Programowanie
Yuki Hattori
Git and GitHub are absolutely crucial for DevOps, playing a multifaceted role in streamlining the software development lifecycle and enabling smoother collaboration between development and operations teams.DevOps Unleashed with Git and GitHub enables you to harness the power of Git and GitHub to streamline workflows, drive collaboration, and fuel innovation. Authored by an expert from GitHub, the book starts by guiding you through Git fundamentals and delving into DevOps and the developer experience. As you progress, you’ll understand how to leverage GitHub's collaboration and automation features, and even use GitHub Copilot for enhanced productivity. You'll also learn how to bridge the DevOps gap, maintain code quality, and implement robust security measures. Additionally, hands-on exercises will equip you to elevate your developer experience, foster teamwork, and drive innovation at the speed of DevOps.By the end of this DevOps book, you’ll have mastered the Git fundamentals, conquered collaboration challenges, and unleashed the power of GitHub as you transform your DevOps workflows.
DevOps w praktyce. Wdrażanie narzędzi Terraform, Azure DevOps, Kubernetes i Jenkins. Wydanie II
Mikael Krief
DevOps jest doskonałym rozwiązaniem dla każdej organizacji, która musi zwiększyć przepływ pracy technicznej przy zachowaniu odpowiedniej jakości i niezawodności. Pozwala też na uzyskanie trwałości projektów i wzorową współpracę programistów z zespołem operacyjnym. Wiele organizacji decyduje się na wdrożenie praktyk DevOps. Pomyślne przeprowadzenie tego procesu wymaga przygotowań, w ich ramach zaś kluczowe znaczenie ma wybór odpowiednich do potrzeb wzorców i narzędzi. To drugie, zaktualizowane i uzupełnione wydanie książki poświęconej wdrażaniu najlepszych praktyk DevOps przy użyciu nowoczesnych narzędzi. Przedstawiono w niej informacje o kulturze DevOps, opisano różne narzędzia i techniki stosowane do jej wdrażania, takie jak IaC, potoki Git i CI/CD, a także automatyzację testów i analizę kodu. Sporo miejsca poświęcono konteneryzacji aplikacji za pomocą Dockera i platformy Kubernetes. Znajdziemy tutaj również kwestię skracania przestojów podczas wdrażania oprogramowania i omówienie możliwości stosowania praktyk DevOps w projektach open source. Warto zwrócić uwagę na ostatni rozdział, w którym pokazano zasady wdrażania niektórych praktyk DevOps w całym cyklu życia projektów. Najciekawsze zagadnienia: infrastruktura jako kod (IaC) udostępnianie i konfigurowanie infrastruktury chmurowej tworzenie lokalnego środowiska programistycznego i konteneryzowanie aplikacji zastosowanie DevSecOps do testowania zgodności i zabezpieczania infrastruktury potoki DevOps CI/CD i zielononiebieskie praktyki wdrażania praktyki DevOps dla projektów open source Potrzebujesz efektywności? Praktykuj DevOps i wygrywaj na rynku!
DevOps with Kubernetes. Accelerating software delivery with container orchestrators
Hideto Saito, Hui-Chuan Chloe Lee, Cheng-Yang Wu
Containerization is said to be the best way to implement DevOps. Google developed Kubernetes, which orchestrates containers efficiently and is considered the frontrunner in container orchestration. Kubernetes is an orchestrator that creates and manages your containers on clusters of servers. This book will guide you from simply deploying a container to administrate a Kubernetes cluster, and then you will learn how to do monitoring, logging, and continuous deployment in DevOps. The initial stages of the book will introduce the fundamental DevOps and the concept of containers. It will move on to how to containerize applications and deploy them into. The book will then introducenetworks in Kubernetes. We then move on to advanced DevOps skills such as monitoring, logging, and continuous deployment in Kubernetes. It will proceed to introduce permission control for Kubernetes resources via attribute-based access control and role-based access control. The final stage of the book will cover deploying and managing yourcontainer clusters on the popular public cloud Amazon Web Services and GoogleCloud Platform. At the end of the book, other orchestration frameworks, such asDocker Swarm mode, Amazon ECS, and Apache Mesos will be discussed.
