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Most applications today are distributed in some fashion. Monitoring the health and performance of these distributed architectures requires a new approach. Enter distributed tracing, a method of profiling and monitoring applications--especially those that use microservice architectures. There's just one problem: distributed tracing can be hard. But it doesn't have to be. With this practical guide, you'll learn what distributed tracing is and how to use it to understand the performance and operation of your software. Key players at LightStep walk you through instrumenting your code for tracing, collecting the data that your instrumentation produces, and turning it into useful, operational insights. If you want to start implementing distributed tracing, this book tells you what you need to know. You'll learn: The pieces of a distributed tracing deployment: Instrumentation, data collection, and delivering value Best practices for instrumentation (the methods for generating trace data from your service) How to deal with or avoid overhead, costs, and sampling How to work with spans (the building blocks of request-based distributed traces) and choose span characteristics that lead to valuable traces Where distributed tracing is headed in the future
Since most applications today are distributed in some fashion, monitoring their health and performance requires a new approach. Enter distributed tracing, a method of profiling and monitoring distributed applications—particularly those that use microservice architectures. There’s just one problem: distributed tracing can be hard. But it doesn’t have to be. With this guide, you’ll learn what distributed tracing is and how to use it to understand the performance and operation of your software. Key players at LightStep and other organizations walk you through instrumenting your code for tracing, collecting the data that your instrumentation produces, and turning it into useful operational insights. If you want to implement distributed tracing, this book tells you what you need to know. You’ll learn: The pieces of a distributed tracing deployment: instrumentation, data collection, and analysis Best practices for instrumentation: methods for generating trace data from your services How to deal with (or avoid) overhead using sampling and other techniques How to use distributed tracing to improve baseline performance and to mitigate regressions quickly Where distributed tracing is headed in the future
Since most applications today are distributed in some fashion, monitoring their health and performance requires a new approach. Enter distributed tracing, a method of profiling and monitoring distributed applications—particularly those that use microservice architectures. There’s just one problem: distributed tracing can be hard. But it doesn’t have to be. With this guide, you’ll learn what distributed tracing is and how to use it to understand the performance and operation of your software. Key players at LightStep and other organizations walk you through instrumenting your code for tracing, collecting the data that your instrumentation produces, and turning it into useful operational insights. If you want to implement distributed tracing, this book tells you what you need to know. You’ll learn: The pieces of a distributed tracing deployment: instrumentation, data collection, and analysis Best practices for instrumentation: methods for generating trace data from your services How to deal with (or avoid) overhead using sampling and other techniques How to use distributed tracing to improve baseline performance and to mitigate regressions quickly Where distributed tracing is headed in the future
Understand how to apply distributed tracing to microservices-based architectures Key FeaturesA thorough conceptual introduction to distributed tracingAn exploration of the most important open standards in the spaceA how-to guide for code instrumentation and operating a tracing infrastructureBook Description Mastering Distributed Tracing will equip you to operate and enhance your own tracing infrastructure. Through practical exercises and code examples, you will learn how end-to-end tracing can be used as a powerful application performance management and comprehension tool. The rise of Internet-scale companies, like Google and Amazon, ushered in a new era of distributed systems operating on thousands of nodes across multiple data centers. Microservices increased that complexity, often exponentially. It is harder to debug these systems, track down failures, detect bottlenecks, or even simply understand what is going on. Distributed tracing focuses on solving these problems for complex distributed systems. Today, tracing standards have developed and we have much faster systems, making instrumentation less intrusive and data more valuable. Yuri Shkuro, the creator of Jaeger, a popular open-source distributed tracing system, delivers end-to-end coverage of the field in Mastering Distributed Tracing. Review the history and theoretical foundations of tracing; solve the data gathering problem through code instrumentation, with open standards like OpenTracing, W3C Trace Context, and OpenCensus; and discuss the benefits and applications of a distributed tracing infrastructure for understanding, and profiling, complex systems. What you will learnHow to get started with using a distributed tracing systemHow to get the most value out of end-to-end tracingLearn about open standards in the spaceLearn about code instrumentation and operating a tracing infrastructureLearn where distributed tracing fits into microservices as a core functionWho this book is for Any developer interested in testing large systems will find this book very revealing and in places, surprising. Every microservice architect and developer should have an insight into distributed tracing, and the book will help them on their way. System administrators with some development skills will also benefit. No particular programming language skills are required, although an ability to read Java, while non-essential, will help with the core chapters.
