Petri nets are a popular and powerful formal model for the analysis and modelling of concurrent systems, and a rich theory has developed around them. Petri nets are taught to undergraduates, and also used by industrial practitioners. This book focuses on a particular class of petri nets, free choice petri nets, which play a central role in the theory. The text is very clearly organised, with every notion carefully explained and every result proved. Clear exposition is given for place invariants, siphons, traps and many other important analysis techniques. The material is organised along the lines of a course book, and each chapter contains numerous exercises, making this book ideal for graduate students and research workers alike.

The foundations of parallel computation, especially the efficiency of computation, are the concern of this book. Distinguished international researchers have contributed fifteen chapters which together form a coherent stream taking the reader who has little prior knowledge of the field to a position of being familiar with leading edge issues. The book may also function as a source of teaching material and reference for researchers. The first part is devoted to the Parallel Random Access Machine (P-RAM) model of parallel computation. The initial chapters justify and define the model, which is then used for the development of algorithm design in a variety of application areas such as deterministic algorithms, randomisation and algorithm resilience. The second part deals with distributed memory models of computation. The question of efficiently implementing P-RAM algorithms within these models is addressed as are the immensely interesting prospects for general purpose parallel computation.

Leverage OpenTelemetry's API, libraries, tools and the collector to produce and collect telemetry along with using open-source tools to analyze distributed traces, check metrics and logs, and gain insights into application health Key Features Get to grips with OpenTelemetry, an open-source cloud-native software observability standard Use vendor-neutral tools to instrument applications to produce better telemetry and improve observability Understand how telemetry data can be correlated and interpreted to understand distributed systems Book DescriptionCloud-Native Observability with OpenTelemetry is a guide to helping you look for answers to questions about your applications. This book teaches you how to produce telemetry from your applications using an open standard to retain control of data. OpenTelemetry provides the tools necessary for you to gain visibility into the performance of your services. It allows you to instrument your application code through vendor-neutral APIs, libraries and tools. By reading Cloud-Native Observability with OpenTelemetry, you'll learn about the concepts and signals of OpenTelemetry - traces, metrics, and logs. You'll practice producing telemetry for these signals by configuring and instrumenting a distributed cloud-native application using the OpenTelemetry API. The book also guides you through deploying the collector, as well as telemetry backends necessary to help you understand what to do with the data once it's emitted. You'll look at various examples of how to identify application performance issues through telemetry. By analyzing telemetry, you'll also be able to better understand how an observable application can improve the software development life cycle. By the end of this book, you'll be well-versed with OpenTelemetry, be able to instrument services using the OpenTelemetry API to produce distributed traces, metrics and logs, and more. What you will learn Understand the core concepts of OpenTelemetry Explore concepts in distributed tracing, metrics, and logging Discover the APIs and SDKs necessary to instrument an application using OpenTelemetry Explore what auto-instrumentation is and how it can help accelerate application instrumentation Configure and deploy the OpenTelemetry Collector Get to grips with how different open-source backends can be used to analyze telemetry data Understand how to correlate telemetry in common scenarios to get to the root cause of a problem Who this book is forThis book is for software engineers, library authors, and systems operators looking to better understand their infrastructure, services and applications by leveraging telemetry data like never before. Working knowledge of Python programming is assumed for the example applications that you'll be building and instrumenting using the OpenTelemetry API and SDK. Some familiarity with Go programming, Linux, and Docker is preferable to help you set up additional components in various examples throughout the book.

