Troubleshooting OpenStack. Click here to enter text

Tony Campbell

OpenStack is a collection of software projects that work together to provide a cloud fabric. OpenStack is one of the fastest growing open source projects in history that unlocks cloud computing for everyone. With OpenStack, you are able to create public or private clouds on your own hardware. The flexibility and control afforded by OpenStack puts the cloud within reach of anyone willing to learn this technology.Starting with an introduction to OpenStack troubleshooting tools, we’ll walk through each OpenStack service and how you can quickly diagnose, troubleshoot, and correct problems in your OpenStack. Understanding the various projects and how they interact is essential for anyone attempting to troubleshoot an OpenStack cloud. We will start by explaining each of the major components and the dependencies between them, and move on to show you how to identify and utilize an effective set of OpenStack troubleshooting tools and fix common Keystone problems. Next, we will expose you to common errors and problems you may encounter when using the OpenStack Block Storage service (Cinder). We will then examine Heat, the OpenStack Orchestration Service, where you will learn how to trace errors, determine their root cause, and effectively correct the issue.Finally, you will get to know the best practices to architect your OpenStack cloud in order to achieve optimal performance, availability, and reliability.

Functional Python Programming. Discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads - Second Edition

Steven F. Lott

If you’re a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you’ll explore common functional features such as first-class and higher-order functions, pure functions, and more. You’ll see how these are accomplished in Python 3.6 to give you the core foundations you’ll build upon. After that, you’ll discover common functional optimizations for Python to help your apps reach even higher speeds. You’ll learn FP concepts such as lazy evaluation using Python’s generator functions and expressions. Moving forward, you’ll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you’ll at look at the PyMonad project and some larger examples to put everything into perspective.

Multithreading with C# Cookbook. Quick answers to common problems - Second Edition

Evgenii Agafonov

Multi-core processors are synonymous with computing speed and power in today’s world, which is why multithreading has become a key concern for C# developers. Multithreaded code helps you create effective, scalable, and responsive applications.This is an easy-to-follow guide that will show you difficult programming problems in context. You will learn how to solve them with practical, hands-on, recipes. With these recipes, you’ll be able to start creating your own scalable and reliable multithreaded applications. Starting from learning what a thread is, we guide you through the basics and then move on to more advanced concepts such as task parallel libraries, C# asynchronous functions, and much more.Rewritten to the latest C# specification, C# 6, and updated with new and modern recipes to help you make the most of the hardware you have available, this book will help you push the boundaries of what you thought possible in C#.

Modernizing Legacy Applications to Microsoft Azure. Plan and execute your modernization journey seamlessly

Steve Read, Larry Mead, Bob Ellsworth

Organizations have varying circumstances, objectives, and prerequisites when contemplating a hyper-scale cloud solution transformation to a platform such as Azure. Modernizing Legacy Applications to Microsoft Azure uncovers potential scenarios and provides choices, methodologies, techniques, and prospective possibilities for transitioning from legacy applications to the Microsoft Azure environment.You’ll start by understanding the legacy systems and the main concerns regarding migration. Then, you’ll investigate why distributed architectures are compelling and the various components of the Azure platform needed during migration. After that, you’ll explore the approaches to modernizing legacy applications and the Rs of modernizing (i.e., rehost, refactor, rearchitect, and retire). You’ll also learn about integration approaches and potential pitfalls.By the end of this book, you’ll be well equipped to modernize your legacy workloads while being aware of pitfalls and best practices.

RabbitMQ Essentials. Hop straight into developing your own messaging applications by learning how to utilize RabbitMQ

David Dossot

Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 - Third Edition

Sebastian Raschka, Vahid Mirjalili

Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself.Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents.This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.

Bioinformatics with Python Cookbook. Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology - Second Edition

Tiago Antao

Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data.This book covers next-generation sequencing, genomics, metagenomics, population genetics, phylogenetics, and proteomics. You'll learn modern programming techniques to analyze large amounts of biological data. With the help of real-world examples, you'll convert, analyze, and visualize datasets using various Python tools and libraries.This book will help you get a better understanding of working with a Galaxy server, which is the most widely used bioinformatics web-based pipeline system. This updated edition also includes advanced next-generation sequencing filtering techniques. You'll also explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks such as Dask and Spark.By the end of this book, you'll be able to use and implement modern programming techniques and frameworks to deal with the ever-increasing deluge of bioinformatics data.

