systems_performance_2nd_edition_by_brendan_gregg

Systems Performance, 2nd Edition, by Brendan Gregg

Book Summary

Systems Performance, Second Edition, covers Performance concepts, performance strategy, performance tools, and performance tuning for operating systems performance and application performance, using Linux-based operating systems as the primary example. A deep understanding of these tools and [[performance techniques is critical for developers today. Implementing the performance strategies described in this thoroughly revised and updated edition can lead to a better end-user performance experience and lower costs, especially for cloud computing environments that charge by the OS instance.

Systems performance expert and best-selling author Brendan Gregg summarizes relevant operating system performance, hardware performance, and application performance theory to quickly get professionals up to speed even if they've never analyzed performance before. Gregg then provides in-depth explanations of the latest tools and techniques, including extended BPF, and shows how to get the most out of cloud performance, web performance, and large-scale enterprise systems performance. Key topics covered include:

Featuring up-to-date coverage of Linux operating systems performance and Linux environments, Systems Performance, Second Edition, also addresses performance issues that apply to any computer system. The book will be a go-to performance reference for many years to come and, like the first edition, required reading at leading tech companies.

About the Author

Brendan Gregg is an industry expert in computing performance and cloud computing. He is a senior performance architect at Netflix, where he does performance design, performance evaluation, performance analysis, and performance tuning. The author of multiple technical books including BPF Performance Tools and Systems Performance, he received the USENIX LISA Award for Outstanding Achievement in System Administration. He has also been a kernel engineer, performance lead, and professional technical trainer, and was program co-chair for the USENIX LISA 2018 conference. He has created performance tools included in multiple operating systems, and visualizations and methodologies for performance analysis, including flame graphs.

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Performance: Systems performance, Systems performance bibliography, Systems Performance Outline: (Systems Performance Introduction, Systems Performance Methodologies, Systems Performance Operating Systems, Systems Performance Observability Tools, Systems Performance Applications, Systems Performance CPUs, Systems Performance Memory, Systems Performance File Systems, Systems Performance Disks, Systems Performance Network, Systems Performance Cloud Computing, Systems Performance Benchmarking, Systems Performance perf, Systems Performance Ftrace, Systems Performance BPF, Systems Performance Case Study), Accuracy, Algorithmic efficiency (Big O notation), Algorithm performance, Amdahl's Law, Android performance, Application performance engineering, Async programming, Bandwidth, Bandwidth utilization, bcc, Benchmark (SPECint and SPECfp), BPF, bpftrace, Performance bottleneck (“Hotspots”), Browser performance, C performance, C++ performance, C# performance, Cache hit, Cache performance, Capacity planning, Channel capacity, Clock rate, Clojure performance, Compiler performance (Just-in-time (JIT) compilation - Ahead-of-time compilation (AOT), Compile-time, Optimizing compiler), Compression ratio, Computer performance, Concurrency, Concurrent programming, Concurrent testing, Container performance, CPU cache, CPU cooling, CPU cycle, CPU overclocking (CPU boosting, CPU multiplier), CPU performance, CPU speed, CPU throttling (Dynamic frequency scaling - Dynamic voltage scaling - Automatic underclocking), CPU time, CPU load - CPU usage - CPU utilization, Cycles per second (Hz), CUDA (Nvidia), Data transmission time, Database performance (ACID-CAP theorem, Database sharding, Cassandra performance, Kafka performance, IBM Db2 performance, MongoDB performance, MySQL performance, Oracle Database performance, PostgreSQL performance, Spark performance, SQL Server performance), Disk I/O, Disk latency, Disk performance, Disk speed, Disk usage - Disk utilization, Distributed computing performance (Fallacies of distributed computing), DNS performance, Efficiency - Relative efficiency, Encryption performance, Energy efficiency, Environmental impact, Fast, Filesystem performance, Fortran performance, FPGA, Gbps, Global Interpreter Lock - GIL, Golang performance, GPU - GPGPU, GPU performance, Hardware performance, Hardware performance testing, Hardware stress test, Haskell performance, High availability (HA), Hit ratio, IOPS - I/O operations per second, IPC - Instructions per cycle, IPS - Instructions per second, Java performance (Java data structure performance - Java ArrayList is ALWAYS faster than LinkedList, Apache JMeter), JavaScript performance (V8 JavaScript engine performance, Node.js performance - Deno performance), JVM performance (GraalVM, HotSpot), Kubernetes performance, Kotlin performance, Lag (video games) (Frame rate - Frames per second (FPS)), Lagometer, Latency, Lazy evaluation, Linux performance, Load balancing, Load testing, Logging, macOS performance, Mainframe performance, Mbps, Memory footprint, Memory speed, Memory performance, Memory usage - Memory utilization, Micro-benchmark, Microsecond, Monitoring