Solve the complexity of running a business in a multi-cloud environment with practical guidelines backed by industry experience Key Features * Explore the benefits of the major cloud providers to make better informed decisions * Accelerate digital transformation with multi-cloud adoption, including the use of PaaS and SaaS concepts * Get the best out of multi-cloud by exploring relevant use cases for data platforms and IoT Book Description Most enterprises adopt multi-cloud with the intention of accelerating digital transformation, but moving data and applications to public clouds and implementing Platform as a Service (PaaS) and Software as a Service (SaaS) solutions are challenging. One of the biggest challenges is deciding what parts of which services are the most useful to help the company thrive. Through this book, you'll learn how to choose the most apt cloud service and how to manage operations, cost, and security, all while learning how to overcome the complexities associated with multi-cloud adoption via use cases (IoT, data mining, Web3, financial management, and more). This new edition is focused on helping you stay in control of your cloud environments by using the concepts of BaseOps, FinOps, and DevSecOps. You'll learn how to develop, release, and manage products and services in the major public clouds Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP), whilst optimizing costs and maximizing security using the various tools and services that these cloud providers offer. By the end of this book, you will have become familiar with the complexities associated with running a business in a multi-cloud environment and identified ways to solve these complexities in the domains of operations, financial management, and security. What you will learn * Learn how to choose the right cloud platform via various use cases * Understand the concepts associated with multi-cloud, including IaC, SaaS, PaaS, and CaC * Use the techniques and tools offered by Azure, AWS, and GCP to integrate security * Learn about enterprise architecture, value streams, and well-architected frameworks of Azure, AWS, and GCP * Use FinOps to define cost models and create transparency in cloud costs with showback and chargeback * Improve security with the DevSecOps maturity model * Explore the concepts of AIOps and GreenOps Who This Book Is For Cloud architects, solutions architects, enterprise architects, and cloud consultants will find this book valuable. Basic knowledge of any one of the major public clouds (Azure, AWS, or GCP) will be helpful.

As spoken natural language dialog systems technology continues to make great strides, numerous issues regarding dialog processing still need to be resolved. This book presents an exciting new dialog processing architecture that allows for a number of behaviors required for effective human-machine interactions, including: problem-solving to help the user carry out a task, coherent subdialog movement during the problem-solving process, user model usage, expectation usage for contextual interpretation and error correction, and variable initiative behavior for interacting with users of differing expertise. The book also details how different dialog problems in processing can be handled simultaneously, and provides instructions and in-depth result from pertinent experiments. Researchers and professionals in natural language systems will find this important new book an invaluable addition to their libraries.

Deploy, configure, administer, and run Microsoft Azure Stack Hub Key Features Understand the topics required for the Microsoft Azure AZ-600 exam Configure and provide services from Microsoft Azure Stack Hub Implement data center integration with Microsoft Azure Stack Hub Book DescriptionAzure Stack Hub is the on-premise offering from Microsoft, which provides Azure Cloud services within a customer's own data center. It provides consistent processes between on-site and the cloud, allowing developers to test locally and deploy to the cloud in exactly the same manner. Azure Stack Hub Demystified provides complete coverage of deploying, configuring, administrating, and running Microsoft Azure Stack Hub efficiently. Firstly, you will learn how to deploy Azure Stack Hub within an organization. As you progress, you'll understand configuration and the different services provided by the platform. The book also focuses on the underlying architecture and connectivity options for the modern data center. Later, you will understand various approaches to DevOps and their implementation, and learn key topics for the AZ-600 exam. By the end of this Azure book, you will have a thorough understanding of Azure Stack Hub and the services that are provided by the platform, along with the confidence and information you need to be able to pass the AZ-600 exam. What you will learn Understand the architecture of Azure Stack Hub Get up to speed with the management and administration of Azure Stack Hub Explore how to administer virtual networking within your Azure Stack Become well versed in using the Azure Stack Hub support model and updating Azure Stack Hub Understand how licensing and billing is done with Azure Stack Hub Discover the tools that can be used to implement security within Azure Stack Hub Focus on how DevOps practices can be incorporated with Azure Stack Hub Who this book is forIf you are an Azure Administrator and Azure Stack Hub Operator who provides or is looking to provide cloud services to end users or customers within their own data center, then this book is for you. This book will also be beneficial to those who are preparing for Exam AZ-600: Configuring and Operating a Hybrid Cloud with Microsoft Azure Stack Hub.

