Book picks similar to
Distributed Tracing in Practice: Instrumenting, Analyzing, and Debugging Microservices by Austin Parker
tech
microservices
programming
software-engineering
The Little Book on CoffeeScript
Alex MacCaw - 2012
Through example code, this guide demonstrates how CoffeeScript abstracts JavaScript, providing syntactical sugar and preventing many common errors. You’ll learn CoffeeScript’s syntax and idioms step by step, from basic variables and functions to complex comprehensions and classes.Written by Alex MacCaw, author of JavaScript Web Applications (O’Reilly), with contributions from CoffeeScript creator Jeremy Ashkenas, this book quickly teaches you best practices for using this language—not just on the client side, but for server-side applications as well. It’s time to take a ride with the little language that could.Discover how CoffeeScript’s syntax differs from JavaScriptLearn about features such as array comprehensions, destructuring assignments, and classesExplore CoffeeScript idioms and compare them to their JavaScript counterpartsCompile CoffeeScript files in static sites with the Cake build systemUse CommonJS modules to structure and deploy CoffeeScript client-side applicationsExamine JavaScript’s bad parts—including features CoffeeScript was able to fix
The REST API Design Handbook
George Reese - 2012
The RESTful approach to web services design is rapidly become the approach of choice. Unfortunately, too few people have truly solid REST API design skills, and discussions of REST can become bogged down in dry theory.The REST API Design Handbook is a simple, practical guide to aid software engineers and software architects create lasting, scalable APIs based on REST architectural principles. The book provides a sound foundation in discussing the constraints that define a REST API. It quickly goes beyond that into the practical aspects of implementing such an API in the real world.Written by cloud computing expert George Reese, The REST API Design Handbook reflects hands on work in consuming many different third party APIs as well the development of REST-based web services APIs. It addresses all of the debates the commonly arise while creating these APIs. Subjects covered include:* REST architectural constraints* Using HTTP methods and response codes in an API* Authenticating RESTful API calls* Versioning* Asynchronous Operations* Pagination and Streaming* Polling and Push Notifications* Rate Limiting
The Art of Doing Science and Engineering: Learning to Learn
Richard Hamming - 1996
By presenting actual experiences and analyzing them as they are described, the author conveys the developmental thought processes employed and shows a style of thinking that leads to successful results is something that can be learned. Along with spectacular successes, the author also conveys how failures contributed to shaping the thought processes. Provides the reader with a style of thinking that will enhance a person's ability to function as a problem-solver of complex technical issues. Consists of a collection of stories about the author's participation in significant discoveries, relating how those discoveries came about and, most importantly, provides analysis about the thought processes and reasoning that took place as the author and his associates progressed through engineering problems.
DevOps Troubleshooting: Linux Server Best Practices
Kyle Rankin - 2012
It has saved me hours in troubleshooting complicated operations problems." -Trotter Cashion, cofounder, Mashion DevOps can help developers, QAs, and admins work together to solve Linux server problems far more rapidly, significantly improving IT performance, availability, and efficiency. To gain these benefits, however, team members need common troubleshooting skills and practices. In
DevOps Troubleshooting: Linux Server Best Practices
, award-winning Linux expert Kyle Rankin brings together all the standardized, repeatable techniques your team needs to stop finger-pointing, collaborate effectively, and quickly solve virtually any Linux server problem. Rankin walks you through using DevOps techniques to troubleshoot everything from boot failures and corrupt disks to lost email and downed websites. You'll master indispensable skills for diagnosing high-load systems and network problems in production environments. Rankin shows how to Master DevOps' approach to troubleshooting and proven Linux server problem-solving principles Diagnose slow servers and applications by identifying CPU, RAM, and Disk I/O bottlenecks Understand healthy boots, so you can identify failure points and fix them Solve full or corrupt disk issues that prevent disk writes Track down the sources of network problems Troubleshoot DNS, email, and other network services Isolate and diagnose Apache and Nginx Web server failures and slowdowns Solve problems with MySQL and Postgres database servers and queries Identify hardware failures-even notoriously elusive intermittent failures
Data Science from Scratch: First Principles with Python
Joel Grus - 2015
In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.
