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| azure learning path diagram: Microsoft Azure Essentials Azure Machine Learning Jeff Barnes, 2015-04-25 Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series. |
| azure learning path diagram: Microsoft Azure Essentials - Fundamentals of Azure Michael Collier, Robin Shahan, 2015-01-29 Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. The first ebook in the series, Microsoft Azure Essentials: Fundamentals of Azure, introduces developers and IT professionals to the wide range of capabilities in Azure. The authors - both Microsoft MVPs in Azure - present both conceptual and how-to content for key areas, including: Azure Websites and Azure Cloud Services Azure Virtual Machines Azure Storage Azure Virtual Networks Databases Azure Active Directory Management tools Business scenarios Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the “Microsoft Azure Essentials” series. |
| azure learning path diagram: Microsoft Azure Security Center Yuri Diogenes, Tom Shinder, 2018-06-04 Discover high-value Azure security insights, tips, and operational optimizations This book presents comprehensive Azure Security Center techniques for safeguarding cloud and hybrid environments. Leading Microsoft security and cloud experts Yuri Diogenes and Dr. Thomas Shinder show how to apply Azure Security Center’s full spectrum of features and capabilities to address protection, detection, and response in key operational scenarios. You’ll learn how to secure any Azure workload, and optimize virtually all facets of modern security, from policies and identity to incident response and risk management. Whatever your role in Azure security, you’ll learn how to save hours, days, or even weeks by solving problems in most efficient, reliable ways possible. Two of Microsoft’s leading cloud security experts show how to: • Assess the impact of cloud and hybrid environments on security, compliance, operations, data protection, and risk management • Master a new security paradigm for a world without traditional perimeters • Gain visibility and control to secure compute, network, storage, and application workloads • Incorporate Azure Security Center into your security operations center • Integrate Azure Security Center with Azure AD Identity Protection Center and third-party solutions • Adapt Azure Security Center’s built-in policies and definitions for your organization • Perform security assessments and implement Azure Security Center recommendations • Use incident response features to detect, investigate, and address threats • Create high-fidelity fusion alerts to focus attention on your most urgent security issues • Implement application whitelisting and just-in-time VM access • Monitor user behavior and access, and investigate compromised or misused credentials • Customize and perform operating system security baseline assessments • Leverage integrated threat intelligence to identify known bad actors |
| azure learning path diagram: Learn Azure in a Month of Lunches, Second Edition Iain Foulds, 2020-10-06 Learn Azure in a Month of Lunches, Second Edition, is a tutorial on writing, deploying, and running applications in Azure. In it, you’ll work through 21 short lessons that give you real-world experience. Each lesson includes a hands-on lab so you can try out and lock in your new skills. Summary You can be incredibly productive with Azure without mastering every feature, function, and service. Learn Azure in a Month of Lunches, Second Edition gets you up and running quickly, teaching you the most important concepts and tasks in 21 practical bite-sized lessons. As you explore the examples, exercises, and labs, you'll pick up valuable skills immediately and take your first steps to Azure mastery! This fully revised new edition covers core changes to the Azure UI, new Azure features, Azure containers, and the upgraded Azure Kubernetes Service. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Microsoft Azure is vast and powerful, offering virtual servers, application templates, and prebuilt services for everything from data storage to AI. To navigate it all, you need a trustworthy guide. In this book, Microsoft engineer and Azure trainer Iain Foulds focuses on core skills for creating cloud-based applications. About the book Learn Azure in a Month of Lunches, Second Edition, is a tutorial on writing, deploying, and running applications in Azure. In it, you’ll work through 21 short lessons that give you real-world experience. Each lesson includes a hands-on lab so you can try out and lock in your new skills. What's inside Understanding Azure beyond point-and-click Securing applications and data Automating your environment Azure services for machine learning, containers, and more About the reader This book is for readers who can write and deploy simple web or client/server applications. About the author Iain Foulds is an engineer and senior content developer with Microsoft. Table of Contents PART 1 - AZURE CORE SERVICES 1 Before you begin 2 Creating a virtual machine 3 Azure Web Apps 4 Introduction to Azure Storage 5 Azure Networking basics PART 2 - HIGH AVAILABILITY AND SCALE 6 Azure Resource Manager 7 High availability and redundancy 8 Load-balancing applications 9 Applications that scale 10 Global databases with Cosmos DB 11 Managing network traffic and routing 12 Monitoring and troubleshooting PART 3 - SECURE BY DEFAULT 13 Backup, recovery, and replication 14 Data encryption 15 Securing information with Azure Key Vault 16 Azure Security Center and updates PART 4 - THE COOL STUFF 17 Machine learning and artificial intelligence 18 Azure Automation 19 Azure containers 20 Azure and the Internet of Things 21 Serverless computing |
| azure learning path diagram: Deep Learning with Azure Mathew Salvaris, Danielle Dean, Wee Hyong Tok, 2018-08-24 Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI? Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll Learn Become familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AI Use pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more) Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolving Discover the options for training and operationalizing deep learning models on Azure Who This Book Is For Professional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful. |
