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LINUX KERNEL PERFORMANCE ENGINEERING : Understand Scheduling, Memory, I/O, Networking, Filesystems, Interrupts, NUMA, eBPF, Profiling, and Kernel-Level Performance Optimization
Master Linux performance from the kernel up.
LINUX KERNEL PERFORMANCE ENGINEERING is a practical, production-focused guide to understanding, diagnosing, and optimizing Linux systems across CPU scheduling, memory, NUMA, storage, filesystems, networking, interrupts, and kernel observability.
Instead of relying on generic tuning advice, this book teaches an evidence-driven
Measure → Localize → Profile → Trace → Optimize → Validate
You will learn how to investigate scheduler latency, context switching, CPU migrations, memory pressure, page faults, reclaim, MGLRU, DAMON, NUMA locality, page cache behavior, blk-mq, NVMe queueing, TCP performance, SoftIRQ saturation, XDP, AF_XDP, and more.
Hands-on coverage includes perf, ftrace, trace-cmd, eBPF, bpftrace, BCC, bpftool, BTF, libbpf, CO-RE, PSI, fio, iperf3, sysstat, numactl, ethtool, and other essential Linux performance tools.
You will also learn how
Diagnose CPU, memory, storage, filesystem, and network bottlenecksInterpret p95, p99, and tail-latency problemsUse PSI to identify real resource pressureAnalyze on-CPU and off-CPU timeTrace scheduler, lock, I/O, and TCP behaviorInvestigate IRQ and SoftIRQ imbalanceTune cgroup v2 CPU, memory, I/O, and cpuset controlsEvaluate NUMA placement and memory localityBuild repeatable performance benchmarksApply kernel and sysctl changes safelyValidate every optimization with before-and-after evidenceThe final capstone brings everything together in a complete zero-to-production performance engineering project where you diagnose a deliberately degraded Linux server, identify the true kernel-level bottlenecks, apply controlled optimizations, and prove measurable improvements in throughput and tail latency.
Whether you are a Linux administrator, SRE, DevOps engineer, platform engineer, systems engineer, performance engineer, or advanced Linux user, this book gives you a practical framework for turning Linux performance problems into measurable, explainable, and repeatable engineering decisions.
LINUX KERNEL PERFORMANCE ENGINEERING is a practical, production-focused guide to understanding, diagnosing, and optimizing Linux systems across CPU scheduling, memory, NUMA, storage, filesystems, networking, interrupts, and kernel observability.
Instead of relying on generic tuning advice, this book teaches an evidence-driven
Measure → Localize → Profile → Trace → Optimize → Validate
You will learn how to investigate scheduler latency, context switching, CPU migrations, memory pressure, page faults, reclaim, MGLRU, DAMON, NUMA locality, page cache behavior, blk-mq, NVMe queueing, TCP performance, SoftIRQ saturation, XDP, AF_XDP, and more.
Hands-on coverage includes perf, ftrace, trace-cmd, eBPF, bpftrace, BCC, bpftool, BTF, libbpf, CO-RE, PSI, fio, iperf3, sysstat, numactl, ethtool, and other essential Linux performance tools.
You will also learn how
Diagnose CPU, memory, storage, filesystem, and network bottlenecksInterpret p95, p99, and tail-latency problemsUse PSI to identify real resource pressureAnalyze on-CPU and off-CPU timeTrace scheduler, lock, I/O, and TCP behaviorInvestigate IRQ and SoftIRQ imbalanceTune cgroup v2 CPU, memory, I/O, and cpuset controlsEvaluate NUMA placement and memory localityBuild repeatable performance benchmarksApply kernel and sysctl changes safelyValidate every optimization with before-and-after evidenceThe final capstone brings everything together in a complete zero-to-production performance engineering project where you diagnose a deliberately degraded Linux server, identify the true kernel-level bottlenecks, apply controlled optimizations, and prove measurable improvements in throughput and tail latency.
Whether you are a Linux administrator, SRE, DevOps engineer, platform engineer, systems engineer, performance engineer, or advanced Linux user, this book gives you a practical framework for turning Linux performance problems into measurable, explainable, and repeatable engineering decisions.
437 pages, Kindle Edition
Expected publication October 13, 2026
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