If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out.
Get a crash course in Python
Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science
Collect, explore, clean, munge, and manipulate data
Dive into the fundamentals of machine learning
Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering
Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
Amazon Web Services in Action
Andreas Wittig - 2015
The book will teach you about the most important services on AWS. You will also learn about best practices regarding automation, security, high availability, and scalability.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyPhysical data centers require lots of equipment and take time and resources to manage. If you need a data center, but don't want to build your own, Amazon Web Services may be your solution. Whether you're analyzing real-time data, building software as a service, or running an e-commerce site, AWS offers you a reliable cloud-based platform with services that scale. All services are controllable via an API which allows you to automate your infrastructure.About the BookAmazon Web Services in Action introduces you to computing, storing, and networking in the AWS cloud. The book will teach you about the most important services on AWS. You will also learn about best practices regarding security, high availability and scalability.You'll start with a broad overview of cloud computing and AWS and learn how to spin-up servers manually and from the command line. You'll learn how to automate your infrastructure by programmatically calling the AWS API to control every part of AWS. You will be introduced to the concept of Infrastructure as Code with the help of AWS CloudFormation.You will learn about different approaches to deploy applications on AWS. You'll also learn how to secure your infrastructure by isolating networks, controlling traffic and managing access to AWS resources. Next, you'll learn options and techniques for storing your data. You will experience how to integrate AWS services into your own applications by the use of SDKs. Finally, this book teaches you how to design for high availability, fault tolerance, and scalability.What's InsideOverview of cloud concepts and patternsManage servers on EC2 for cost-effectivenessInfrastructure automation with Infrastructure as Code (AWS CloudFormation)Deploy applications on AWSStore data on AWS: SQL, NoSQL, object storage and block storageIntegrate Amazon's pre-built servicesArchitect highly available and fault tolerant systemsAbout the ReaderWritten for developers and DevOps engineers moving distributed applications to the AWS platform.About the AuthorsAndreas Wittig and Michael Wittig are software engineers and consultants focused on AWS and web development.Table of ContentsPART 1 GETTING STARTEDWhat is Amazon Web Services?A simple example: WordPress in five minutesPART 2 BUILDING VIRTUAL INFRASTRUCTURE WITH SERVERS AND NETWORKINGUsing virtual servers: EC2Programming your infrastructure: the command line, SDKs, and CloudFormationAutomating deployment: CloudFormation, Elastic Beanstalk, and OpsWorksSecuring your system: IAM, security groups, and VPCPART 3 STORING DATA IN THE CLOUDStoring your objects: S3 and GlacierStoring your data on hard drives: EBS and instance storeUsing a relational database service: RDSProgramming for the NoSQL database service: DynamoDBPART 4 ARCHITECTING ON AWSAchieving high availability: availability zones, auto-scaling, and CloudWatchDecoupling your infrastructure: ELB and SQSDesigning for fault-toleranceScaling up and down: auto-scaling and CloudWatch
Data Science at the Command Line: Facing the Future with Time-Tested Tools
Jeroen Janssens - 2014
You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.To get you started--whether you're on Windows, OS X, or Linux--author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.Discover why the command line is an agile, scalable, and extensible technology. Even if you're already comfortable processing data with, say, Python or R, you'll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
Trevor Hastie - 2001
With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.
