Tanaka Caleb (57 results)

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Paperback. Condition: new. Paperback. Build a secure Rancher and RKE2 platform that can actually run enterprise Kubernetes at scale.Once Kubernetes spreads beyond a single cluster, keeping dozens of environments consistent, secure and affordable becomes the real problem. Manual YAML, ad hoc upgrades and one off scripts do not survive growth.This book shows platform engineers and SREs how to turn SUSE Rancher, RKE2 and K3s into a managed platform that standardizes clusters across regions, clouds and teams while staying aligned with security and compliance requirements.Design a hardened RKE2 based management cluster and Rancher architecture that fits your scale and risk profileInstall Rancher on RKE2 with TLS, identity integration and feature flags that reflect enterprise security standardsProvision and operate RKE2, RKE, K3s and managed services such as EKS, AKS and GKE from a single management planeApply CIS benchmarks to RKE2 and K3s, including node level hardening, SELinux, FIPS and repeatable self assessmentsUse Terraform, Fleet and GitOps to define cluster baselines, shared services and application rollouts across many clustersBuild observability with Rancher Monitoring, Prometheus, Grafana, SLO based alerting and centralized logging with LokiSecure workloads with NeuVector, from registry scanning and runtime protection to multi cluster security federationPlan and test backup, restore and disaster recovery for Rancher, management clusters and downstream workloadsRun day 2 operations with health checks, safe upgrades, incident response and migration paths from RKE to RKE2Adopt practical multi cloud, edge and retail reference architectures with clear patterns, anti patterns and checklistsThe book includes production runbooks and practical checklists for common Rancher and RKE2 scenarios so teams can standardize the way they respond to incidents and platform changes.Throughout the chapters you will work with real shell commands, YAML manifests, RKE2 and Rancher configurations and Terraform snippets that you can adapt directly into your own platform code.If you are responsible for a growing Kubernetes estate and want a repeatable platform instead of one off clusters, add this book to your toolkit today. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condition: new. Paperback. Build a faster development workstation on Gentoo with precise control over Portage, compiler flags, and custom toolchains.Generic Linux setups hide how software is built, which slows compile and link cycles, bloats dependencies, and makes debugging harder. Developers need a workstation that is predictable under load, tuned for their CPU, and flexible across language stacks.This book shows how to plan, install, and maintain a Gentoo system that fits professional workflows. You will compile from source with intent, shape Portage policy for stability and speed, and apply data driven optimizations that shorten iteration time without sacrificing reliability.Plan a developer focused Gentoo layout, choose filesystems, and set tmpfs or disk strategies that accelerate buildsConfigure Portage cleanly with makeconf packageuse packageenv and per package environments for lto thinlto mold lld debug and sanitizersUse USE flags with discipline to reduce dependency sprawl while enabling exactly the features your projects requireTune compiler and linker flags including march mtune optimization levels frame pointers visibility and section based dead code removalApply link time and profile guided optimization and verify gains with repeatable benchmarks and perf based profilingSpeed up compilation with ccache distcc parallel jobs and load controls that keep the desktop responsiveBuild and switch multiple GCC Clang and LLVM versions and manage Rust Go Python and CC++ toolchains side by sideCreate cross compilation toolchains and consistent sysroots for embedded and multi architecture targetsConfigure kernels for development tasks enable debugging options and manage multiple kernels safelySet up editors IDEs version control build systems CICD hooks and container workflows with Docker and PodmanUse overlays effectively track cutting edge tools without destabilizing the base and package local or internal softwareMaintain with a clear weekly update routine handle conflicts quickly rebuild preserved dependencies and keep binary packages for rollbackBack up configuration and artifacts with snapshots binary packages and offsite archives and recover confidently with a chrootContribute fixes upstream and improve docs so future updates are smoother for you and your teamThis is a code heavy guide with working Bash Python C CMake Rust TOML Dockerfile and configuration snippets that you can copy into real projects and adapt with minimal changes.Grab your copy today. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condition: new. Paperback. Master Kubernetes scheduler internals and build custom scheduling solutions that optimize resource utilization, reduce costs, and meet complex workload requirements at scale.The default Kubernetes scheduler works well for basic workloads, but production clusters running AI, batch processing, or latency-sensitive applications need more. You need topology-aware placement, dynamic GPU allocation, load-based bin packing, and custom scheduling logic that matches your infrastructure reality. This book gives you the deep architectural knowledge and practical code to extend the scheduler, write plugins, and deploy production-grade scheduling strategies.Written for platform engineers, SREs, and architects managing large Kubernetes clusters, this guide takes you inside the scheduler's control plane flow, from the scheduling cycle through binding. You'll understand extension points, build custom plugins with proper state management, configure multiple scheduler profiles for different workload classes, and implement topology-aware placement that respects NUMA boundaries, storage locality, and zone distribution.What You'll Learn: Scheduler architecture internals: control plane flow, scheduling and binding cycles, queues, cache behavior, requeue hints, and how unschedulable pods move through the systemWriting scheduler plugins: minimal plugin skeleton, registration, plugin arguments, using CycleState to share data across phases with cost control, testing with fake client, and profiling with pprofKubeSchedulerConfiguration v1 with safe defaults, multiple profiles with schedulerName, zero-downtime migration, and performance tuning including percentageOfNodesToScore and API QPS limitsBuilt-in plugin behavior: NodeResourcesFit and RequestedToCapacityRatio shapes, affinity and anti-affinity defaults, topology spread constraints, and load-aware scoring with Trimaran TargetLoadPackingDynamic Resource Allocation end to end: DRA objects (DeviceClass, ResourceClaim, ResourceSlice), scheduler integration, GPU examples with NVIDIA DRA driver, and migration from device plugins with quotasNode resource managers and topology: CPU Manager, Memory Manager, PSI, Memory QoS tuning, Topology Manager policies for single NUMA alignment, SMT pitfalls, and Node Resource Topology plugin with RTE or NFDTopology-aware placement: pod topology spread constraints with cluster defaults, batch and AI scheduling with Kueue, and colocation with Koordinator for interference control and NUMA hintsStorage-aware scheduling: WaitForFirstConsumer mode, PV NodeAffinity, CSI storage capacity tracking with scheduler hints, and StatefulSets with zone-aware placement for disaster readinessScheduler observability: throughput and latency SLOs, key metrics and alert rules, load generation with ClusterLoader2 and kube-burner for repeatable performance labsProduction operations: priority and preemption, fairness, quotas, batch queues, Descheduler strategies for safe rebalancing with PDBs, and managed Kubernetes caveats for EKS, GKE, and AKSThe book includes working code illustrations for plugin development, configuration examples, and performance tuning playbooks. You'll see complete plugin implementations, multi-profile configurations, DRA integration code, and observability setups ready for your cluster.Take control of Kubernetes scheduling today and optimize your cluster for the workloads that matter most. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.