| azure learning path diagram: Exam Ref DP-900 Microsoft Azure Data Fundamentals Daniel A. Seara, Francesco Milano, 2021-03-12 Prepare for Microsoft Exam DP-900 Demonstrate your real-world foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services. Designed for business users, functional consultants, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure Data Fundamentals level. Focus on the expertise measured by these objectives: Describe core data concepts Describe how to work with relational data on Azure Describe how to work with non-relational data on Azure Describe an analytics workload on Azure This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you have foundational knowledge of core data concepts and their implementation with Microsoft Azure data services, and are beginning to work with data in the cloud About the Exam Exam DP-900 focuses on core knowledge for describing fundamental database concepts and skills for cloud environments; cloud data services within Azure; cloud data roles, tasks, and responsibilities; Azure relational and non-relational data offerings, provisioning, and deployment; querying Azure relational databases; working with Azure non-relational data stores; building modern Azure data analytics solutions; and exploring Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure Data Fundamentals certification, demonstrating your understanding of the core capabilities of Azure data services and their use with relational data, non-relational data, and analytics workloads. See full details at: www.microsoft.com/learn |
| azure learning path diagram: Designing Distributed Systems Brendan Burns, 2018-02-20 Without established design patterns to guide them, developers have had to build distributed systems from scratch, and most of these systems are very unique indeed. Today, the increasing use of containers has paved the way for core distributed system patterns and reusable containerized components. This practical guide presents a collection of repeatable, generic patterns to help make the development of reliable distributed systems far more approachable and efficient. Author Brendan Burns—Director of Engineering at Microsoft Azure—demonstrates how you can adapt existing software design patterns for designing and building reliable distributed applications. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system. Understand how patterns and reusable components enable the rapid development of reliable distributed systems Use the side-car, adapter, and ambassador patterns to split your application into a group of containers on a single machine Explore loosely coupled multi-node distributed patterns for replication, scaling, and communication between the components Learn distributed system patterns for large-scale batch data processing covering work-queues, event-based processing, and coordinated workflows |
| azure learning path diagram: Interpretable Machine Learning Christoph Molnar, 2020 This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project. |
| azure learning path diagram: Enterprise Cloud Strategy Barry Briggs, Eduardo Kassner, 2016-01-07 How do you start? How should you build a plan for cloud migration for your entire portfolio? How will your organization be affected by these changes? This book, based on real-world cloud experiences by enterprise IT teams, seeks to provide the answers to these questions. Here, you’ll see what makes the cloud so compelling to enterprises; with which applications you should start your cloud journey; how your organization will change, and how skill sets will evolve; how to measure progress; how to think about security, compliance, and business buy-in; and how to exploit the ever-growing feature set that the cloud offers to gain strategic and competitive advantage. |
| azure learning path diagram: Hands-On Machine Learning with Azure Thomas K Abraham, Parashar Shah, Jen Stirrup, Lauri Lehman, Anindita Basak, 2018-10-31 Implement machine learning, cognitive services, and artificial intelligence solutions by leveraging Azure cloud technologies Key FeaturesLearn advanced concepts in Azure ML and the Cortana Intelligence Suite architectureExplore ML Server using SQL Server and HDInsight capabilitiesImplement various tools in Azure to build and deploy machine learning modelsBook Description Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML projects in the cloud in a cost-effective way. The book begins by covering the benefits of ML and AI in the cloud. You will then explore Microsoft’s Team Data Science Process to establish a repeatable process for successful AI development and implementation. You will also gain an understanding of AI technologies available in Azure and the Cognitive Services APIs to integrate them into bot applications. This book lets you explore prebuilt templates with Azure Machine Learning Studio and build a model using canned algorithms that can be deployed as web services. The book then takes you through a preconfigured series of virtual machines in Azure targeted at AI development scenarios. You will get to grips with the ML Server and its capabilities in SQL and HDInsight. In the concluding chapters, you’ll integrate patterns with other non-AI services in Azure. By the end of this book, you will be fully equipped to implement smart cognitive actions in your models. What you will learnDiscover the benefits of leveraging the cloud for ML and AIUse Cognitive Services APIs to build intelligent botsBuild a model using canned algorithms from Microsoft and deploy it as a web serviceDeploy virtual machines in AI development scenariosApply R, Python, SQL Server, and Spark in AzureBuild and deploy deep learning solutions with CNTK, MMLSpark, and TensorFlowImplement model retraining in IoT, Streaming, and Blockchain solutionsExplore best practices for integrating ML and AI functions with ADLA and logic appsWho this book is for If you are a data scientist or developer familiar with Azure ML and cognitive services and want to create smart models and make sense of data in the cloud, this book is for you. You’ll also find this book useful if you want to bring powerful machine learning services into your cloud applications. Some experience with data manipulation and processing, using languages like SQL, Python, and R, will aid in understanding the concepts covered in this book |
