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Use BPF Tools to Optimize Performance, Fix Problems, and See Inside Running Systems BPF-based performance tools give you unprecedented visibility into systems and applications, so you can optimize performance, troubleshoot code, strengthen security, and reduce costs. BPF Performance Tools: Linux System and Application Observability is the definitive guide to using these tools for observability. Pioneering BPF expert Brendan Gregg presents more than 150 ready-to-run analysis and debugging tools, expert guidance on applying them, and step-by-step tutorials on developing your own. You’ll learn how to analyze CPUs, memory, disks, file systems, networking, languages, applications, containers, hypervisors, security, and the kernel. Gregg guides you from basic to advanced tools, helping you generate deeper, more useful technical insights for improving virtually any Linux system or application. • Learn essential tracing concepts and both core BPF front-ends: BCC and bpftrace • Master 150+ powerful BPF tools, including dozens created just for this book, and available for download • Discover practical strategies, tips, and tricks for more effective analysis • Analyze compiled, JIT-compiled, and interpreted code in multiple languages: C, Java, bash shell, and more • Generate metrics, stack traces, and custom latency histograms • Use complementary tools when they offer quick, easy wins • Explore advanced tools built on BPF: PCP and Grafana for remote monitoring, eBPF Exporter, and kubectl-trace for tracing Kubernetes • Foreword by Alexei Starovoitov, creator of the new BPF BPF Performance Tools will be an indispensable resource for all administrators, developers, support staff, and other IT professionals working with any recent Linux distribution in any enterprise or cloud environment.
Securing, observing, and troubleshooting containerized workloads on Kubernetes can be daunting. It requires a range of considerations, from infrastructure choices and cluster configuration to deployment controls and runtime and network security. With this practical book, you'll learn how to adopt a holistic security and observability strategy for building and securing cloud native applications running on Kubernetes. Whether you're already working on cloud native applications or are in the process of migrating to its architecture, this guide introduces key security and observability concepts and best practices to help you unleash the power of cloud native applications. Authors Brendan Creane and Amit Gupta from Tigera take you through the full breadth of new cloud native approaches for establishing security and observability for applications running on Kubernetes. Learn why you need a security and observability strategy for cloud native applications and determine your scope of coverage Understand key concepts behind the book's security and observability approach Explore the technology choices available to support this strategy Discover how to share security responsibilities across multiple teams or roles Learn how to architect Kubernetes security and observability for multicloud and hybrid environments
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
Build your expertise in the BPF virtual machine in the Linux kernel with this practical guide for systems engineers. You’ll not only dive into the BPF program lifecycle but also learn to write applications that observe and modify the kernel’s behavior; inject code to monitor, trace, and securely observe events in the kernel; and more. Authors David Calavera and Lorenzo Fontana help you harness the power of BPF to make any computing system more observable. Familiarize yourself with the essential concepts you’ll use on a day-to-day basis and augment your knowledge about performance optimization, networking, and security. Then see how it all comes together with code examples in C, Go, and Python. Write applications that use BPF to observe and modify the Linux kernel’s behavior on demand Inject code to monitor, trace, and observe events in the kernel in a secure way—no need to recompile the kernel or reboot the system Explore code examples in C, Go, and Python Gain a more thorough understanding of the BPF program lifecycle
Continuous delivery adds enormous value to the business and the entire software delivery lifecycle, but adopting this practice means mastering new skills typically outside of a developer’s comfort zone. In this practical book, Daniel Bryant and Abraham Marín-Pérez provide guidance to help experienced Java developers master skills such as architectural design, automated quality assurance, and application packaging and deployment on a variety of platforms. Not only will you learn how to create a comprehensive build pipeline for continually delivering effective software, but you’ll also explore how Java application architecture and deployment platforms have affected the way we rapidly and safely deliver new software to production environments. Get advice for beginning or completing your migration to continuous delivery Design architecture to enable the continuous delivery of Java applications Build application artifacts including fat JARs, virtual machine images, and operating system container (Docker) images Use continuous integration tooling like Jenkins, PMD, and find-sec-bugs to automate code quality checks Create a comprehensive build pipeline and design software to separate the deploy and release processes Explore why functional and system quality attribute testing is vital from development to delivery Learn how to effectively build and test applications locally and observe your system while it runs in production
The purpose of this fantastically useful book is to lay out an overview on possible tools for state reconstruction in nonlinear systems. Here, basic observability notions and observer structures are recalled, together with ingredients for advanced designs on this basis. The problem of state reconstruction in dynamical systems, known as observer problem, is crucial for controlling or even merely monitoring processes. For linear systems, the theory has been well established for several years, so this book attempts to tackle the problem for non-linear systems.