Explore different aspects of building modular microservices such as development, testing, maintenance, and deployment using the Micronaut framework Key Features Learn how to build scalable, fast, and resilient microservices with this concise guide Explore the many advantages of using reflection-free, compile-time dependency injections and aspect-oriented programming Build cloud-native applications easily with the Micronaut framework Book DescriptionThe open source Micronaut (R) framework is a JVM-based toolkit designed to create microservices quickly and easily. This book will help full-stack and Java developers build modular, high-performing, and reactive microservice-based apps using the Micronaut framework. You'll start by building microservices and learning about the core components, such as ahead-of-time compilation, reflection-less dependency injection, and reactive baked-in HTTP clients and servers. Next, you will work on a real-time microservice application and learn how to integrate Micronaut projects with different kinds of relational and non-relational databases. You'll also learn how to employ different security mechanisms to safeguard your microservices and integrate microservices using event-driven architecture in the Apache Kafka ecosystem. As you advance, you'll get to grips with automated testing and popular testing tools. The book will help you understand how you can easily handle microservice concerns in Micronaut projects, such as service discovery, API documentation, distributed configuration management, fallbacks, and circuit breakers. Finally, you'll explore the deployment and maintenance aspects of microservices and get up to speed with the Internet of Things (IoT) using the Framework. By the end of this book, you'll be able to build, test, deploy, and maintain your own microservice apps using the framework. What you will learn Understand why the Micronaut framework is best suited for building microservices Build web endpoints and services in the Micronaut framework Safeguard microservices using Session, JWT, and OAuth in Micronaut projects Get to grips with event-driven architecture in Micronaut applications Discover how to automate testing at various levels using built-in tools and testing frameworks Deploy your microservices to containers and cloud platforms Become well-versed with distributed logging, tracing, and monitoring in Micronaut projects Get hands-on with the IoT using Alexa and the Micronaut framework Who this book is forThis book is for developers who have been building microservices on traditional frameworks such as Spring Boot and are looking for a faster alternative. Intermediate-level knowledge of Java programming and implementing web services development in Java is required.

In recent years, most applications deal with constraint decision-making systems as problems are based on imprecise information and parameters. It is difficult to understand the nature of data based on applications and it requires a specific model for understanding the nature of the system. Further research on constraint decision-making systems in engineering is required. Constraint Decision-Making Systems in Engineering derives and explores several types of constraint decisions in engineering and focuses on new and innovative conclusions based on problems, robust and efficient systems, and linear and non-linear applications. Covering topics such as fault detection, data mining techniques, and knowledge-based management, this premier reference source is an essential resource for engineers, managers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

Enhance your applications' performance using best practices for benchmarking, application profiling, asynchronous programming, designing responsive UIs, gRPC communication, and distributed applications Key Features Make the best use of performance enhancements in C# 10.0 and .NET 6 Boost application performance by identifying hardware bottlenecks and common performance pitfalls Get to grips with best practices and techniques for improving the scalability of distributed systems Book DescriptionWriting high-performance code while building an application is crucial, and over the years, Microsoft has focused on delivering various performance-related improvements within the .NET ecosystem. This book will help you understand the aspects involved in designing responsive, resilient, and high-performance applications with the new version of C# and .NET. You will start by understanding the foundation of high-performance code and the latest performance-related improvements in C# 10.0 and .NET 6. Next, you'll learn how to use tracing and diagnostics to track down performance issues and the cause of memory leaks. The chapters that follow then show you how to enhance the performance of your networked applications and various ways to improve directory tasks, file tasks, and more. Later, you'll go on to improve data querying performance and write responsive user interfaces. You'll also discover how you can use cloud providers such as Microsoft Azure to build scalable distributed solutions. Finally, you'll explore various ways to process code synchronously, asynchronously, and in parallel to reduce the time it takes to process a series of tasks. By the end of this C# programming book, you'll have the confidence you need to build highly resilient, high-performance applications that meet your customer's demands. What you will learn Use correct types and collections to enhance application performance Profile, benchmark, and identify performance issues with the codebase Explore how to best perform queries on LINQ to improve an application's performance Effectively utilize a number of CPUs and cores through asynchronous programming Build responsive user interfaces with WinForms, WPF, MAUI, and WinUI Benchmark ADO.NET, Entity Framework Core, and Dapper for data access Implement CQRS and event sourcing and build and deploy microservices Who this book is forThis book is for software engineers, professional software developers, performance engineers, and application profilers looking to improve the speed of their code or take their skills to the next level to gain a competitive advantage. You should be a proficient C# programmer who can already put the language to good use and is also comfortable using Microsoft Visual Studio 2022.