Microsoft Team Foundation Server 2015 Cookbook. Over 80 hands-on DevOps and ALM-focused recipes for Scrum Teams to enable the Continuous Delivery of high-quality Software.. Faster!

Tarun Arora

Team Foundation Server (TFS) allows you to manage code repositories, build processes, test infrastructure, and deploy labs. TFS supports your team, enabling you to connect, collaborate, and deliver on time. Microsoft's approach to Application Lifecycle Management (ALM) provides a flexible and agile environment that adapts to the needs of your team, removes barriers between roles, and streamlines processes.The book introduces you to creating and setting up team projects for scrum teams. You'll explore various source control repositories, branching, and merging activities, along with a demonstration of how to embed quality into every code check-in. Then, you'll discover agile project planning and management tools. Later, emphasis is given to the testing and release management features of TFS which facilitate the automation of the release pipeline in order to create potentially shippable increments. By the end of the book, you'll have learned to extend and customize TFS plugins to incorporate them into other platforms and enable teams to manage the software lifecycle effectively.

Containers for Developers Handbook. A practical guide to developing and delivering applications using software containers

Francisco Javier Ramírez Urea

Developers are changing their deployment artifacts from application binaries to container images, giving rise to the need to build container-based apps as part of their new development workflow. Managing an app’s life cycle is complex and requires effort—this book will show you how to efficiently develop, share, and execute applications.You’ll learn how to automate the build and delivery process using CI/CD tools with containers as container orchestrators manage the complexity of running cluster-wide applications, creating infrastructure abstraction layers, while your applications run with high availability, resilience, and persistence. As you advance, you’ll develop, test, and debug applications on your desktop and get them ready to run in production with optimal security standards, using deployment patterns and monitoring tools to help identify common issues. You’ll also review deployment patterns that’ll enable you to solve common deployment problems, providing high availability, scalability, and security to your applications. Finally, you’ll explore different solutions to monitor, log, and instrument your applications as per open-source community standards.By the end of this book, you’ll be able to manage your app’s life cycle by implementing CI/CD workflows using containers to automate the building and delivery of its components.

Learn Azure Synapse Data Explorer. A guide to building real-time analytics solutions to unlock log and telemetry data

Pericles (Peri) Rocha

Large volumes of data are generated daily from applications, websites, IoT devices, and other free-text, semi-structured data sources. Azure Synapse Data Explorer helps you collect, store, and analyze such data, and work with other analytical engines, such as Apache Spark, to develop advanced data science projects and maximize the value you extract from data.This book offers a comprehensive view of Azure Synapse Data Explorer, exploring not only the core scenarios of Data Explorer but also how it integrates within Azure Synapse. From data ingestion to data visualization and advanced analytics, you’ll learn to take an end-to-end approach to maximize the value of unstructured data and drive powerful insights using data science capabilities. With real-world usage scenarios, you’ll discover how to identify key projects where Azure Synapse Data Explorer can help you achieve your business goals. Throughout the chapters, you'll also find out how to manage big data as part of a software as a service (SaaS) platform, as well as tune, secure, and serve data to end users.By the end of this book, you’ll have mastered the big data life cycle and you'll be able to implement advanced analytical scenarios from raw telemetry and log data.

Hands-On Exploratory Data Analysis with R. Become an expert in exploratory data analysis using R packages

Radhika Datar, Harish Garg

Hands-On Exploratory Data Analysis with R will help you build a strong foundation in data analysis and get well-versed with elementary ways to analyze data. You will learn how to understand your data and summarize its characteristics. You'll also study the structure of your data, and you'll explore graphical and numerical techniques using the R language.This book covers the entire exploratory data analysis (EDA) process—data collection, generating statistics, distribution, and invalidating the hypothesis. As you progress through the book, you will set up a data analysis environment with tools such as ggplot2, knitr, and R Markdown, using DOE Scatter Plot and SML2010 for multifactor, optimization, and regression data problems.By the end of this book, you will be able to successfully carry out a preliminary investigation on any dataset, uncover hidden insights, and present your results in a business context.