DevOps with Kubernetes. Accelerating software delivery with container orchestrators - Second Edition
Hideto Saito, Hui-Chuan Chloe Lee, Cheng-Yang Wu
Kubernetes has been widely adopted across public clouds and on-premise data centers. As we're living in an era of microservices, knowing how to use and manage Kubernetes is an essential skill for everyone in the IT industry.This book is a guide to everything you need to know about Kubernetes—from simply deploying a container to administrating Kubernetes clusters wisely. You'll learn about DevOps fundamentals, as well as deploying a monolithic application as microservices and using Kubernetes to orchestrate them. You will then gain an insight into the Kubernetes network, extensions, authentication and authorization. With the DevOps spirit in mind, you'll learn how to allocate resources to your application and prepare to scale them efficiently. Knowing the status and activity of the application and clusters is crucial, so we’ll learn about monitoring and logging in Kubernetes. Having an improved ability to observe your services means that you will be able to build a continuous delivery pipeline with confidence. At the end of the book, you'll learn how to run managed Kubernetes services on three top cloud providers: Google Cloud Platform, Amazon Web Services, and Microsoft Azure.
Gerard Johansen
An understanding of how digital forensics integrates with the overall response to cybersecurity incidents is key to securing your organization's infrastructure from attacks. This updated second edition will help you perform cutting-edge digital forensic activities and incident response.After focusing on the fundamentals of incident response that are critical to any information security team, you’ll move on to exploring the incident response framework. From understanding its importance to creating a swift and effective response to security incidents, the book will guide you with the help of useful examples. You’ll later get up to speed with digital forensic techniques, from acquiring evidence and examining volatile memory through to hard drive examination and network-based evidence. As you progress, you’ll discover the role that threat intelligence plays in the incident response process. You’ll also learn how to prepare an incident response report that documents the findings of your analysis. Finally, in addition to various incident response activities, the book will address malware analysis, and demonstrate how you can proactively use your digital forensic skills in threat hunting.By the end of this book, you’ll have learned how to efficiently investigate and report unwanted security breaches and incidents in your organization.
Digitalizacja w systemach automatyki SIMATIC. Teoria, przykłady, ćwiczenia
Artur Nowocień
Z pamięci papieru do pamięci komputera Współczesnym przemysłem rządzi... informatyka. Ta dziedzina stale się rozwija i zagarnia pod swoje skrzydła kolejne sektory ― od produkcji, przez logistykę i księgowość, po dystrybucję i sprzedaż. Tyle teorii. W praktyce zaś często się okazuje, że podczas gdy otoczenie biznesowe i technologie pędzą naprzód, systemy stosowane w przemyśle zostają nieco z tyłu. Głównym celem, jaki przyświeca autorowi tej publikacji, skierowanej przede wszystkim do automatyków i programistów sterowników PLC, jest odczarowanie pojęcia digitalizacji i udowodnienie, że technologie, które się w nie wpisują, nie są wcale zarezerwowane dla specjalistów IT. W rzeczywistości wszyscy stosujemy je na co dzień, tylko w okrojonej formie. W książce poruszane są takie tematy jak podstawowe założenia czwartej rewolucji przemysłowej, cyberbezpieczeństwo, mechanizmy informatyczne implementowane na poziomie konwencjonalnych urządzeń automatyki, internet rzeczy, chmury obliczeniowe, systemy brzegowe, a także technologie, które wyznaczają przyszłość automatyki przemysłowej. Każdy rozdział składa się z dwóch części: teoretycznej, zawierającej omówienie podstawowych zagadnień, które należy przyswoić, aby móc świadomie korzystać z danej technologii, i praktycznej, prezentującej jej implementację przy użyciu powszechnie stosowanych komponentów automatyki.