A step-by-step, comprehensive guide that includes real-world use cases to help you successfully develop and run applications and mission-critical workloads using MicroK8s Key Features An easy-to-follow guide that helps you get started with MicroK8s and other Kubernetes components Understand the key concepts and constraints for building IoT and edge architectures Get guidance on how to develop and deploy use cases and examples on IoT and edge computing platforms Book DescriptionAre you facing challenges with developing, deploying, monitoring, clustering, storing, securing, and managing Kubernetes in production environments as you're not familiar with infrastructure technologies? MicroK8s - a zero-ops, lightweight, and CNCF-compliant Kubernetes with a small footprint is the apt solution for you. This book gets you up and running with production-grade, highly available (HA) Kubernetes clusters on MicroK8s using best practices and examples based on IoT and edge computing. Beginning with an introduction to Kubernetes, MicroK8s, and IoT and edge computing architectures, this book shows you how to install, deploy sample apps, and enable add-ons (like DNS and dashboard) on the MicroK8s platform. You'll work with multi-node Kubernetes clusters on Raspberry Pi and networking plugins (such as Calico and Cilium) and implement service mesh, load balancing with MetalLB and Ingress, and AI/ML workloads on MicroK8s. You'll also understand how to secure containers, monitor infrastructure and apps with Prometheus, Grafana, and the ELK stack, manage storage replication with OpenEBS, resist component failure using a HA cluster, and more, as well as take a sneak peek into future trends. By the end of this book, you'll be able to use MicroK8 to build and implement scenarios for IoT and edge computing workloads in a production environment. What you will learn Get a holistic view of MicroK8s features using a sample application Understand IoT and edge computing and their architecture constraints Create, scale, and update HA Raspberry Pi multi-node clusters Implement AI/ML use cases with the Kubeflow platform Work with various networking plugins, and monitoring and logging tools Perform service mesh integrations using Istio and Linkerd Run serverless applications using Knative and OpenFaaS frameworks Secure your containers using Kata and strict confinement options Who this book is forThis book is for DevOps and cloud engineers, SREs, and application developers who want to implement efficient techniques for deploying their software solutions. It will also be useful for technical architects and technology leaders who are looking to adopt cloud-native technologies. A basic understanding of container-based application design and development, virtual machines, networking, databases, and programming will be helpful for using this book.

A comprehensive guide to rolling out Datadog to monitor infrastructure and applications running in both cloud and datacenter environments Key Features Learn Datadog to proactively monitor your infrastructure and cloud services Use Datadog as a platform for aggregating monitoring efforts in your organization Leverage Datadog's alerting service to implement on-call and site reliability engineering (SRE) processes Book DescriptionDatadog is an essential cloud monitoring and operational analytics tool which enables the monitoring of servers, virtual machines, containers, databases, third-party tools, and application services. IT and DevOps teams can easily leverage Datadog to monitor infrastructure and cloud services, and this book will show you how. The book starts by describing basic monitoring concepts and types of monitoring that are rolled out in a large-scale IT production engineering environment. Moving on, the book covers how standard monitoring features are implemented on the Datadog platform and how they can be rolled out in a real-world production environment. As you advance, you'll discover how Datadog is integrated with popular software components that are used to build cloud platforms. The book also provides details on how to use monitoring standards such as Java Management Extensions (JMX) and StatsD to extend the Datadog platform. Finally, you'll get to grips with monitoring fundamentals, learn how monitoring can be rolled out using Datadog proactively, and find out how to extend and customize the Datadog platform. By the end of this Datadog book, you will have gained the skills needed to monitor your cloud infrastructure and the software applications running on it using Datadog. What you will learn Understand monitoring fundamentals, including metrics, monitors, alerts, and thresholds Implement core monitoring requirements using Datadog features Explore Datadog's integration with cloud platforms and tools Extend Datadog using custom scripting and standards such as JMX and StatsD Discover how proactive monitoring can be rolled out using various Datadog features Understand how Datadog can be used to monitor microservices in both Docker and Kubernetes environments Get to grips with advanced Datadog features such as APM and Security Monitoring Who this book is forThis book is for DevOps engineers, site reliability engineers (SREs), IT Production engineers, software developers and architects, cloud engineers, system administrators, and anyone looking to monitor and visualize their infrastructure and applications with Datadog. Basic working knowledge of cloud and infrastructure is useful. Working experience of Linux distribution and some scripting knowledge is required to fully take advantage of the material provided in the book.