The concept of observability of entities in physical science is typically analyzed in terms of the nature and significance of a dichotomy between observables and unobservables. In this book, however, this categorization is resisted and observability is analyzed in a descriptive way in terms of the information which one can receive through interaction with objects in the world. The account of interaction and the transfer of information is done using applicable scientific theories. In this way the question of observability of scientific entities is put to science itself. Several examples are presented which show how this interaction-information account of observability is done. It is demonstrated that observability has many dimensions which are in general orthogonal. The epistemic significance of these dimensions is explained. This study is intended primarily as a method for understanding problems of observability rather than as a solution to those problems. The important issue of scientific realism and its relation to observability, however, demands attention. Hence, the implication of the interaction-information account for realism is drawn in terms of the epistemic significance of the dimensions of observability. This amounts to specifying what it is about good observations that make them objective evidence for scientific theories.
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
Janet Gregory and Lisa Crispin pioneered the agile testing discipline with their previous work, Agile Testing. Now, in More Agile Testing, they reflect on all they've learned since. They address crucial emerging issues, share evolved agile practices, and cover key issues agile testers have asked to learn more about. Packed with new examples from real teams, this insightful guide offers detailed information about adapting agile testing for your environment; learning from experience and continually improving your test processes; scaling agile testing across teams; and overcoming the pitfalls of automated testing. You'll find brand-new coverage of agile testing for the enterprise, distributed teams, mobile/embedded systems, regulated environments, data warehouse/BI systems, and DevOps practices. You'll come away understanding - How to clarify testing activities within the team - Ways to collaborate with business experts to identify valuable features and deliver the right capabilities - How to design automated tests for superior reliability and easier maintenance - How agile team members can improve and expand their testing skills - How to plan "just enough," balancing small increments with larger feature sets and the entire system - How to use testing to identify and mitigate risks associated with your current agile processes and to prevent defects - How to address challenges within your product or organizational context - How to perform exploratory testing using "personas" and "tours" - Exploratory testing approaches that engage the whole team, using test charters with session- and thread-based techniques - How to bring new agile testers up to speed quickly-without overwhelming them The eBook edition of More Agile Testing also is available as part of a two-eBook collection, The Agile Testing Collection (9780134190624).
The author approaches an old classic problem - the existence of solutions of Navier-Stokes equations. The main objective is to model and derive of equation of continuity, Euler equation of fluid motion, energy flux equation, Navier-Stokes equations from the observer point of view and solve classic problem for this interpretation of fluid motion laws. If we have a piece of metal or a volume of liquid, the idea impresses itself upon us that it is divisible without limit, that any part of it, however small, would again have the same properties. But, wherever the methods of research in the physics of matter were refined sufficiently, limits to divisibility were reached that are not due to the inadequacy of our experiments but to the nature of the subject matter. Observability in mathematics were developed by the author based on denial of infinity idea. He introduces observers into arithmetic, and arithmetic becomes dependent on observers. And after that the basic mathematical parts also become dependent on observers. This approach permits to reconsider the fluid motion laws, analyze them and get solutions of classic problems. Table of Contents 1. Introduction. 2. Observability and Arithmetic. 3. Observability and Vector Algebra. 4. Observability and Mathematical Analysis (Calculus). 5. Classic Fluid Mechanics equations and Observability. 6. Observability and Thermodynamical equations. 7. Observability and equation of continuity. 8. Observability and Euler equation of motion of the fluid. 9. Observability and energy flux and moment flux equations. 10. Observability and incompressible fluids. 11. Observability and Navier-Stokes equations. 12. Observability and Relativistic Fluid Mechanics. 13. Appendix: Review of publications of the Mathematics with Observers. 14. Glossary. Bibliography Index Biography Boris Khots, DrSci, lives in Iowa, USA, Independent Researcher. Alma Mater - Moscow State Lomonosov University, Department of Mathematics and Mechanics (mech-math). Creator of Observer’s Mathematics. Participant of more than 30 Mathematical international congresses, conferences. In particular, participated with presentation at International Congresses of Mathematicians on 1998 (Germany), 2002 (China), 2006 (Spain), 2010 (India), 2014 (South Korea). More than 150 mathematical books and papers.