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Establish successful FinOps practice and bring financial visibility to define cost optimization goals and apply learnings to realize savings for your organization. Key Features Build a FinOps team and foster cross-organizational collaboration to optimize costsGain a deep insight into resource usage and rates to unlock the secrets of cost optimizationApply your FinOps expertise to run a successful practice, reinvesting savings into new feature development Book Description To gain a competitive edge in today's unpredictable economic climate, you’ll need to unravel the mystery of saving costs on Microsoft Azure Cloud. This book helps you do just that with proven strategies for building, running, and sustaining repeated cost optimization initiatives across your organization. You’ll learn how to collaborate with finance, procurement, product, and engineering teams to optimize your cloud spend and achieve cost savings that can make a significant impact on your bottom line. The book begins by showing you how to effectively monitor and manage your cloud usage, identify cost-saving opportunities, and implement changes that’ll reduce your overall spend. Whether you're a small start-up or a large enterprise, this book will equip you with the knowledge and skills needed to achieve cost savings and maintain a lean cloud infrastructure. As you advance, you'll find out how to benchmark your current cloud spend and establish a budget for cloud usage. Throughout the chapters, you’ll learn how to negotiate with your cloud provider to optimize your rate, allocate cost for the container, and gain a solid understanding of metric-driven cost optimization. By the end of this FinOps book, you’ll have become proficient in Azure Cloud financial management with the help of real-world examples, use cases, and scenarios. What you will learn Learn FinOps Informe, Optimize and Operate model for Microsoft AzureChoose from Reservations, Savings Plans, and Spot VMs to reduce costDiscover resource waste using provided pre-built workbooksWrite an effective financial business case and build a FinOps strategyRelate what you learned with three real world use caseAccurately forecast future cloud spend and track budgets Who this book is for This book is for cloud governance experts, finance managers, procurement specialists, product developers, and engineering teams looking to get clear and actionable guidance needed to implement all the phases of the FinOps life cycle in the Microsoft Azure context. This book is ideal for anyone with a basic understanding of financial terms, analytics tools, and the Azure cloud.

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 standardUse vendor-neutral tools to instrument applications to produce better telemetry and improve observabilityUnderstand how telemetry data can be correlated and interpreted to understand distributed systems Book Description Cloud-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 OpenTelemetryExplore concepts in distributed tracing, metrics, and loggingDiscover the APIs and SDKs necessary to instrument an application using OpenTelemetryExplore what auto-instrumentation is and how it can help accelerate application instrumentationConfigure and deploy the OpenTelemetry CollectorGet to grips with how different open-source backends can be used to analyze telemetry dataUnderstand how to correlate telemetry in common scenarios to get to the root cause of a problem Who this book is for This 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.

Securing Cloud Services – A pragmatic guide gives an overview of security architecture processes and explains how they may be used to derive an appropriate set of security controls to manage the risks associated with working in the Cloud. The book: * Introduces the concepts of Cloud computing and the associated security threats; * Explains key security architectures and how they can be applied to Cloud services; and * Covers security considerations for the different Cloud service models: IaaS (Infrastructure as a Service), PaaS (Platform as a Service), SaaS (Software as a Service) and FaaS (Function as a Service). Cloud computing represents a major change to the IT services landscape, but it also introduces changes to the risk landscape, which need to be understood and addressed. The flexibility of Cloud computing does not come without compromise or risk. Security remains a major concern for CIOs (chief information officers) considering a move to Cloud-based services. This book gives organisations pragmatic guidance on how to achieve consistent and cohesive security across their IT services – regardless of whether those services are hosted on-premises, on Cloud services or using a combination of both. This guidance in Securing Cloud Services – A pragmatic guide is provided through the application of a Security Reference Model to the different Cloud delivery models – IaaS, PaaS and SaaS – and also considers the changes in approach required to work securely with the newer FaaS model. Part 1 introduces the concepts embodied within Cloud computing, describes the associated security threats and lists some of the leading industry initiatives dedicated to improving the security of Cloud services. Part 2 introduces security architecture concepts and a conceptual Security Reference Model. This model is then applied to the different Cloud service models to show how the conceptual security services within the reference model can be delivered for each Cloud service model. This book will help organisations looking to implement Cloud services aimed at the enterprise – such as Amazon Web Services, Microsoft Azure, Google Cloud Platform and Salesforce – and to do so in a risk-managed manner. It is aimed at business decision makers, senior IT stakeholders, enterprise architects, information security professionals. Manage the risks associated with Cloud computing – buy this book today!

