Systems Performance: Enterprise and the Cloud [NOOK Book]

Overview

The Complete Guide to Optimizing Systems Performance

 

Written by the winner of the 2013 LISA Award for Outstanding Achievement in System Administration


Large-scale enterprise, cloud, and virtualized computing systems have introduced serious performance challenges. Now, internationally renowned performance expert Brendan Gregg has brought together proven methodologies, tools, and metrics for analyzing and tuning even the most ...

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Systems Performance: Enterprise and the Cloud

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Overview

The Complete Guide to Optimizing Systems Performance

 

Written by the winner of the 2013 LISA Award for Outstanding Achievement in System Administration


Large-scale enterprise, cloud, and virtualized computing systems have introduced serious performance challenges. Now, internationally renowned performance expert Brendan Gregg has brought together proven methodologies, tools, and metrics for analyzing and tuning even the most complex environments. Systems Performance: Enterprise and the Cloud focuses on Linux® and Unix® performance, while illuminating performance issues that are relevant to all operating systems. You’ll gain deep insight into how systems work and perform, and learn methodologies for analyzing and improving system and application performance. Gregg presents examples from bare-metal systems and virtualized cloud tenants running Linux-based Ubuntu®, Fedora®, CentOS, and the illumos-based Joyent® SmartOS™ and OmniTI OmniOS®. He systematically covers modern systems performance, including the “traditional” analysis of CPUs, memory, disks, and networks, and new areas including cloud computing and dynamic tracing. This book also helps you identify and fix the “unknown unknowns” of complex performance: bottlenecks that emerge from elements and interactions you were not aware of. The text concludes with a detailed case study, showing how a real cloud customer issue was analyzed from start to finish.

 

Coverage includes

• Modern performance analysis and tuning: terminology, concepts, models, methods, and techniques

• Dynamic tracing techniques and tools, including examples of DTrace, SystemTap, and perf

• Kernel internals: uncovering what the OS is doing

• Using system observability tools, interfaces, and frameworks

• Understanding and monitoring application performance

• Optimizing CPUs: processors, cores, hardware threads, caches, interconnects, and kernel scheduling

• Memory optimization: virtual memory, paging, swapping, memory architectures, busses, address spaces, and allocators

• File system I/O, including caching

• Storage devices/controllers, disk I/O workloads, RAID, and kernel I/O

• Network-related performance issues: protocols, sockets, interfaces, and physical connections

• Performance implications of OS and hardware-based virtualization, and new issues encountered with cloud computing

• Benchmarking: getting accurate results and avoiding common mistakes

 

This guide is indispensable for anyone who operates enterprise or cloud environments: system, network, database, and web admins; developers; and other professionals. For students and others new to optimization, it also provides exercises reflecting Gregg’s extensive instructional experience.

 

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Product Details

  • ISBN-13: 9780133390100
  • Publisher: Pearson Education
  • Publication date: 10/21/2013
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 1
  • Pages: 792
  • Sales rank: 680,574
  • File size: 39 MB
  • Note: This product may take a few minutes to download.

Meet the Author

Brendan Gregg, lead performance engineer at Joyent, analyzes performance and scalability throughout the software stack. As performance lead and kernel engineer at Sun Microsystems (and later Oracle), his work included developing the ZFS L2ARC, a pioneering file system technology for improving performance using flash memory. He has invented and developed many performance tools, including some that ship with Mac OS X and Oracle® Solaris™ 11. His recent work has included performance visualizations for Linux and illumos kernel analysis. For contributions to system administration, and his work on performance analysis methodologies, he is the recipient of the USENIX 2013 LISA Award for Outstanding Achievement in System Administration. He is also a coauthor of Dtrace: Dynamic Tracing in Oracle Solaris, Mac OS X and FreeBSD (Prentice Hall, 2011),  and Solaris™ Performance and Tools: DTrace and MDB Techniques for Solaris 10 and OpenSolaris, (Prentice Hall, 2007).