| azure learning path diagram: 37 Things One Architect Knows about IT Transformation Gregor Hohpe, 2016-08-01 Many large enterprises are feeling pressure from the rapid digitalization of the world: digital disruptors attack unexpectedly with brand-new business models; the FaceBook generation has dramatically different user expectations; and a whole slew of new technologies has become available to everyone with a credit card. This is tough stuff for enterprises that have been, and still are, very successful, but are built around traditional technology and organizational structures. Turning the tanker, as the need to transform is often described, has become a board room-level topic in many traditional enterprises. Not as easily done as said. Chief IT Architects and CTOs play a key role in such a digital transformation endeavor. They combine the technical, communication, and organizational skill to understand how a tech stack refresh can actually benefit the business, what being agile and DevOps really mean, and what technology infrastructure is needed to assure quality while moving faster. Their job is not an easy one, though: they must maneuver in an organization where IT is often still seen as a cost center, where operations means run as opposed to change, and where middle-aged middle-management has become cozy neither understanding the business strategy nor the underlying technology. It's no surprise then that IT architects have become some of the most sought-after IT professionals around the globe. This book aims to equip IT architects with the skills necessary to become effective not just in systems architecture, but also in shaping and driving the necessary transformation of large-scale IT departments. In today's world, technical transformation and organizational transformation have become inseparable. Organized into 37 episodes, this book explains: The role and qualities of an architect in a large enterprise How to think about architecture at enterprise scale How to communicate to a variety of stakeholders Organizational structures and systems How to transform traditional organizations Armed with these insights, architects and CTOs will be able to ride the Architect Elevator up and down the organization to instill lasting change. |
| azure learning path diagram: Microsoft Azure Security Infrastructure Yuri Diogenes, Tom Shinder, Debra Shinder, 2016-08-19 This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Implement maximum control, security, and compliance processes in Azure cloud environments In Microsoft Azure Security Infrastructure,1/e three leading experts show how to plan, deploy, and operate Microsoft Azure with outstanding levels of control, security, and compliance. You’ll learn how to prepare infrastructure with Microsoft’s integrated tools, prebuilt templates, and managed services–and use these to help safely build and manage any enterprise, mobile, web, or Internet of Things (IoT) system. The authors guide you through enforcing, managing, and verifying robust security at physical, network, host, application, and data layers. You’ll learn best practices for security-aware deployment, operational management, threat mitigation, and continuous improvement–so you can help protect all your data, make services resilient to attack, and stay in control no matter how your cloud systems evolve. Three Microsoft Azure experts show you how to: • Understand cloud security boundaries and responsibilities • Plan for compliance, risk management, identity/access management, operational security, and endpoint and data protection • Explore Azure’s defense-in-depth security architecture • Use Azure network security patterns and best practices • Help safeguard data via encryption, storage redundancy, rights management, database security, and storage security • Help protect virtual machines with Microsoft Antimalware for Azure Cloud Services and Virtual Machines • Use the Microsoft Azure Key Vault service to help secure cryptographic keys and other confidential information • Monitor and help protect Azure and on-premises resources with Azure Security Center and Operations Management Suite • Effectively model threats and plan protection for IoT systems • Use Azure security tools for operations, incident response, and forensic investigation |
| azure learning path diagram: Clean Architecture Robert C. Martin, 2017-09-12 Practical Software Architecture Solutions from the Legendary Robert C. Martin (“Uncle Bob”) By applying universal rules of software architecture, you can dramatically improve developer productivity throughout the life of any software system. Now, building upon the success of his best-selling books Clean Code and The Clean Coder, legendary software craftsman Robert C. Martin (“Uncle Bob”) reveals those rules and helps you apply them. Martin’s Clean Architecture doesn’t merely present options. Drawing on over a half-century of experience in software environments of every imaginable type, Martin tells you what choices to make and why they are critical to your success. As you’ve come to expect from Uncle Bob, this book is packed with direct, no-nonsense solutions for the real challenges you’ll face–the ones that will make or break your projects. Learn what software architects need to achieve–and core disciplines and practices for achieving it Master essential software design principles for addressing function, component separation, and data management See how programming paradigms impose discipline by restricting what developers can do Understand what’s critically important and what’s merely a “detail” Implement optimal, high-level structures for web, database, thick-client, console, and embedded applications Define appropriate boundaries and layers, and organize components and services See why designs and architectures go wrong, and how to prevent (or fix) these failures Clean Architecture is essential reading for every current or aspiring software architect, systems analyst, system designer, and software manager–and for every programmer who must execute someone else’s designs. Register your product for convenient access to downloads, updates, and/or corrections as they become available. |
| azure learning path diagram: Domain-driven Design Eric Evans, 2004 Domain-Driven Design incorporates numerous examples in Java-case studies taken from actual projects that illustrate the application of domain-driven design to real-world software development. |
| azure learning path diagram: Learning UML Sinan Si Alhir, 2003 This new book is the definitive primer for UML, and starts with the foundational concepts of object-orientation in order to provide the proper context for explaining UML. |
| azure learning path diagram: Learning Microsoft Azure Geoff Webber-Cross, 2014-10-16 If you are a developer interested in building systems for Microsoft Azure, with an understanding of efficient cloud-based application development, then this is the book for you. |