Digitalizacja w systemach automatyki SIMATIC. Teoria, przykłady, ćwiczenia. Wydanie II
Artur Nowocień
Z pamięci papieru do pamięci komputera Współczesnym przemysłem rządzi... informatyka. Ta dziedzina stale się rozwija i zagarnia pod swoje skrzydła kolejne sektory ― od produkcji, przez logistykę i księgowość, po dystrybucję i sprzedaż. Tyle teorii. W praktyce zaś często się okazuje, że podczas gdy otoczenie biznesowe i technologie pędzą naprzód, systemy stosowane w przemyśle zostają nieco z tyłu. Głównym celem, jaki przyświeca autorowi tej publikacji, skierowanej przede wszystkim do automatyków i programistów sterowników PLC, jest odczarowanie pojęcia digitalizacji i udowodnienie, że technologie, które się w nie wpisują, nie są wcale zarezerwowane dla specjalistów IT. W rzeczywistości wszyscy stosujemy je na co dzień, tylko w okrojonej formie. W książce poruszane są takie tematy jak podstawowe założenia czwartej rewolucji przemysłowej, cyberbezpieczeństwo, mechanizmy informatyczne implementowane na poziomie konwencjonalnych urządzeń automatyki, internet rzeczy, chmury obliczeniowe, systemy brzegowe, a także technologie, które wyznaczają przyszłość automatyki przemysłowej. Każdy rozdział składa się z dwóch części: teoretycznej, zawierającej omówienie podstawowych zagadnień, które należy przyswoić, aby móc świadomie korzystać z danej technologii, i praktycznej, prezentującej jej implementację przy użyciu powszechnie stosowanych komponentów automatyki.
Abhilash G B
This is a step-by-step guide that will help you understand disaster recovery using VMware vSphere Replication 5.5 and VMware vCenter Site Recovery Manager (SRM) 5.5. The topics and configuration procedures are accompanied with relevant screenshots, flowcharts, and logical diagrams that makes grasping the concepts easier. This book is a guide for anyone who is keen on using vSphere Replication or vCenter Site Recovery Manager as a disaster recovery solution. This is an excellent handbook for solution architects, administrators, on-field engineers, and support professionals. Although the book assumes that the reader has some basic knowledge of data center virtualization using VMware vSphere, it can still be a very good reference for anyone who is new to virtualization.
Distributed Computing in Java 9. Leverage the latest features of Java 9 for distributed computing
Raja Malleswara Rao Malleswara Rao Pattamsetti
Distributed computing is the concept with which a bigger computation process is accomplished by splitting it into multiple smaller logical activities and performed by diverse systems, resulting in maximized performance in lower infrastructure investment. This book will teach you how to improve the performance of traditional applications through the usage of parallelism and optimized resource utilization in Java 9.After a brief introduction to the fundamentals of distributed and parallel computing, the book moves on to explain different ways of communicating with remote systems/objects in a distributed architecture. You will learn about asynchronous messaging with enterprise integration and related patterns, and how to handle large amount of data using HPC and implement distributed computing for databases. Moving on, it explains how to deploy distributed applications on different cloud platforms and self-contained application development. You will also learn about big data technologies and understand how they contribute to distributed computing. The book concludes with the detailed coverage of testing, debugging, troubleshooting, and security aspects of distributed applications so the programs you build are robust, efficient, and secure.
Distributed Computing in Java 9. Leverage the latest features of Java 9 for distributed computing
Raja Malleswara Rao Malleswara Rao Pattamsetti
Distributed computing is the concept with which a bigger computation process is accomplished by splitting it into multiple smaller logical activities and performed by diverse systems, resulting in maximized performance in lower infrastructure investment. This book will teach you how to improve the performance of traditional applications through the usage of parallelism and optimized resource utilization in Java 9.After a brief introduction to the fundamentals of distributed and parallel computing, the book moves on to explain different ways of communicating with remote systems/objects in a distributed architecture. You will learn about asynchronous messaging with enterprise integration and related patterns, and how to handle large amount of data using HPC and implement distributed computing for databases. Moving on, it explains how to deploy distributed applications on different cloud platforms and self-contained application development. You will also learn about big data technologies and understand how they contribute to distributed computing. The book concludes with the detailed coverage of testing, debugging, troubleshooting, and security aspects of distributed applications so the programs you build are robust, efficient, and secure.