For several years, it has been economically and technically feasible to build parallel systems that scale from tens to hundreds of processors. By necessity tools embody knowledge of the execution environment, identifying performance bottlenecks or logical program errors in terms of application code constructs and their interaction with the execution environment. Experience comes with time, as tool developers understand the common programming idioms, the interactions of application code and the underlying hardware and software, and the user interfaces best suited for relating these interactions in intuitive ways. Simply put developing good tools takes time, experience, and substantial effort.
This book contains papers and working group summaries from discussions on software tools for parallel computer systems that explore the current situation, outline research issues, and technology transition remedies. Developers of both debugging and performance analysis tools and application developers and vendors discuss the technical and sociological problems facing the field. The goal of this book is to maximize the return from shared development so that the reader can learn from others' needs and frustrations in building and using tools on parallel systems. It covers three major research themes: tools for task and data parallel languages, techniques for real-time adaptive system control, and optimization of heterogeneous metacomputing applications.

Get to grips with Microsoft Azure cost management and gain complete, reliable, and sustainable control of your cloud spend Key Features Explore resource rightsizing and cleanup methods and their implementation Learn key resource usage optimization concepts Understand app optimization and plan for optimized and sustainable cloud native applications Book DescriptionCloud teams and ICT cost controllers working with Azure will be able to put their knowledge to work with this practical guide, introducing a process model for structured cost governance. The Road to Azure Cost Governance is a must-read if you find yourself facing the harsh reality of monthly cloud costs gradually getting out of control. Starting with how resources are created and managed, everything you need to know in order to track, display, optimize, rightsize, and clean up cloud resources will be tackled with a workflow approach that will leave the choice of operation to you (be it the Azure CLI, automation, logic apps, or even custom code). Using real-world datasets, you'll learn everything from basic cost management to modeling your cloud spend across your technical resources in a sustainable way. The book will also show you how to create a recursive optimization process that will give you full control of spending and savings, while helping you reserve budget for future cloud projects and innovation. By the end of this Azure book, you'll have a clear understanding and control of your cloud spend along with knowledge of a number of cost-saving techniques used by companies around the world, application optimization patterns, and the carbon impact of your cloud infrastructure. What you will learn Use Azure reporting, monitoring, and configurations to model your cloud resources and make costs clearer Discover resource-saving techniques and put them into practice Establish a continuous clean-up and rightsizing process Explore and implement automation to drive recurrent savings Find out how to use Azure Reservations in the best possible way Get started with building cloud native, cost-optimized applications Get to grips with implementing cost- and carbon-aware applications on Azure Who this book is forIf you're someone who deals with Azure cloud costs and has a technical background, this book will help you understand and control your cloud spending. This book is for decision-makers, cloud managers, cloud architects, cost controllers, and software solution professionals working with Microsoft cloud services in Azure and looking to build optimized solutions for their enterprise operations.

Achieve your business goals and build highly available, scalable, and secure cloud infrastructure by designing robust and cost-effective solutions as a Google Cloud Architect. Key Features Gain hands-on experience in designing and managing high-performance cloud solutions Leverage Google Cloud Platform to optimize technical and business processes using cutting-edge technologies and services Use Google Cloud Big Data, AI, and ML services to design scalable and intelligent data solutions Book DescriptionGoogle has been one of the top players in the public cloud domain thanks to its agility and performance capabilities. This book will help you design, develop, and manage robust, secure, and dynamic solutions to successfully meet your business needs. You'll learn how to plan and design network, compute, storage, and big data systems that incorporate security and compliance from the ground up. The chapters will cover simple to complex use cases for devising solutions to business problems, before focusing on how to leverage Google Cloud's Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) capabilities for designing modern no-operations platforms. Throughout this book, you'll discover how to design for scalability, resiliency, and high availability. Later, you'll find out how to use Google Cloud to design modern applications using microservices architecture, automation, and Infrastructure-as-Code (IaC) practices. The concluding chapters then demonstrate how to apply machine learning and artificial intelligence (AI) to derive insights from your data. Finally, you will discover best practices for operating and monitoring your cloud solutions, as well as performing troubleshooting and quality assurance. By the end of this Google Cloud book, you'll be able to design robust enterprise-grade solutions using Google Cloud Platform. What you will learn Get to grips with compute, storage, networking, data analytics, and pricing Discover delivery models such as IaaS, PaaS, and SaaS Explore the underlying technologies and economics of cloud computing Design for scalability, business continuity, observability, and resiliency Secure Google Cloud solutions and ensure compliance Understand operational best practices and learn how to architect a monitoring solution Gain insights into modern application design with Google Cloud Leverage big data, machine learning, and AI with Google Cloud Who this book is forThis book is for cloud architects who are responsible for designing and managing cloud solutions with GCP. You'll also find the book useful if you're a system engineer or enterprise architect looking to learn how to design solutions with Google Cloud. Moreover, cloud architects who already have experience with other cloud providers and are now beginning to work with Google Cloud will benefit from the book. Although an intermediate-level understanding of cloud computing and distributed apps is required, prior experience of working in the public and hybrid cloud domain is not mandatory.