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Table of Contents

Acknowledgments xxxiii

About the Author xxxv

 

Chapter 1: Introduction 1

1.1 Systems Performance 1

1.2 Roles 2

1.3 Activities 3

1.4 Perspectives 4

1.5 Performance Is Challenging 4

1.6 Latency 6

1.7 Dynamic Tracing 7

1.8 Cloud Computing 8

1.9 Case Studies 9

 

Chapter 2: Methodology 15

2.1 Terminology 16

2.2 Models 17

2.3 Concepts 18

2.4 Perspectives 32

2.5 Methodology 35

2.6 Modeling 57

2.7 Capacity Planning 65

2.8 Statistics 69

2.9 Monitoring 74

2.10 Visualizations 76

2.11 Exercises 82

2.12 References 82

 

Chapter 3: Operating Systems 85

3.1 Terminology 86

3.2 Background 87

3.3 Kernels 105

3.4 Exercises 113

3.5 References 113

 

Chapter 4: Observability Tools 115

4.1 Tool Types 116

4.2 Observability Sources 120

4.3 DTrace 133

4.4 SystemTap 144

4.5 perf 149

4.6 Observing Observability 150

4.7 Exercises 151

4.8 References 151

 

Chapter 5: Applications 153

5.1 Application Basics 153

5.2 Application Performance Techniques 158

5.3 Programming Languages 163

5.4 Methodology and Analysis 167

5.5 Exercises 186

5.6 References 187

 

Chapter 6: CPUs 189

6.1 Terminology 190

6.2 Models 191

6.3 Concepts 193

6.4 Architecture 199

6.5 Methodology 214

6.6 Analysis 224

6.7 Experimentation 254

6.8 Tuning 256

6.9 Exercises 260

6.10 References 262

 

Chapter 7: Memory 265

7.1 Terminology 266

7.2 Concepts 267

7.3 Architecture 272

7.4 Methodology 289

7.5 Analysis 295

7.6 Tuning 314

7.7 Exercises 319

7.8 References 320

 

Chapter 8: File Systems 323

8.1 Terminology 324

8.2 Models 325

8.3 Concepts 326

8.4 Architecture 337

8.5 Methodology 353

8.6 Analysis 362

8.7 Experimentation 383

8.8 Tuning 387

8.9 Exercises 391

8.10 References 392

 

Chapter 9: Disks 395

9.1 Terminology 396

9.2 Models 397

9.3 Concepts 399

9.4 Architecture 407

9.5 Methodology 421

9.6 Analysis 431

9.7 Experimentation 465

9.8 Tuning 467

9.9 Exercises 470

9.10 References 471

 

Chapter 10: Network 473

10.1 Terminology 474

10.2 Models 474

10.3 Concepts 476

10.4 Architecture 483

10.5 Methodology 493

10.6 Analysis 503

10.7 Experimentation 535

10.8 Tuning 536

10.9 Exercises 542

10.10 References 543

 

Chapter 11: Cloud Computing 545

11.1 Background 546

11.2 OS Virtualization 551

11.3 Hardware Virtualization 563

11.4 Comparisons 581

11.5 Exercises 583

11.6 References 584

 

Chapter 12: Benchmarking 587

12.1 Background 588

12.2 Benchmarking Types 597

12.3 Methodology 602

12.4 Benchmark Questions 613

12.5 Exercises 614

12.6 References 615

 

Chapter 13: Case Study 617

13.1 Case Study: The Red Whale 617

13.2 Comments 633

13.3 Additional Information 634

13.4 References 634

 

Appendix A: USE Method: Linux 637

Physical Resources 637

Software Resources 640

Reference 641

 

Appendix B: USE Method: Solaris 643

Physical Resources 643

Software Resources 646

References 647

 

Appendix C: sar Summary 649

Linux 649

Solaris 650

 

Appendix D: DTrace One-Liners 651

syscall Provider 651

proc Provider 655

profile Provider 655

sched Provider 657

fbt Provider 658

pid Provider 659

io Provider 660

sysinfo Provider 660

vminfo Provider 661

ip Provider 661

tcp provider 662

udp provider 663

 

Appendix E: DTrace to SystemTap 665

Functionality 665

Terminology 666

Probes 666

Built-in Variables 667

Functions 668

Example 1: Listing syscall Entry Probes 668

Example 2: Summarize read() Returned Size 668

Example 3: Count syscalls by Process Name 670

Example 4: Count syscalls by syscall Name, for Process ID 123 671

Example 5: Count syscalls by syscall Name, for "httpd" Processes 672

Example 6: Trace File open()s with Process Name and Path Name 672

Example 7: Summarize read() Latency for "mysqld" Processes 672

Example 8: Trace New Processes with Process Name and Arguments 673

Example 9: Sample Kernel Stacks at 100 Hz 674

References 674

 

Appendix F: Solutions to Selected Exercises 675

Chapter 2 Methodology 675

Chapter 3 Operating Systems 675

Chapter 6 CPUs 675

Chapter 7 Memory 676

Chapter 8 File Systems 676

Chapter 9 Disks 677

Chapter 11 Cloud Computing 677

 

Appendix G: Systems Performance Who's Who 679

 

Glossary 683

Bibliography 689

Index 697

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