| azure learning path diagram: Building Cloud Apps with Microsoft Azure Scott Guthrie, Mark Simms, Tom Dykstra, Rick Anderson, Mike Wasson, 2014-07-18 This ebook walks you through a patterns-based approach to building real-world cloud solutions. The patterns apply to the development process as well as to architecture and coding practices. The content is based on a presentation developed by Scott Guthrie and delivered by him at the Norwegian Developers Conference (NDC) in June of 2013 (part 1, part 2), and at Microsoft Tech Ed Australia in September 2013 (part 1, part 2). Many others updated and augmented the content while transitioning it from video to written form. Who should read this book Developers who are curious about developing for the cloud, are considering a move to the cloud, or are new to cloud development will find here a concise overview of the most important concepts and practices they need to know. The concepts are illustrated with concrete examples, and each chapter includes links to other resources that provide more in-depth information. The examples and the links to additional resources are for Microsoft frameworks and services, but the principles illustrated apply to other web development frameworks and cloud environments as well. Developers who are already developing for the cloud may find ideas here that will help make them more successful. Each chapter in the series can be read independently, so you can pick and choose topics that you're interested in. Anyone who watched Scott Guthrie's Building Real World Cloud Apps with Windows Azure presentation and wants more details and updated information will find that here. Assumptions This ebook expects that you have experience developing web applications by using Visual Studio and ASP.NET. Familiarity with C# would be helpful in places. |
| azure learning path diagram: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| azure learning path diagram: Kubernetes: Up and Running Kelsey Hightower, Brendan Burns, Joe Beda, 2017-09-07 Legend has it that Google deploys over two billion application containers a week. How’s that possible? Google revealed the secret through a project called Kubernetes, an open source cluster orchestrator (based on its internal Borg system) that radically simplifies the task of building, deploying, and maintaining scalable distributed systems in the cloud. This practical guide shows you how Kubernetes and container technology can help you achieve new levels of velocity, agility, reliability, and efficiency. Authors Kelsey Hightower, Brendan Burns, and Joe Beda—who’ve worked on Kubernetes at Google and other organizatons—explain how this system fits into the lifecycle of a distributed application. You will learn how to use tools and APIs to automate scalable distributed systems, whether it is for online services, machine-learning applications, or a cluster of Raspberry Pi computers. Explore the distributed system challenges that Kubernetes addresses Dive into containerized application development, using containers such as Docker Create and run containers on Kubernetes, using the docker image format and container runtime Explore specialized objects essential for running applications in production Reliably roll out new software versions without downtime or errors Get examples of how to develop and deploy real-world applications in Kubernetes |
| azure learning path diagram: Introducing Microsoft Power BI Alberto Ferrari, Marco Russo, 2016-07-07 This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Introducing Microsoft Power BI enables you to evaluate when and how to use Power BI. Get inspired to improve business processes in your company by leveraging the available analytical and collaborative features of this environment. Be sure to watch for the publication of Alberto Ferrari and Marco Russo's upcoming retail book, Analyzing Data with Power BI and Power Pivot for Excel (ISBN 9781509302765). Go to the book's page at the Microsoft Press Store here for more details:http://aka.ms/analyzingdata/details. Learn more about Power BI at https://powerbi.microsoft.com/. |
| azure learning path diagram: Azure DevOps Server 2019 Cookbook Tarun Arora, Utkarsh Shigihalli, 2019-05-03 Over 70 recipes to effectively apply DevOps best practices and implement Agile, Git, CI-CD & Test automation using Azure DevOps Server (TFS) 2019 Key FeaturesLearn improving code quality using pull requests, branch policies, githooks and git branching designAccelerate the deployment of high quality software by automating build and releases using CI-CD Pipelines.Learn tried and tested techniques to automate database deployments, App Service & Function Deployments in Azure.Book Description Azure DevOps Server, previously known as Team Foundation Server (TFS), is a comprehensive on-premise DevOps toolset with a rich ecosystem of open source plugins. This book is your one stop guide to learn how to effectively use all of these Azure DevOps services to go from zero to DevOps. You will start by building high-quality scalable software targeting .NET, .NET core or Node.js applications. You will learn techniques that will help you to set up end-to-end traceability of your code changes from design through to release. Whether you are deploying software on-premise or in the cloud in App Service, Functions, or Azure VMs, this book will help you learn release management techniques to reduce release failures. Next, you will be able to secure application configuration by using Azure KeyVault. You will also learn how to create and release extensions to the Azure DevOps marketplace and reach million developer ecosystem for feedback. The working extension samples will allow you to iterate changes in your extensions easily and release updates to the marketplace quickly. By the end of this book, techniques provided in the book will help you break down the invisible silos between your software development teams. This will transform you from being a good software development team to an elite modern cross functional software development team. What you will learnSet up a team project for an Agile delivery team, importing requirements from ExcelPlan,track, and monitor progress using self updating boards, Sprint and Kanban boardsUnlock the features of Git by using branch policies, Git pull requests, forks, and Git hooksBuild and release .NET core, SQL and Node.js applications using Azure PipelineAutomate testing by integrating Microsoft and open source testing frameworksExtend Azure DevOps Server to a million developer ecosystemWho this book is for This book is for anyone looking to succeed with DevOps. The techniques in this book apply to all roles of the software development lifecycle including developers, testers, architects, configuration analysts, site reliability engineers and release managers. If you are a new user you’ll learn how to get started; if you are an experienced user you’ll learn how to launch your project into a modern and mature DevOps enabled software development team. |
| azure learning path diagram: Microsoft System Center - Network Virtualization and Cloud Computing Mitch Tulloch, Nader Benmessaoud, C. J. Williams, Uma Mahesh Mudigonda, Microsoft Corporation, 2014-03-07 Part of a series of specialized guides on System Center - this book delivers a focused overview of network virtualization capabilities and cloud computing scenarios. Series editor Mitch Tulloch and a team of System Center experts provide concise technical guidance as they step you through key technical scenarios and considerations. |