Since most applications today are distributed in some fashion, monitoring their health and performance requires a new approach. Enter distributed tracing, a method of profiling and monitoring distributed applications--particularly those that use microservice architectures. There's just one problem: distributed tracing can be hard. But it doesn't have to be. With this guide, you'll learn what distributed tracing is and how to use it to understand the performance and operation of your software. Key players at LightStep and other organizations walk you through instrumenting your code for tracing, collecting the data that your instrumentation produces, and turning it into useful operational insights. If you want to implement distributed tracing, this book tells you what you need to know. You'll learn: The pieces of a distributed tracing deployment: instrumentation, data collection, and analysis Best practices for instrumentation: methods for generating trace data from your services How to deal with (or avoid) overhead using sampling and other techniques How to use distributed tracing to improve baseline performance and to mitigate regressions quickly Where distributed tracing is headed in the future.
The overwhelming majority of a software system’s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization. This book is divided into four sections: Introduction—Learn what site reliability engineering is and why it differs from conventional IT industry practices Principles—Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practices—Understand the theory and practice of an SRE’s day-to-day work: building and operating large distributed computing systems Management—Explore Google's best practices for training, communication, and meetings that your organization can use
As nations race to hone contact-tracing efforts, the world's experts consider strategies for maximum transparency and impact. As public health professionals around the world work tirelessly to respond to the COVID-19 pandemic, it is clear that traditional methods of contact tracing need to be augmented in order to help address a public health crisis of unprecedented scope. Innovators worldwide are racing to develop and implement novel public-facing technology solutions, including digital contact tracing technology. These technological products may aid public health surveillance and containment strategies for this pandemic and become part of the larger toolbox for future infectious outbreak prevention and control. As technology evolves in an effort to meet our current moment, Johns Hopkins Project on Ethics and Governance of Digital Contact Tracing Technologies—a rapid research and expert consensus group effort led by Dr. Jeffrey P. Kahn of the Johns Hopkins Berman Institute of Bioethics in collaboration with the university's Center for Health Security—carried out an in-depth analysis of the technology and the issues it raises. Drawing on this analysis, they produced a report that includes detailed recommendations for technology companies, policymakers, institutions, employers, and the public. The project brings together perspectives from bioethics, health security, public health, technology development, engineering, public policy, and law to wrestle with the complex interactions of the many facets of the technology and its applications. This team of experts from Johns Hopkins University and other world-renowned institutions has crafted clear and detailed guidelines to help manage the creation, implementation, and application of digital contact tracing. Digital Contact Tracing for Pandemic Response is the essential resource for this fast-moving crisis. Contributors: Joseph Ali, JD; Anne Barnhill, PhD; Anita Cicero, JD; Katelyn Esmonde, PhD; Amelia Hood, MA; Brian Hutler, Phd, JD; Jeffrey P. Kahn, PhD, MPH; Alan Regenberg, MBE; Crystal Watson, DrPH, MPH; Matthew Watson; Robert Califf, MD, MACC; Ruth Faden, PhD, MPH; Divya Hosangadi, MSPH; Nancy Kass, ScD; Alain Labrique, PhD, MHS, MS; Deven McGraw, JD, MPH, LLM; Michelle Mello, JD, PhD; Michael Parker, BEd (Hons), MA, PhD; Stephen Ruckman, JD, MSc, MAR; Lainie Rutkow, JD, MPH, PhD; Josh Sharfstein, MD; Jeremy Sugarman, MD, MPH, MA; Eric Toner, MD; Mar Trotochaud, MSPH; Effy Vayena, PhD; Tal Zarsky, JSD, LLM, LLB
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(R) and Unix(R) 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(R), Fedora(R), CentOS, and the illumos-based Joyent(R) SmartOS(TM) and OmniTI OmniOS(R). 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.
In a microservices architecture, the whole is indeed greater than the sum of its parts. But in practice, individual microservices can inadvertently impact others and alter the end user experience. Effective microservices architectures require standardization on an organizational level with the help of a platform engineering team. This practical book provides a series of progressive steps that platform engineers can apply technically and organizationally to achieve highly resilient Java applications. Author Jonathan Schneider covers many effective SRE practices from companies leading the way in microservices adoption. You’ll examine several patterns discovered through much trial and error in recent years, complete with Java code examples. Chapters are organized according to specific patterns, including: Application metrics: Monitoring for availability with Micrometer Debugging with observability: Logging and distributed tracing; failure injection testing Charting and alerting: Building effective charts; KPIs for Java microservices Safe multicloud delivery: Spinnaker, deployment strategies, and automated canary analysis Source code observability: Dependency management, API utilization, and end-to-end asset inventory Traffic management: Concurrency of systems; platform, gateway, and client-side load balancing
Annotation Over the past 10 years, distributed systems have become more fine-grained. From the large multi-million line long monolithic applications, we are now seeing the benefits of smaller self-contained services. Rather than heavy-weight, hard to change Service Oriented Architectures, we are now seeing systems consisting of collaborating microservices. Easier to change, deploy, and if required retire, organizations which are in the right position to take advantage of them are yielding significant benefits. This book takes an holistic view of the things you need to be cognizant of in order to pull this off. It covers just enough understanding of technology, architecture, operations and organization to show you how to move towards finer-grained systems.