Building AI Applications with OpenAI APIs. Leverage ChatGPT, Whisper, and DALL-E APIs to build 10 innovative AI projects - Second Edition

Martin Yanev

Unlock the power of AI in your applications with ChatGPT with this practical guide that shows you how to seamlessly integrate OpenAI APIs into your projects, enabling you to navigate complex APIs and ensure seamless functionality with ease.This new edition is updated with key topics such as OpenAI Embeddings, which’ll help you understand the semantic relationships between words and phrases. You’ll find out how to use ChatGPT, Whisper, and DALL-E APIs through 10 AI projects using the latest OpenAI models, GPT-3.5, and GPT-4, with Visual Studio Code as the IDE. Within these projects, you’ll integrate ChatGPT with frameworks and tools such as Flask, Django, Microsoft Office APIs, and PyQt. You’ll get to grips with NLP tasks, build a ChatGPT clone, and create an AI code bug-fixing SaaS app. The chapters will also take you through speech recognition, text-to-speech capabilities, language translation, generating email replies, creating PowerPoint presentations, and fine-tuning ChatGPT, along with adding payment methods by integrating the ChatGPT API with Stripe.By the end of this book, you’ll be able to develop, deploy, and monetize your own groundbreaking applications by harnessing the full potential of ChatGPT APIs.

Oracle Cloud Infrastructure for Solutions Architects. A practical guide to effectively designing enterprise-grade solutions with OCI services

Prasenjit Sarkar, Guillermo Ruiz

Oracle Cloud Infrastructure (OCI) is a set of complementary cloud services that enables you to build and run a wide range of applications and services in a highly available hosted environment. This book is a fast-paced practical guide that will help you develop the capabilities to leverage OCI services and effectively manage your cloud infrastructure.Oracle Cloud Infrastructure for Solutions Architects begins by helping you get to grips with the fundamentals of Oracle Cloud Infrastructure, and moves on to cover the building blocks of the layers of Infrastructure as a Service (IaaS), such as Identity and Access Management (IAM), compute, storage, network, and database. As you advance, you’ll delve into the development aspects of OCI, where you’ll learn to build cloud-native applications and perform operations on OCI resources as well as use the CLI, API, and SDK. Finally, you’ll explore the capabilities of building an Oracle hybrid cloud infrastructure.By the end of this book, you’ll have learned how to leverage the OCI and gained a solid understanding of the persona of an architect as well as a developer’s perspective.

Instant Heat Maps in R How-to. Learn how to design heat maps in R to enhance your data analysis

Sebastian Raschka

R has grown rapidly over the years to become one of the most versatile and valuable tools for data analysis and graphing. One of its many useful features is the heat map representation of numerical data, which is an invaluable tool to discover patterns in data quickly and efficiently.Instant Heat Maps in R How-to provides you with practical recipes to create heat maps of all difficulty levels by yourself right from the start. At the end of each recipe, you will find an in-depth analysis that will equip you with everything you need to know to frame the code to your own needs.Instant Heat Maps in R will present you with all the different heat map plotting functions that exist in R. You will start by creating simple heat maps before moving on to learn how to add more features to them. While you advance step-by-step through the well-connected recipes, you will find out which tool suits the given situation best. You will learn how to read data from popular file formats and how to format the data to create heat maps as well as the ways to export them for presentation.

C# Interview Guide. Boost your confidence with answers to hundreds of secret interview questions

Konstantin Semenenko

If you're gearing up for technical interviews by enhancing your programming skills and aiming for a successful career in C# programming and software development, the C# Interview Guide is your key to interview success.Designed to equip you with essential skills for excelling in technical interviews, this guide spans a broad spectrum, covering fundamental C# programming concepts to intricate technical details. As you progress, you'll develop proficiency in crafting compelling resumes, adeptly answering behavioral questions, and navigating the complexities of salary negotiations and job evaluations. What sets this book apart is its coverage, extending beyond technical know-how and incorporating real-world experiences and expert insights from industry professionals. This comprehensive approach, coupled with guidance on overcoming challenges, ranging from interview preparation to post-interview strategies, makes this guide an invaluable resource for those aspiring to advance in their C# programming careers.By the end of this guide, you’ll emerge with a solid understanding of C# programming, advanced technical interview skills, and the ability to apply industry best practices.

Accelerate Model Training with PyTorch 2.X. Build more accurate models by boosting the model training process

Maicon Melo Alves, Lúcia Maria de Assumpçao Drummond

This book, written by an HPC expert with over 25 years of experience, guides you through enhancing model training performance using PyTorch. Here you’ll learn how model complexity impacts training time and discover performance tuning levels to expedite the process, as well as utilize PyTorch features, specialized libraries, and efficient data pipelines to optimize training on CPUs and accelerators. You’ll also reduce model complexity, adopt mixed precision, and harness the power of multicore systems and multi-GPU environments for distributed training. By the end, you'll be equipped with techniques and strategies to speed up training and focus on building stunning models.