| azure learning path diagram: Mastering Azure Analytics Zoiner Tejada, 2017-04-06 Helps users understand the breadth of Azure services by organizing them into a reference framework they can use when crafting their own big-data analytics solution. |
| azure learning path diagram: Microsoft Azure Architect Technologies and Design Complete Study Guide Benjamin Perkins, William Panek, 2021-01-13 Become a proficient Microsoft Azure solutions architect Azure certifications are critical to the millions of IT professionals Microsoft has certified as MCSE and MCSA in Windows Server in the last 20 years. All of these professionals need to certify in key Azure exams to stay current and advance in their careers. Exams AZ-303 and AZ-304 are the key solutions architect exams that experienced Windows professionals will find most useful at the intermediate and advanced points of their careers. Microsoft Azure Architect Technologies and Design Complete Study Guide Exams AZ-303 and AZ-304 covers the two critical Microsoft Azure exams that intermediate and advanced Microsoft IT professionals will need to show proficiency as their organizations move to the Azure cloud. Understand Azure Set up your Microsoft Cloud network Solve real-world problems Get the confidence to pass the exam By learning all of these things plus using the Study Guide review questions and practice exams, the reader will be ready to take the exam and perform the job with confidence. |
| azure learning path diagram: Programming Microsoft Azure Service Fabric Haishi Bai, 2016-06-01 Build exceptionally scalable cloud applications for fast-growing businesses Microsoft Azure Service Fabric makes it easier than ever before to build large-scale distributed cloud applications. You can quickly develop and update microservice-based applications, efficiently operate highly reliable hyperscale services, and deploy the same application code on public, hosted, or private clouds. This book introduces all key Azure Service Fabric concepts and walks you through implementing several real-world applications. You’ll find advanced design patterns, tuning tips, and lessons learned from early adopters—all from the perspective of developing and operating large projects in production. Microsoft Azure evangelist Haishi Bai shows how to: Implement background services and use stateless services to handle user requests Solve state-management problems in distributed systems Package, stage, and deploy applications Upgrade applications in place, with zero downtime Leverage Quality of Service (QoS) options throughout app design, implementation, and operation Manage Service Fabric clusters with Windows PowerShell and the Management Portal Configure Service Fabric Diagnostics and analyze collected data Test functionality and performance Design Internet of Things (IoT) solutions that capture and manage petabytes of data Handle demanding real-time data-streaming compute scenarios Understand multitenancy and single-tenancy as logical architecture choices Build Service Fabric game engines to support large-scale, multiplayer online games Model complex systems with the Service Fabric Actors Pattern About This Book For all cloud developers who want to create and operate large-scale distributed cloud applications by using Microsoft Azure Service Fabric For all IT professionals who want to integrate Windows Server and Microsoft Azure in any environment, including datacenters |
| azure learning path diagram: Microsoft Azure Sentinel Yuri Diogenes, Nicholas DiCola, Jonathan Trull, 2020-02-25 Microsoft Azure Sentinel Plan, deploy, and operate Azure Sentinel, Microsoft’s advanced cloud-based SIEM Microsoft’s cloud-based Azure Sentinel helps you fully leverage advanced AI to automate threat identification and response – without the complexity and scalability challenges of traditional Security Information and Event Management (SIEM) solutions. Now, three of Microsoft’s leading experts review all it can do, and guide you step by step through planning, deployment, and daily operations. Leveraging in-the-trenches experience supporting early customers, they cover everything from configuration to data ingestion, rule development to incident management… even proactive threat hunting to disrupt attacks before you’re exploited. Three of Microsoft’s leading security operations experts show how to: • Use Azure Sentinel to respond to today’s fast-evolving cybersecurity environment, and leverage the benefits of its cloud-native architecture • Review threat intelligence essentials: attacker motivations, potential targets, and tactics, techniques, and procedures • Explore Azure Sentinel components, architecture, design considerations, and initial configuration • Ingest alert log data from services and endpoints you need to monitor • Build and validate rules to analyze ingested data and create cases for investigation • Prevent alert fatigue by projecting how many incidents each rule will generate • Help Security Operation Centers (SOCs) seamlessly manage each incident’s lifecycle • Move towards proactive threat hunting: identify sophisticated threat behaviors and disrupt cyber kill chains before you’re exploited • Do more with data: use programmable Jupyter notebooks and their libraries for machine learning, visualization, and data analysis • Use Playbooks to perform Security Orchestration, Automation and Response (SOAR) • Save resources by automating responses to low-level events • Create visualizations to spot trends, identify or clarify relationships, and speed decisions • Integrate with partners and other third-parties, including Fortinet, AWS, and Palo Alto |
| azure learning path diagram: Microsoft System Center Designing Orchestrator Runbooks David Ziembicki, Aaron Cushner, Andreas Rynes, Mitch Tulloch, 2013-09-15 Part of a series of specialized guides on System Center - this book delivers a focused drilldown into designing runbooks for Orchestrator workflow management solutions. Series editor Mitch Tulloch and a team of System Center experts provide concise technical guidance as they step you through key design concepts, criteria, and tasks. |