Distributed Computing with Go. Practical concurrency and parallelism for Go applications
V.N. Nikhil Anurag, Jinzhu Zhang, Pankaj Khairnar
Distributed Computing with Go gives developers with a good idea how basic Go development works the tools to fulfill the true potential of Golang development in a world of concurrent web and cloud applications. Nikhil starts out by setting up a professional Go development environment. Then you’ll learn the basic concepts and practices of Golang concurrent and parallel development. You’ll find out in the new few chapters how to balance resources and data with REST and standard web approaches while keeping concurrency in mind. Most Go applications these days will run in a data center or on the cloud, which is a condition upon which the next chapter depends. There, you’ll expand your skills considerably by writing a distributed document indexing system during the next two chapters. This system has to balance a large corpus of documents with considerable analytical demands. Another use case is the way in which a web application written in Go can be consciously redesigned to take distributed features into account. The chapter is rather interesting for Go developers who have to migrate existing Go applications to computationally and memory-intensive environments. The final chapter relates to the rather onerous task of testing parallel and distributed applications, something that is not usually taught in standard computer science curricula.
Francesco Pierfederici
CPU-intensive data processing tasks have become crucial considering the complexity of the various big data applications that are used today. Reducing the CPU utilization per process is very important to improve the overall speed of applications.This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more.
Distributed Data Systems with Azure Databricks. Create, deploy, and manage enterprise data pipelines
Alan Bernardo Palacio
Microsoft Azure Databricks helps you to harness the power of distributed computing and apply it to create robust data pipelines, along with training and deploying machine learning and deep learning models. Databricks' advanced features enable developers to process, transform, and explore data. Distributed Data Systems with Azure Databricks will help you to put your knowledge of Databricks to work to create big data pipelines. The book provides a hands-on approach to implementing Azure Databricks and its associated methodologies that will make you productive in no time. Complete with detailed explanations of essential concepts, practical examples, and self-assessment questions, you’ll begin with a quick introduction to Databricks core functionalities, before performing distributed model training and inference using TensorFlow and Spark MLlib. As you advance, you’ll explore MLflow Model Serving on Azure Databricks and implement distributed training pipelines using HorovodRunner in Databricks. Finally, you’ll discover how to transform, use, and obtain insights from massive amounts of data to train predictive models and create entire fully working data pipelines. By the end of this MS Azure book, you’ll have gained a solid understanding of how to work with Databricks to create and manage an entire big data pipeline.
Distributed Data Systems with Azure Databricks. Create, deploy, and manage enterprise data pipelines
Alan Bernardo Palacio
Microsoft Azure Databricks helps you to harness the power of distributed computing and apply it to create robust data pipelines, along with training and deploying machine learning and deep learning models. Databricks' advanced features enable developers to process, transform, and explore data. Distributed Data Systems with Azure Databricks will help you to put your knowledge of Databricks to work to create big data pipelines. The book provides a hands-on approach to implementing Azure Databricks and its associated methodologies that will make you productive in no time. Complete with detailed explanations of essential concepts, practical examples, and self-assessment questions, you’ll begin with a quick introduction to Databricks core functionalities, before performing distributed model training and inference using TensorFlow and Spark MLlib. As you advance, you’ll explore MLflow Model Serving on Azure Databricks and implement distributed training pipelines using HorovodRunner in Databricks. Finally, you’ll discover how to transform, use, and obtain insights from massive amounts of data to train predictive models and create entire fully working data pipelines. By the end of this MS Azure book, you’ll have gained a solid understanding of how to work with Databricks to create and manage an entire big data pipeline.
Guanhua Wang
Reducing time cost in machine learning leads to a shorter waiting time for model training and a faster model updating cycle. Distributed machine learning enables machine learning practitioners to shorten model training and inference time by orders of magnitude. With the help of this practical guide, you'll be able to put your Python development knowledge to work to get up and running with the implementation of distributed machine learning, including multi-node machine learning systems, in no time. You'll begin by exploring how distributed systems work in the machine learning area and how distributed machine learning is applied to state-of-the-art deep learning models. As you advance, you'll see how to use distributed systems to enhance machine learning model training and serving speed. You'll also get to grips with applying data parallel and model parallel approaches before optimizing the in-parallel model training and serving pipeline in local clusters or cloud environments. By the end of this book, you'll have gained the knowledge and skills needed to build and deploy an efficient data processing pipeline for machine learning model training and inference in a distributed manner.