Linux/UNIX commands for assessing system performance include:

  • uptime the system reliability and load average
  • top for an overall system view
  • vmstat vmstat reports information about runnable or blocked processes, memory, paging, block I/O, traps, and CPU.
  • htop interactive process viewer
  • dstat, atop helps correlate all existing resource data for processes, memory, paging, block I/O, traps, and CPU activity.
  • iftop interactive network traffic viewer per interface
  • nethogs interactive network traffic viewer per process
  • iotop interactive I/O viewer
  • iostat for storage I/O statistics
  • netstat for network statistics
  • mpstat for CPU statistics
  • tload load average graph for terminal
  • xload load average graph for X
  • /proc/loadavg text file containing load average

(Event monitoring - Event log analysis, Google Cloud's operations suite (formerly Stackdriver), htop, mpstat, macOS Activity Monitor, Nagios Core, Network monitoring, netstat-iproute2, proc filesystem (procfs)]] - ps (Unix), System monitor, sar (Unix) - systat (BSD), top - top (table of processes), vmstat), Moore’s law, Multicore - Multi-core processor, Multiprocessor, Multithreading, mutex, Network capacity, Network congestion, Network I/O, Network latency (Network delay, End-to-end delay, packet loss, ping - ping (networking utility) (Packet InterNet Groper) - traceroute - netsniff-ng, Round-trip delay (RTD) - Round-trip time (RTT)), Network performance, Network switch performance, Network usage - Network utilization, NIC performance, NVMe, NVMe performance, Observability, Operating system performance, Optimization (Donald Knuth: “Premature optimization is the root of all evil), Parallel processing, Parallel programming (Embarrassingly parallel), Perceived performance, Performance analysis (Profiling), Performance design, Performance engineer, Performance equation, Performance evaluation, Performance gains, Performance Mantras, Performance measurement (Quantifying performance, Performance metrics), Perfmon, Performance testing, Performance tuning, PowerShell performance, Power consumption - Performance per watt, Processing power, Processing speed, Productivity, Python performance (CPython performance, PyPy performance - PyPy JIT), Quality of service (QOS) performance, Refactoring, Reliability, Response time, Resource usage - Resource utilization, Router performance (Processing delay - Queuing delay), Ruby performance, Rust performance, Scala performance, Scalability, Scalability test, Server performance, Size and weight, Slow, Software performance, Software performance testing, Speed, Stress testing, SSD, SSD performance, Swift performance, Supercomputing, Tbps, Throughput, Time (Time units, Nanosecond, Millisecond, Frequency (rate), Startup time delay - Warm-up time, Execution time), TPU - Tensor processing unit, Tracing, Transistor count, TypeScript performance, Virtual memory performance (Thrashing), Volume testing, WebAssembly, Web framework performance, Web performance, Windows performance (Windows Performance Monitor). (navbar_performance)


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systems_performance_2nd_edition_by_brendan_gregg.txt · Last modified: 2024/04/28 03:36 (external edit)