Digital transformation requires the ability to identify opportunities across industries and apply the right technologies and tools to achieve results. This book is divided into two parts with the first covering what digital transformation is and why it is important. The second part focuses on how digital transformation works. After an introduction to digital transformation, you will explore the transformation journey in logical steps and understand how to build business cases and create productivity benefit statements. Next, you'll delve into advanced topics relating to overcoming various challenges. Later, the book will take you through case studies in both private and public sector organizations. You'll explore private sector organizations such as industrial and hi-tech manufacturing in detail and get to grips with public sector organizations by learning how transformation can be achieved on a global scale and how the resident experience can be improved. Finally, you'll discover how to create a playbook that can ensure success in digital transformation. By the end of this book, you'll be well-versed with industrial digital transformation and be able to apply your skills in the real world.

Perform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and Polly Key Features * Explore popular machine learning and deep learning services with their underlying algorithms * Discover readily available artificial intelligence(AI) APIs on AWS like Vision and Language Services * Design robust architectures to enable experimentation, extensibility, and maintainability of AI apps Book Description From data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS. With this book, you'll work through hands-on exercises and learn to use these services to solve real-world problems. You'll even design, develop, monitor, and maintain machine and deep learning models on AWS. The book starts with an introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services. You'll then get to grips with detecting and translating text with Amazon Rekognition and Amazon Translate. The book will assist you in performing speech-to-text with Amazon Transcribe and Amazon Polly. Later, you'll discover the use of Amazon Comprehend for extracting information from text, and Amazon Lex for building voice chatbots. You will also understand the key capabilities of Amazon SageMaker such as wrangling big data, discovering topics in text collections, and classifying images. Finally, you'll cover sales forecasting with deep learning and autoregression, before exploring the importance of a feedback loop in machine learning. By the end of this book, you will have the skills you need to implement AI in AWS through hands-on exercises that cover all aspects of the ML model life cycle. What you will learn * Gain useful insights into different machine and deep learning models * Build and deploy robust deep learning systems to production * Train machine and deep learning models with diverse infrastructure specifications * Scale AI apps without dealing with the complexity of managing the underlying infrastructure * Monitor and Manage AI experiments efficiently * Create AI apps using AWS pre-trained AI services Who this book is for This book is for data scientists, machine learning developers, deep learning researchers, and artificial intelligence enthusiasts who want to harness the power of AWS to implement powerful artificial intelligence solutions. A basic understanding of machine learning concepts is expected.

Become a certified Azure Architect and learn to design effective solutions that span compute, security, networking, and development Key Features * Learn to successfully design and architect powerful and cost-effective solutions on Microsoft Azure * Prepare to gain AZ-300 certification with the help of mock tests and practice questions * Enhance your computing, networking, storage, and security skills to design modern cloud-based solutions Book Description From designing solutions on Azure to configuring and managing virtual networks, AZ-300 certification can help you achieve all this and more. Whether you want to get certified or gain hands-on experience in administering, developing, and architecting Azure solutions, this study guide will help you get started. The book features not only the different exam objectives, but also guides you through configuring, managing, securing, and architecting Azure resources. Divided into five modules, this book will systematically take you through the different concepts and features as you advance through the sections. The first module demonstrates how to deploy and configure infrastructure. You will cover techniques related to implementing workloads and security, before learning how to create and deploy apps in the next module. To build on your knowledge, the final two modules will get you up to speed with implementing authentication, data security, and application and platform monitoring, along with covering Azure storage, alerting, and automation strategies. Finally, you'll work through exam-based mock tests with answers to boost your confidence in passing the exam. By the end of this book, you'll have learned the concepts and techniques you need to know in order to prepare for the AZ-300 exam, along with the skills to design effective solutions on Microsoft Azure. What you will learn * Manage Azure subscriptions and resources * Understand how to migrate servers to Azure * Configure and manage virtual networks * Monitor and troubleshoot virtual network connectivity * Manage Azure Active Directory (Azure AD) Connect and implement multi-factor authentication * Implement and manage hybrid identities * Develop solutions that use Cosmos DB and the Azure SQL Database * Get to grips with implementing secure data solutions Who this book is for This book is for solution architects and experienced developers who advise stakeholders and translate business requirements into secure, scalable, and reliable solutions. Technical architects interested in learning more about designing cloud solutions will also find this book useful. Some experience and knowledge of various aspects of IT operations, including networking, security, business continuity, disaster recovery, budgeting, and governance are required to grasp the concepts covered in the book effectively.

This book will help you prepare for Google's popular Professional Cloud Architect certification from the ground up. You will learn the necessary skills to design, develop, and manage enterprise-grade cloud solutions, and thereby achieve your organization's business objectives.

Azure Resource Manager (ARM) templates are declarations of Azure resources in the JSON format to provision and maintain them using infrastructure as code. This book gives practical solutions and examples for provisioning and managing various Azure services using ARM templates.