| azure learning path diagram: Model-Based Machine Learning John Winn, 2023-11-30 Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains. A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to a concrete, real world problem. This book tackles this challenge through model-based machine learning which focuses on understanding the assumptions encoded in a machine learning system and their corresponding impact on the behaviour of the system. The key ideas of model-based machine learning are introduced through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications that it makes sense to discuss modelling assumptions. Each chapter introduces one case study and works through step-by-step to solve it using a model-based approach. The aim is not just to explain machine learning methods, but also showcase how to create, debug, and evolve them to solve a problem. Features: Explores the assumptions being made by machine learning systems and the effect these assumptions have when the system is applied to concrete problems. Explains machine learning concepts as they arise in real-world case studies. Shows how to diagnose, understand and address problems with machine learning systems. Full source code available, allowing models and results to be reproduced and explored. Includes optional deep-dive sections with more mathematical details on inference algorithms for the interested reader. |
| azure learning path diagram: Microsoft Project 2016 Step by Step Carl Chatfield, Timothy Johnson, 2016-04-08 The quick way to learn Microsoft Project 2016! This is learning made easy. Get more done quickly with Project 2016. Jump in wherever you need answers–brisk lessons and colorful screenshots show you exactly what to do, step by step. Quickly start a new plan, build task lists, and assign resources Share your plan and track your progress Capture and fine-tune work and cost details Use Gantt charts and other views and reports to visualize project schedules Share resources across multiple plans and consolidate projects Master project management best practices while you learn Project Look up just the tasks and lessons you need |
| azure learning path diagram: Ripple Quick Start Guide Febin John James, 2018-12-31 Learn to work with XRP and build applications on Ripple's blockchain Key FeaturesLearn to use Ripple’s decentralized system for transfering digital assets globallyA simpilfied and shortened learning curve to understand the Ripple innovation and BlockchainTakes a hands-on approach to work with XRP – Ripple’s native currencyBook Description This book starts by giving you an understanding of the basics of blockchain and the Ripple protocol. You will then get some hands-on experience of working with XRP. You will learn how to set up a Ripple wallet and see how seamlessly you can transfer money abroad. You will learn about different types of wallets through which you can store and transact XRP, along with the security precautions you need to take to keep your money safe. Since Ripple is currency agnostic, it can enable the transfer of value in USD, EUR, and any other currency. You can even transfer digital assets using Ripple. You will see how you can pay an international merchant with their own native currency and how Ripple can exchange it on the fly. Once you understand the applications of Ripple, you will learn how to create a conditionally-held escrow using the Ripple API, and how to send and cash checks. Finally, you will also understand the common misconceptions people have about Ripple and discover the potential risks you must consider before making investment decisions. By the end of this book, you will have a solid foundation for working with Ripple's blockchain. Using it, you will be able to solve problems caused by traditional systems in your respective industry. What you will learnUnderstand the fundamentals of blockchain and RippleLearn how to choose a Ripple walletSet up a Ripple wallet to send and receive XRPLearn how to protect your XRPUnderstand the applications of RippleLearn how to work with the Ripple APILearn how to build applications on check and escrow features of RippleWho this book is for This book is for anyone interested in getting their hands on Ripple technology and learn where it can be used to gain competitive advantages in their respective fields. For most parts of the book, you need not have any pre-requisite knowledge. However, you need to have basic background of JavaScript to write an escrow. |
| azure learning path diagram: Azure Data Factory Cookbook Dmitry Anoshin, Dmitry Foshin, Roman Storchak, Xenia Ireton, 2020-12-24 Solve real-world data problems and create data-driven workflows for easy data movement and processing at scale with Azure Data Factory Key FeaturesLearn how to load and transform data from various sources, both on-premises and on cloudUse Azure Data Factory’s visual environment to build and manage hybrid ETL pipelinesDiscover how to prepare, transform, process, and enrich data to generate key insightsBook Description Azure Data Factory (ADF) is a modern data integration tool available on Microsoft Azure. This Azure Data Factory Cookbook helps you get up and running by showing you how to create and execute your first job in ADF. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines. This book will help you to discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage, which are frequently used for big data analytics. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premise infrastructure with cloud-native tools to get relevant business insights. As you advance, you’ll be able to integrate the most commonly used Azure Services into ADF and understand how Azure services can be useful in designing ETL pipelines. The book will take you through the common errors that you may encounter while working with ADF and show you how to use the Azure portal to monitor pipelines. You’ll also understand error messages and resolve problems in connectors and data flows with the debugging capabilities of ADF. By the end of this book, you’ll be able to use ADF as the main ETL and orchestration tool for your data warehouse or data platform projects. What you will learnCreate an orchestration and transformation job in ADFDevelop, execute, and monitor data flows using Azure SynapseCreate big data pipelines using Azure Data Lake and ADFBuild a machine learning app with Apache Spark and ADFMigrate on-premises SSIS jobs to ADFIntegrate ADF with commonly used Azure services such as Azure ML, Azure Logic Apps, and Azure FunctionsRun big data compute jobs within HDInsight and Azure DatabricksCopy data from AWS S3 and Google Cloud Storage to Azure Storage using ADF's built-in connectorsWho this book is for This book is for ETL developers, data warehouse and ETL architects, software professionals, and anyone who wants to learn about the common and not-so-common challenges faced while developing traditional and hybrid ETL solutions using Microsoft's Azure Data Factory. You’ll also find this book useful if you are looking for recipes to improve or enhance your existing ETL pipelines. Basic knowledge of data warehousing is expected. |
