A longer format book such as Cloud Computing Bible allows a complete definition of the topic as well as in-depth introductions to essential technologies and platforms. Additionally it allows significant technologies to be presented in a form that provides enough detail for the reader to determine if it is something that they are interested in learning more about.
It is important to stress platform and technologies as the main subject and intersperse that with products in order to provide an extended life span, but have current appeal. Leverage Azure security services to architect robust cloud solutions in Microsoft Azure Key Features Secure your Azure cloud workloads across applications and networks Protect your Azure infrastructure from cyber attacks Discover tips and techniques for implementing, deploying, and maintaining secure cloud services using best practices Book Description Security is always integrated into cloud platforms, causing users to let their guard down as they take cloud security for granted.
Cloud computing brings new security challenges, but you can overcome these with Microsoft Azure's shared responsibility model. Mastering Azure Security covers the latest security features provided by Microsoft to identify different threats and protect your Azure cloud using innovative techniques.
The book takes you through the built-in security controls and the multi-layered security features offered by Azure to protect cloud workloads across apps and networks. You'll get to grips with using Azure Security Center for unified security management, building secure application gateways on Azure, protecting the cloud from DDoS attacks, safeguarding with Azure Key Vault, and much more. Additionally, the book covers Azure Sentinel, monitoring and auditing, Azure security and governance best practices, and securing PaaS deployments.
By the end of this book, you'll have developed a solid understanding of cybersecurity in the cloud and be able to design secure solutions in Microsoft Azure.
What you will learn Understand cloud security concepts Get to grips with managing cloud identities Adopt the Azure security cloud infrastructure Grasp Azure network security concepts Discover how to keep cloud resources secure Implement cloud governance with security policies and rules Who this book is for This book is for Azure cloud professionals, Azure architects, and security professionals looking to implement secure cloud services using Azure Security Centre and other Azure security features.
A fundamental understanding of security concepts and prior exposure to the Azure cloud will help you understand the key concepts covered in the book more effectively. Cloud Data Centers and Cost Modeling establishes a framework for strategic decision-makers to facilitate the development of cloud data centers. Just as building a house requires a clear understanding of the blueprints, architecture, and costs of the project; building a cloud-based data center requires similar knowledge.
The authors take a theoretical and practical approach, starting with the key questions to help uncover needs and clarify project scope. They then demonstrate probability tools to test and support decisions, and provide processes that resolve key issues. After laying a foundation of cloud concepts and definitions, the book addresses data center creation, infrastructure development, cost modeling, and simulations in decision-making, each part building on the previous.
In this way the authors bridge technology, management, and infrastructure as a service, in one complete guide to data centers that facilitates educated decision making.
Explains how to balance cloud computing functionality with data center efficiency Covers key requirements for power management, cooling, server planning, virtualization, and storage management Describes advanced methods for modeling cloud computing cost including Real Option Theory and Monte Carlo Simulations Blends theoretical and practical discussions with insights for developers, consultants, and analysts considering data center development.
Discover your complete guide to designing, deploying, and managing OpenStack-based clouds in mid-to-large IT infrastructures with best practices, expert understanding, and more About This Book Design and deploy an OpenStack-based cloud in your mid-to-large IT infrastructure using automation tools and best practices Keep yourself up-to-date with valuable insights into OpenStack components and new services in the latest OpenStack release Discover how the new features in the latest OpenStack release can help your enterprise and infrastructure Who This Book Is For This book is for system administrators, cloud engineers, and system architects who would like to deploy an OpenStack-based cloud in a mid-to-large IT infrastructure.
This book requires a moderate level of system administration and familiarity with cloud concepts. What You Will Learn Explore the main architecture design of OpenStack components and core-by-core services, and how they work together Design different high availability scenarios and plan for a no-single-point-of-failure environment Set up a multinode environment in production using orchestration tools Boost OpenStack's performance with advanced configuration Delve into various hypervisors and container technology supported by OpenStack Get familiar with deployment methods and discover use cases in a real production environment Adopt the DevOps style of automation while deploying and operating in an OpenStack environment Monitor the cloud infrastructure and make decisions on maintenance and performance improvement In Detail In this second edition, you will get to grips with the latest features of OpenStack.