Hibernate in Action
Christian Bauer - 2004
Why is this open-source tool so popular? Because it automates a tedious task: persisting your Java objects to a relational database. The inevitable mismatch between your object-oriented code and the relational database requires you to write code that maps one to the other. This code is often complex, tedious and costly to develop. Hibernate does the mapping for you.Not only that, Hibernate makes it easy. Positioned as a layer between your application and your database, Hibernate takes care of loading and saving of objects. Hibernate applications are cheaper, more portable, and more resilient to change. And they perform better than anything you are likely to develop yourself."Hibernate in Action" carefully explains the concepts you need, then gets you going. It builds on a single example to show you how to use Hibernate in practice, how to deal with concurrency and transactions, how to efficiently retrieve objects and use caching.The authors created Hibernate and they field questions from the Hibernate community every day-they know how to make Hibernate sing. Knowledge and insight seep out of every pore of this book."What's Inside"- ORM concepts- Getting started- Many real-world tasks- The Hibernate application development process
Just for Fun: The Story of an Accidental Revolutionary
Linus Torvalds - 2001
Then he wrote a groundbreaking operating system and distributed it via the Internet -- for free. Today Torvalds is an international folk hero. And his creation LINUX is used by over 12 million people as well as by companies such as IBM.Now, in a narrative that zips along with the speed of e-mail, Torvalds gives a history of his renegade software while candidly revealing the quirky mind of a genius. The result is an engrossing portrayal of a man with a revolutionary vision, who challenges our values and may change our world.
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
Pedro Domingos - 2015
In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.
Apprenticeship Patterns: Guidance for the Aspiring Software Craftsman
Dave Hoover - 2009
To grow professionally, you also need soft skills and effective learning techniques. Honing those skills is what this book is all about. Authors Dave Hoover and Adewale Oshineye have cataloged dozens of behavior patterns to help you perfect essential aspects of your craft. Compiled from years of research, many interviews, and feedback from O'Reilly's online forum, these patterns address difficult situations that programmers, administrators, and DBAs face every day. And it's not just about financial success. Apprenticeship Patterns also approaches software development as a means to personal fulfillment. Discover how this book can help you make the best of both your life and your career. Solutions to some common obstacles that this book explores in-depth include:Burned out at work? "Nurture Your Passion" by finding a pet project to rediscover the joy of problem solving.Feeling overwhelmed by new information? Re-explore familiar territory by building something you've built before, then use "Retreat into Competence" to move forward again.Stuck in your learning? Seek a team of experienced and talented developers with whom you can "Be the Worst" for a while. "Brilliant stuff! Reading this book was like being in a time machine that pulled me back to those key learning moments in my career as a professional software developer and, instead of having to learn best practices the hard way, I had a guru sitting on my shoulder guiding me every step towards master craftsmanship. I'll certainly be recommending this book to clients. I wish I had this book 14 years ago!" -Russ Miles, CEO, OpenCredo
The Well-Grounded Rubyist
David A. Black - 2008
It's a beautifully written tutorial that begins with the basic steps to get your first Ruby program up and running and goes on to explore sophisticated topics like callable objects, reflection, and threading. Whether the topic is simple or tough, the book's easy-to-follow examples and explanations will give you immediate confidence as you build your Ruby programming skills.The Well-Grounded Rubyist is a thoroughly revised and updated edition of the best-selling Ruby for Rails. In this new book, expert author David A. Black moves beyond Rails and presents a broader view of Ruby. It covers Ruby 1.9, and keeps the same sharp focus and clear writing that made Ruby for Rails stand out.Starting with the basics, The Well-Grounded Rubyist explains Ruby objects and their interactions from the ground up. In the middle chapters, the book turns to an examination of Ruby's built-in, core classes, showing the reader how to manipulate strings, numbers, arrays, ranges, hashes, sets, and more. Regular expressions get attention, as do file and other I/O operations.Along the way, the reader is introduced to numerous tools included in the standard Ruby distribution--tools like the task manager Rake and the interactive Ruby console-based interpreter Irb--that facilitate Ruby development and make it an integrated and pleasant experience.The book encompasses advanced topics, like the design of Ruby's class and module system, and the use of Ruby threads, taking even the new Rubyist deep into the language and giving every reader the foundations necessary to use, explore, and enjoy this unusually popular and versatile language.It's no wonder one reader commented: "The technical depth is just right to not distract beginners, yet detailed enough for more advanced readers."Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
PostgreSQL 9.0 High Performance
Gregory Smith - 2010
You could spend years discovering solutions to them all, step by step as you encounter them. Or you can just look in here. All successful database applications are destined to eventually run into issues scaling up their performance. Peek into the future of your PostgreSQL database's problems today. Know the warning signs to look for, and how to avoid the most common issues before they even happen. Surprisingly, most PostgreSQL database applications evolve in the same way: Choose the right hardware. Tune the operating system and server memory use. Optimize queries against the database, with the right indexes. Monitor every layer, from hardware to queries, using some tools that are inside PostgreSQL and others that are external. Using monitoring insight, continuously rework the design and configuration. On reaching the limits of a single server, break things up; connection pooling, caching, partitioning, and replication can all help handle increasing database workloads. The path to a high performance database system isn't always easy. But it doesn't have to be mysterious with the right guide. This book is a clear, step-by-step guide to optimizing and scaling up PostgreSQL database servers. - Publisher.