Bhupesh Guptha Muthiyalu, Suneel Kumar Kunani
Building distributed applications in this modern era can be a tedious task as customers expect high availability, high performance, and improved resilience. With the help of this book, you'll discover how you can harness the power of Microsoft Orleans to build impressive distributed applications.Distributed .NET with Microsoft Orleans will demonstrate how to leverage Orleans to build highly scalable distributed applications step by step in the least possible time and with minimum effort. You'll explore some of the key concepts of Microsoft Orleans, including the Orleans programming model, runtime, virtual actors, hosting, and deployment. As you advance, you'll become well-versed with important Orleans assets such as grains, silos, timers, and persistence. Throughout the book, you'll create a distributed application by adding key components to the application as you progress through each chapter and explore them in detail.By the end of this book, you'll have developed the confidence and skills required to build distributed applications using Microsoft Orleans and deploy them in Microsoft Azure.
Bhupesh Guptha Muthiyalu, Suneel Kumar Kunani
Building distributed applications in this modern era can be a tedious task as customers expect high availability, high performance, and improved resilience. With the help of this book, you'll discover how you can harness the power of Microsoft Orleans to build impressive distributed applications.Distributed .NET with Microsoft Orleans will demonstrate how to leverage Orleans to build highly scalable distributed applications step by step in the least possible time and with minimum effort. You'll explore some of the key concepts of Microsoft Orleans, including the Orleans programming model, runtime, virtual actors, hosting, and deployment. As you advance, you'll become well-versed with important Orleans assets such as grains, silos, timers, and persistence. Throughout the book, you'll create a distributed application by adding key components to the application as you progress through each chapter and explore them in detail.By the end of this book, you'll have developed the confidence and skills required to build distributed applications using Microsoft Orleans and deploy them in Microsoft Azure.
Bhupesh Guptha Muthiyalu, Suneel Kumar Kunani
Building distributed applications in this modern era can be a tedious task as customers expect high availability, high performance, and improved resilience. With the help of this book, you'll discover how you can harness the power of Microsoft Orleans to build impressive distributed applications.Distributed .NET with Microsoft Orleans will demonstrate how to leverage Orleans to build highly scalable distributed applications step by step in the least possible time and with minimum effort. You'll explore some of the key concepts of Microsoft Orleans, including the Orleans programming model, runtime, virtual actors, hosting, and deployment. As you advance, you'll become well-versed with important Orleans assets such as grains, silos, timers, and persistence. Throughout the book, you'll create a distributed application by adding key components to the application as you progress through each chapter and explore them in detail.By the end of this book, you'll have developed the confidence and skills required to build distributed applications using Microsoft Orleans and deploy them in Microsoft Azure.
Scott Newman
This book is designed for readers who learn by doing and employs many examples and screenshots to let the reader dig in and start coding. This book isn't designed to be a reference; instead it has a practical, example-driven approach that teaches you by following along with the examples in the chapters. When you have completed this book, you will fully understand how the template system works, how to extend it when you have specialized needs, and how to optimize the performance and usability of your content. This book is for web developers and template authors who want to fully understand and utilize the Django template system. The reader should have completed the introductory tutorials on the Django project's website and some experience with the framework will be very helpful. Basic knowledge of Python and HTML is assumed.
Django 2 by Example. Build powerful and reliable Python web applications from scratch
Antonio Melé
If you want to learn the entire process of developing professional web applications with Django 2, then this book is for you. You will walk through the creation of four professional Django 2 projects, teaching you how to solve common problems and implement best practices.You will learn how to build a blog application, a social image bookmarking website, an online shop and an e-learning platform. The book will teach you how to enhance your applications with AJAX, create RESTful APIs and set up a production environment for your Django 2 projects. The book walks you through the creation of real-world applications, solving common problems, and implementing best practices. By the end of this book, you will have a deep understanding of Django 2 and how to build advanced web applications.