Starting with an overview of the OpenStack architecture, you'll see how to adopt the DevOps style of automation while deploying and operating in an OpenStack environment. We'll show you how to create your own OpenStack private cloud. Then you'll learn about various hypervisors and container technology supported by OpenStack.
You'll get an understanding about the segregation of compute nodes based on reliability and availability needs. Next, you'll understand the OpenStack infrastructure from a cloud user point of view. Moving on, you'll develop troubleshooting skills, and get a comprehensive understanding of services such as high availability and failover in OpenStack.
Finally, you will gain experience of running a centralized logging server and monitoring OpenStack services. The book will show you how to carry out performance tuning based on OpenStack service logs. You will be able to master OpenStack benchmarking and performance tuning. By the end of the book, you'll be ready to take steps to deploy and manage an OpenStack cloud with the latest open source technologies.
Style and approach This book will help you understand the flexibility of OpenStack by showcasing integration of several out-of-the-box solutions in order to build a large-scale cloud environment.. It will also cover detailed discussions on the various design and deployment strategies for implementing a fault-tolerant and highly available cloud infrastructure.
The primary purpose of this book is to capture the state-of-the-art in Cloud Computing technologies and applications. The book will also aim to identify potential research directions and technologies that will facilitate creation a global market-place of cloud computing services supporting scientific, industrial, business, and consumer applications.
We expect the book to serve as a reference for larger audience such as systems architects, practitioners, developers, new researchers and graduate level students. This area of research is relatively recent, and as such has no existing reference book that addresses it.
This book will be a timely contribution to a field that is gaining considerable research interest, momentum, and is expected to be of increasing interest to commercial developers. The book is targeted for professional computer science developers and graduate students especially at Masters level.
As Cloud Computing is recognized as one of the top five emerging technologies that will have a major impact on the quality of science and society over the next 20 years, its knowledge will help position our readers at the forefront of the field.
If you're involved in planning IT infrastructure as a network or system architect, system administrator, or developer, this book will help you adapt your skills to work with these highly scalable, highly redundant infrastructure services. While analysts hotly debate the advantages and risks of cloud computing, IT staff and programmers are left to determine whether and how to put their applications into these virtualized services.
Cloud Application Architectures provides answers -- and critical guidance -- on issues of cost, availability, performance, scaling, privacy, and security. With Cloud Application Architectures, you will: Understand the differences between traditional deployment and cloud computing Determine whether moving existing applications to the cloud makes technical and business sense Analyze and compare the long-term costs of cloud services, traditional hosting, and owning dedicated servers Learn how to build a transactional web application for the cloud or migrate one to it Understand how the cloud helps you better prepare for disaster recovery Change your perspective on application scaling To provide realistic examples of the book's principles in action, the author delves into some of the choices and operations available on Amazon Web Services, and includes high-level summaries of several of the other services available on the market today.
Cloud Application Architectures provides best practices that apply to every available cloud service. Learn how to make the transition to the cloud and prepare your web applications to succeed.
Recent research shows that cloud computing will be worth billions of dollars in new investments. Organizations are flocking to the cloud services to benefit from the elasticity, self-services, resource abundance, ubiquity, responsiveness, and cost efficiencies that it offers.
Many government and private universities have already migrated to the cloud. The next wave in computing technology—expected to usher in a new era—will be based on cloud computing. 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 Description Multi-cloud has emerged as one of the top cloud computing trends, with businesses wanting to reduce their reliance on only one vendor.
Since it is possible to provision on demand any component of the computing stack, it is easier to turn ideas into products with limited costs and by concentrating technical efforts on what matters: the added value. As any new technology develops and becomes popular, new issues have to be faced. Cloud com-puting is not an exception. New, interesting problems and challenges are regularly being posed to the cloud community, including IT practitioners, managers, governments, and regulators.