xUnit Test Patterns: Refactoring Test Code
Gerard Meszaros - 2003
An effective testing strategy will deliver new functionality more aggressively, accelerate user feedback, and improve quality. However, for many developers, creating effective automated tests is a unique and unfamiliar challenge. xUnit Test Patterns is the definitive guide to writing automated tests using xUnit, the most popular unit testing framework in use today. Agile coach and test automation expert Gerard Meszaros describes 68 proven patterns for making tests easier to write, understand, and maintain. He then shows you how to make them more robust and repeatable--and far more cost-effective. Loaded with information, this book feels like three books in one. The first part is a detailed tutorial on test automation that covers everything from test strategy to in-depth test coding. The second part, a catalog of 18 frequently encountered "test smells," provides trouble-shooting guidelines to help you determine the root cause of problems and the most applicable patterns. The third part contains detailed descriptions of each pattern, including refactoring instructions illustrated by extensive code samples in multiple programming languages. Topics covered includeWriting better tests--and writing them faster The four phases of automated tests: fixture setup, exercising the system under test, result verification, and fixture teardown Improving test coverage by isolating software from its environment using Test Stubs and Mock Objects Designing software for greater testability Using test "smells" (including code smells, behavior smells, and project smells) to spot problems and know when and how to eliminate them Refactoring tests for greater simplicity, robustness, and execution speed This book will benefit developers, managers, and testers working with any agile or conventional development process, whether doing test-driven development or writing the tests last. While the patterns and smells are especially applicable to all members of the xUnit family, they also apply to next-generation behavior-driven development frameworks such as RSpec and JBehave and to other kinds of test automation tools, including recorded test tools and data-driven test tools such as Fit and FitNesse.Visual Summary of the Pattern Language Foreword Preface Acknowledgments Introduction Refactoring a Test PART I: The Narratives Chapter 1 A Brief Tour Chapter 2 Test Smells Chapter 3 Goals of Test Automation Chapter 4 Philosophy of Test Automation Chapter 5 Principles of Test Automation Chapter 6 Test Automation Strategy Chapter 7 xUnit Basics Chapter 8 Transient Fixture Management Chapter 9 Persistent Fixture Management Chapter 10 Result Verification Chapter 11 Using Test Doubles Chapter 12 Organizing Our Tests Chapter 13 Testing with Databases Chapter 14 A Roadmap to Effective Test Automation PART II: The Test Smells Chapter 15 Code Smells Chapter 16 Behavior Smells Chapter 17 Project Smells PART III: The Patterns Chapter 18 Test Strategy Patterns Chapter 19 xUnit Basics Patterns Chapter 20 Fixture Setup Patterns Chapter 21 Result Verification Patterns Chapter 22 Fixture Teardown Patterns Chapter 23 Test Double Patterns Chapter 24 Test Organization Patterns Chapter 25 Database Patterns Chapter 26 Design-for-Testability Patterns Chapter 27 Value Patterns PART IV: Appendixes Appendix A Test Refactorings Appendix B xUnit Terminology Appendix C xUnit Family Members Appendix D Tools Appendix E Goals and Principles Appendix F Smells, Aliases, and Causes Appendix G Patterns, Aliases, and Variations Glossary References Index "