| azure learning path diagram: Penetration Testing Azure for Ethical Hackers David Okeyode, Karl Fosaaen, Charles Horton, 2021-11-25 Simulate real-world attacks using tactics, techniques, and procedures that adversaries use during cloud breaches Key FeaturesUnderstand the different Azure attack techniques and methodologies used by hackersFind out how you can ensure end-to-end cybersecurity in the Azure ecosystemDiscover various tools and techniques to perform successful penetration tests on your Azure infrastructureBook Description “If you're looking for this book, you need it.” — 5* Amazon Review Curious about how safe Azure really is? Put your knowledge to work with this practical guide to penetration testing. This book offers a no-faff, hands-on approach to exploring Azure penetration testing methodologies, which will get up and running in no time with the help of real-world examples, scripts, and ready-to-use source code. As you learn about the Microsoft Azure platform and understand how hackers can attack resources hosted in the Azure cloud, you'll find out how to protect your environment by identifying vulnerabilities, along with extending your pentesting tools and capabilities. First, you'll be taken through the prerequisites for pentesting Azure and shown how to set up a pentesting lab. You'll then simulate attacks on Azure assets such as web applications and virtual machines from anonymous and authenticated perspectives. In the later chapters, you'll learn about the opportunities for privilege escalation in Azure tenants and ways in which an attacker can create persistent access to an environment. By the end of this book, you'll be able to leverage your ethical hacking skills to identify and implement different tools and techniques to perform successful penetration tests on your own Azure infrastructure. What you will learnIdentify how administrators misconfigure Azure services, leaving them open to exploitationUnderstand how to detect cloud infrastructure, service, and application misconfigurationsExplore processes and techniques for exploiting common Azure security issuesUse on-premises networks to pivot and escalate access within AzureDiagnose gaps and weaknesses in Azure security implementationsUnderstand how attackers can escalate privileges in Azure ADWho this book is for This book is for new and experienced infosec enthusiasts who want to learn how to simulate real-world Azure attacks using tactics, techniques, and procedures (TTPs) that adversaries use in cloud breaches. Any technology professional working with the Azure platform (including Azure administrators, developers, and DevOps engineers) interested in learning how attackers exploit vulnerabilities in Azure hosted infrastructure, applications, and services will find this book useful. |
| azure learning path diagram: R Markdown Yihui Xie, J.J. Allaire, Garrett Grolemund, 2018-07-27 R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages. In this book, you will learn Basics: Syntax of Markdown and R code chunks, how to generate figures and tables, and how to use other computing languages Built-in output formats of R Markdown: PDF/HTML/Word/RTF/Markdown documents and ioslides/Slidy/Beamer/PowerPoint presentations Extensions and applications: Dashboards, Tufte handouts, xaringan/reveal.js presentations, websites, books, journal articles, and interactive tutorials Advanced topics: Parameterized reports, HTML widgets, document templates, custom output formats, and Shiny documents. Yihui Xie is a software engineer at RStudio. He has authored and co-authored several R packages, including knitr, rmarkdown, bookdown, blogdown, shiny, xaringan, and animation. He has published three other books, Dynamic Documents with R and knitr, bookdown: Authoring Books and Technical Documents with R Markdown, and blogdown: Creating Websites with R Markdown. J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE. He is an author of several packages in the R Markdown ecosystem including rmarkdown, flexdashboard, learnr, and radix. Garrett Grolemund is the co-author of R for Data Science and author of Hands-On Programming with R. He wrote the lubridate R package and works for RStudio as an advocate who trains engineers to do data science with R and the Tidyverse. |
| azure learning path diagram: NET Application Architecture Guide , 2009 The guide is intended to serve as a practical and convenient overview of, and reference to, the general principles of architecture and design on the Microsoft platform and the .NET Framework. |
| azure learning path diagram: Professional Azure SQL Database Administration Ahmad Osama, 2019-07-19 Leverage the features of Azure SQL database and become an expert in data management Key FeaturesExplore ways to create shards and elastic pools to scale Azure SQL databasesAutomate common management tasks with PowerShellImplement over 40 practical activities and exercises to reinforce your learningBook Description Despite being the cloud version of SQL Server, Azure SQL Database differs in key ways when it comes to management, maintenance, and administration. This book shows you how to administer Azure SQL database to fully benefit from its wide range of features and functionality. Professional Azure SQL Database Administration begins by covering the architecture and explaining the difference between Azure SQL Database and the on-premise SQL Server to help you get comfortable with Azure SQL database. You’ll perform common tasks such as migrating, backing up, and restoring a SQL Server database to an Azure database. As you progress, you’ll study how you can save costs and manage and scale multiple SQL Databases using elastic pools. You’ll also implement a disaster recovery solution using standard and active geo-replication. Whether it is learning different techniques to monitor and tune an Azure SQL database or improving performance using in-memory technology, this book will enable you to make the most out of Azure SQL database features and functionality for data management solutions. By the end of this book, you’ll be well versed with key aspects of an Azure SQL database instance, such as migration, backup restorations, performance optimization, high availability, and disaster recovery. What you will learnUnderstand Azure SQL Database configuration and pricing optionsProvision a new SQL database or migrate an existing on-premise SQL Server database to Azure SQL DatabaseBack up and restore Azure SQL DatabaseSecure an Azure SQL databaseScale an Azure SQL databaseMonitor and tune an Azure SQL databaseImplement high availability and disaster recovery with Azure SQL DatabaseAutomate common management tasks with PowerShellDevelop a scalable cloud solution with Azure SQL DatabaseManage, maintain, and secure managed instancesWho this book is for If you’re a database administrator, database developer, or an application developer interested in developing new applications or migrating existing ones with Azure SQL database, this book is for you. Prior experience of working with an on-premise SQL Server or Azure SQL database along with a basic understanding of PowerShell scripts and C# code is necessary to grasp the concepts covered in this book. |