A comprehensive guide to architecting, managing, implementing, and controlling multi-cloud environments Key Features Deliver robust multi-cloud environments and improve your business productivity Stay in control of the cost, governance, development, security, and continuous improvement of your multi-cloud solution Integrate different solutions, principles, and practices into one multi-cloud foundation Book DescriptionMulti-cloud has emerged as one of the top cloud computing trends, with businesses wanting to reduce their reliance on only one vendor. But when organizations shift to multiple cloud services without a clear strategy, they may face certain difficulties, in terms of how to stay in control, how to keep all the different components secure, and how to execute the cross-cloud development of applications. This book combines best practices from different cloud adoption frameworks to help you find solutions to these problems. With step-by-step explanations of essential concepts and practical examples, you'll begin by planning the foundation, creating the architecture, designing the governance model, and implementing tools, processes, and technologies to manage multi-cloud environments. You'll then discover how to design workload environments using different cloud propositions, understand how to optimize the use of these cloud technologies, and automate and monitor the environments. As you advance, you'll delve into multi-cloud governance, defining clear demarcation models and management processes. Finally, you'll learn about managing identities in multi-cloud: who's doing what, why, when, and where By the end of this book, you'll be able to create, implement, and manage multi-cloud architectures with confidence What you will learn Get to grips with the core functions of multiple cloud platforms Deploy, automate, and secure different cloud solutions Design network strategy and get to grips with identity and access management for multi-cloud Design a landing zone spanning multiple cloud platforms Use automation, monitoring, and management tools for multi-cloud Understand multi-cloud management with the principles of BaseOps, FinOps, SecOps, and DevOps Define multi-cloud security policies and use cloud security tools Test, integrate, deploy, and release using multi-cloud CI/CD pipelines Who this book is forThis book is for architects and lead engineers involved in architecting multi-cloud environments, with a focus on getting governance right to stay in control of developments in multi-cloud. Basic knowledge of different cloud platforms (Azure, AWS, GCP, VMWare, and OpenStack) and understanding of IT governance is necessary.

Create modern yet effective multi-platform applications by building interactive UIs following a single codebase approach to boost productivity Key Features Delve into the FireMonkey framework and explore its powerful capabilities Enhance the user experience by using various technologies included in Delphi and FMX Boost developer productivity through the cross-platform capabilities enabled by the framework Book DescriptionFireMonkey (FMX) is a cross-platform application framework that allows developers to create exciting user interfaces and deliver applications on multiple operating systems (OS). This book will help you learn visual programming with Delphi and FMX. Starting with an overview of the FMX framework, including a general discussion of the underlying philosophy and approach, you'll then move on to the fundamentals and architectural details of FMX. You'll also cover a significant comparison between Delphi and the Visual Component Library (VCL). Next, you'll focus on the main FMX components, data access/data binding, and style concepts, in addition to understanding how to deliver visually responsive UIs. To address modern application development, the book takes you through topics such as animations and effects, and provides you with a general introduction to parallel programming, specifically targeting UI-related aspects, including application responsiveness. Later, you'll explore the most important cross-platform services in the FMX framework, which are essential for delivering your application on multiple platforms while retaining the single codebase approach. Finally, you'll learn about FMX's built-in 3D functionalities. By the end of this book, you'll be familiar with the FMX framework and be able to build effective cross-platform apps. What you will learn Explore FMX's fundamental components with a brief comparison to VCL Achieve visual responsiveness through alignment capabilities and layout components Enrich the user experience with the help of transitions and visual animations Get to grips with data access and visual data binding Build exciting and responsive UIs for desktop and mobile platforms Understand the importance of responsive applications using parallel programming Create visual continuity through your applications with TFrameStand and TFormStand Explore the 3D functionalities offered by FMX Who this book is forThis book is for Delphi developers who are looking to discover the full potential of the FireMonkey framework in order to build interactive cross-platform GUI applications and achieve an optimal UI/UX. Basic familiarity with Delphi programming and the VCL will be beneficial but not mandatory.

