field labs, kube burner load tests, simulator traces, gpu labs, and gatesThis is a code heavy guide with working yaml, bash, go, and json snippets that you can use to stand up labs, tune policies, and ship changes with confidence.Grab your copy today and make Kubernetes scheduling an advantage for your team. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 33,62
EUR 43,15 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Master Kubernetes pod placement with clear, proven practices that deliver predictable performance in real clusters.Scheduling decisions shape reliability, cost, and latency. Many teams struggle with vague rules, uneven spreading, storage surprises, or GPU contention that shows up only under… load.This guide turns the scheduler into a tool you can reason about. It explains how requests, policies, and plugins interact, then gives you repeatable labs and copy-ready manifests so you can apply the lessons in production.understand kube scheduler flow, queueing, filtering, scoring, bindingshape outcomes with profiles, extension points, and plugin weightsset requests and limits that align with qos and stable eviction behaviorsize node allocatable and pod overhead for realistic densityuse node labels, node affinity, and inter pod rules without deadlocksapply taints and tolerations for pool isolation and safe admissionspread with podtopologyspread, maxskew, and default policiesdesign pdbs, priorities, and preemption paths that prevent starvationrun storage aware scheduling with waitforfirstconsumer and csi capacityschedule gpus with device plugins, nvidia operator, mig, and time slicingadopt dra with resourceclass and resourceclaims for accelerator controltune numa policies, cpu manager, memory manager, and topology manageroperate multiple schedulers, avoid risky extenders, add safe pluginsuse the descheduler with budgets and limits to fix drift safelymonitor the metrics that matter and build practical dashboardstroubleshoot incidents like ip exhaustion, pvc flapping, and skew driftrun field labs, kube burner load tests, simulator traces, gpu labs, and gatesThis is a code heavy guide with working yaml, bash, go, and json snippets that you can use to stand up labs, tune policies, and ship changes with confidence.Grab your copy today and make Kubernetes scheduling an advantage for your team. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