| azure learning path diagram: Introducing MLOps Mark Treveil, Nicolas Omont, Clément Stenac, Kenji Lefevre, Du Phan, Joachim Zentici, Adrien Lavoillotte, Makoto Miyazaki, Lynn Heidmann, 2020-11-30 More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized |
| azure learning path diagram: Graph Algorithms Mark Needham, Amy E. Hodler, 2019-05-16 Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. You’ll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection. Learn how graph analytics vary from conventional statistical analysis Understand how classic graph algorithms work, and how they are applied Get guidance on which algorithms to use for different types of questions Explore algorithm examples with working code and sample datasets from Spark and Neo4j See how connected feature extraction can increase machine learning accuracy and precision Walk through creating an ML workflow for link prediction combining Neo4j and Spark |
| azure learning path diagram: Aws Certified Solutions Architect - Professional Zeal Vora, 2018-04-13 AWS Certified Solutions Architect - Professional is considered one of the top certifications in the world and there have been a few discrepancies due to the lack of a well-defined study guide which can help individuals to prepare for the certification. The book, based on the famous AWS Solutions Architect - Professional video course by Zeal, brings the much-needed step by step guide, followed by a well-defined learning process and exam preparation quizzes which will help you prepare for this challenging certification. With the detailed preparation guide and instructor support via email, join us in the journey to be an AWS Certified Solutions Architect - Professional. |
| azure learning path diagram: Azure Data and AI Architect Handbook Olivier Mertens, Breght Van Baelen, 2023-07-31 Master core data architecture design concepts and Azure Data & AI services to gain a cloud data and AI architect’s perspective to developing end-to-end solutions Purchase of the print or Kindle book includes a free PDF eBook Key Features Translate and implement conceptual architectures with the right Azure services Inject artificial intelligence into data solutions for advanced analytics Leverage cloud computing and frameworks to drive data science workloads Book DescriptionWith data’s growing importance in businesses, the need for cloud data and AI architects has never been higher. The Azure Data and AI Architect Handbook is designed to assist any data professional or academic looking to advance their cloud data platform designing skills. This book will help you understand all the individual components of an end-to-end data architecture and how to piece them together into a scalable and robust solution. You’ll begin by getting to grips with core data architecture design concepts and Azure Data & AI services, before exploring cloud landing zones and best practices for building up an enterprise-scale data platform from scratch. Next, you’ll take a deep dive into various data domains such as data engineering, business intelligence, data science, and data governance. As you advance, you’ll cover topics ranging from learning different methods of ingesting data into the cloud to designing the right data warehousing solution, managing large-scale data transformations, extracting valuable insights, and learning how to leverage cloud computing to drive advanced analytical workloads. Finally, you’ll discover how to add data governance, compliance, and security to solutions. By the end of this book, you’ll have gained the expertise needed to become a well-rounded Azure Data & AI architect.What you will learn Design scalable and cost-effective cloud data platforms on Microsoft Azure Explore architectural design patterns with various use cases Determine the right data stores and data warehouse solutions Discover best practices for data orchestration and transformation Help end users to visualize data using interactive dashboarding Leverage OpenAI and custom ML models for advanced analytics Manage security, compliance, and governance for the data estate Who this book is forThis book is for anyone looking to elevate their skill set to the level of an architect. Data engineers, data scientists, business intelligence developers, and database administrators who want to learn how to design end-to-end data solutions and get a bird’s-eye view of the entire data platform will find this book useful. Although not required, basic knowledge of databases and data engineering workloads is recommended. |
| azure learning path diagram: Microsoft Azure Data Solutions - An Introduction Daniel A. Seara, Francesco Milano, Danilo Dominici, 2021-07-14 Discover and apply the Azure platform's most powerful data solutions Cloud technologies are advancing at an accelerating pace, supplanting traditional relational and data warehouse storage solutions with novel, high-value alternatives. Now, three pioneering Azure Data consultants offer an expert introduction to the relational, non-relational, and data warehouse solutions offered by the Azure platform. Drawing on their extensive experience helping organizations get more value from the Microsoft Data Platform, the authors guide you through decision-making, implementation, operations, security, and more. Throughout, step-by-step tutorials and hands-on exercises prepare you to succeed, even if you have no cloud data experience. Three leading experts in Microsoft Azure Data Solutions show how to: Master essential concepts of data storage and processing in cloud environments Handle the changing responsibilities of data engineers moving to the cloud Get started with Azure data storage accounts and other data facilities Walk through implementing relational and non-relational data stores in Azure Secure data using the least-permissions principle, Azure Active Directory, role-based access control, and other methods Develop efficient Azure batch processing and streaming solutions Monitor Azure SQL databases, blob storage, data lakes, Azure Synapse Analytics, and Cosmos DB Optimize Azure data solutions by solving problems with storage, management, and service interactions About This Book For data engineers, systems engineers, IT managers, developers, database administrators, cloud architects, and other IT professionals Requires little or no knowledge about Azure tools and services for data analysis |
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