Unlock the full potential of the Docker containerization platform with this practical guide Key Features Explore tools such as Docker Engine, Machine, Compose, and Swarm Discover how you can integrate Docker into your everyday workflows Get well-versed with Kubernetes options such as Minikube, Kind, and MicroK8s Book DescriptionDocker has been a game changer when it comes to how modern applications are deployed and created. It has now grown into a key driver of innovation beyond system administration, with a significant impact on the world of web development. Mastering Docker shows you how you can ensure that you're keeping up with the innovations it's driving and be sure you're using it to its full potential. This fourth edition not only demonstrates how to use Docker more effectively but also helps you rethink and reimagine what you can achieve with it. You'll start by building, managing, and storing images along with exploring best practices for working with Docker confidently. Once you've got to grips with Docker security, the book covers essential concepts for extending and integrating Docker in new and innovative ways. You'll also learn how to take control of your containers efficiently using Docker Compose, Docker Swarm, and Kubernetes. By the end of this Docker book, you'll have a broad yet detailed sense of what's possible with Docker and how seamlessly it fits in with a range of other platforms and tools. What you will learn Get to grips with essential Docker components and concepts Discover the best ways to build, store, and distribute container images Understand how Docker can fit into your development workflow Secure your containers and files with Docker's security features Explore first-party and third-party cluster tools and plugins Launch and manage your Kubernetes clusters in major public clouds Who this book is forIf you are a software architect, DevOps engineer, sysadmin, or IT professional looking to leverage Docker's extensive features for innovating any process from system administration to web development, Mastering Docker will show you how you can use it to its full potential. A basic understanding of containerization and prior Docker experience is necessary.

Proven methodologies and concurrency techniques that will help you write faster and better code with Go programming Key Features Explore Go's profiling tools to write faster programs by identifying and fixing bottlenecks Address Go-specific performance issues such as memory allocation and garbage collection Delve into the subtleties of concurrency and discover how to successfully implement it in everyday applications Book DescriptionGo is an easy-to-write language that is popular among developers thanks to its features such as concurrency, portability, and ability to reduce complexity. This Golang book will teach you how to construct idiomatic Go code that is reusable and highly performant. Starting with an introduction to performance concepts, you'll understand the ideology behind Go's performance. You'll then learn how to effectively implement Go data structures and algorithms along with exploring data manipulation and organization to write programs for scalable software. This book covers channels and goroutines for parallelism and concurrency to write high-performance code for distributed systems. As you advance, you'll learn how to manage memory effectively. You'll explore the compute unified device architecture (CUDA) application programming interface (API), use containers to build Go code, and work with the Go build cache for quicker compilation. You'll also get to grips with profiling and tracing Go code for detecting bottlenecks in your system. Finally, you'll evaluate clusters and job queues for performance optimization and monitor the application for performance regression. By the end of this Go programming book, you'll be able to improve existing code and fulfill customer requirements by writing efficient programs. What you will learn Organize and manipulate data effectively with clusters and job queues Explore commonly applied Go data structures and algorithms Write anonymous functions in Go to build reusable apps Profile and trace Go apps to reduce bottlenecks and improve efficiency Deploy, monitor, and iterate Go programs with a focus on performance Dive into memory management and CPU and GPU parallelism in Go Who this book is forThis Golang book is a must for developers and professionals who have an intermediate-to-advanced understanding of Go programming, and are interested in improving their speed of code execution.