Security in terms of confidentiality, secrecy, and protection of data in a cloud environment is another important challenge. Organizations do not own the infrastructure they use to process data and store information. This condition poses challenges for confidential data, which organizations cannot afford to reveal. Therefore, assurance on the confidentiality of data and compliance to secu-rity standards, which give a minimum guarantee on the treatment of information on cloud comput-ing systems, are sought.
The problem is not as evident as it seems: even though cryptography can help secure the transit of data from the private premises to the cloud infrastructure, in order to be processed the information needs to be decrypted in memory. This is the weak point of the chain: since virtualization allows capturing almost transparently the memory pages of an instance, these data could easily be obtained by a malicious provider.
Legal issues may also arise. These are specifically tied to the ubiquitous nature of cloud com-puting, which spreads computing infrastructure across diverse geographical locations. Different leg-islation about privacy in different countries may potentially create disputes as to the rights that third parties including government agencies have to your data.
European countries are more restrictive and pro-tect the right of privacy. An interesting scenario comes up when a U. In this case, should this organization be suspected by the government, it would become difficult or even impossible for the U. The idea of renting computing services by leveraging large distributed computing facilities has been around for long time. It dates back to the days of the mainframes in the early s. From there on, technology has evolved and been refined.
This process has created a series of favorable conditions for the realization of cloud computing. In tracking the historical evolution, we briefly review five core technologies that played an important role in the realization of cloud computing. These technolo-gies are distributed systems, virtualization, Web 2.
Clouds are essentially large distributed computing facilities that make available their services to third parties on demand. As a reference, we consider the characterization of a distributed system proposed by Tanenbaum et al. This is a general definition that includes a variety of computer systems, but it evidences two very important elements characterizing a distributed system: the fact that it is composed of multiple independent components and that these components are perceived as a single entity by users.
This is particularly true in the case of cloud computing, in which clouds hide the complex architecture they rely on and provide a single interface to users. The primary purpose of distributed systems is to share resources and utilize them better. This is true in the case of cloud computing, where this concept is taken to the extreme and resources infrastructure, runtime environments, and services are rented to users.
In fact, one of the driving factors of cloud computing has been the availability of the large computing facilities of IT giants Amazon, Google that found that offering their com-puting capabilities as a service provided opportunities to better utilize their infrastructure.
Distributed systems often exhibit other properties such as heterogeneity, openness, scalability,. To some extent these also characterize clouds, especially in the context of scalability, concurrency, and continuous availability. Three major milestones have led to cloud computing: mainframe computing, cluster computing, and grid computing. These were the first examples of large computational facilities leveraging multiple processing units. Mainframes were powerful, highly reliable computers specialized for large.
They were mostly used by large organizations for bulk data processing tasks such as online transactions, enterprise resource planning, and other operations involving the processing of significant amounts of data. Even though mainframes cannot be considered distributed systems, they offered large computational power by using multiple processors, which were presented as a single entity to users. No system shutdown was required to replace failed components, and the system could work without interruption.
Batch processing was the main application of mainframes. Now their popularity and deployments have reduced, but evolved versions of such systems are still in use for transaction processing such as online banking, airline ticket booking, supermarket and telcos, and government services.
Cluster computing [3][4] started as a low-cost alternative to the use of mainframes and supercomputers. The technology advancement that created faster and more powerful mainframes and supercomputers eventually generated an increased availability of cheap commodity machines as a side effect. These machines could then be connected by a high-bandwidth network and controlled by specific software tools that manage them as a single system.
Starting in the s, clusters become the standard technology for parallel and high-performance computing. Built by commodity machines, they were cheaper than mainframes and made high-performance computing available to a large number of groups, including universities and small research labs. Moreover, clusters could be easily extended if more computational power was required.
Grid computing [8] appeared in the early s as an evolution of cluster computing. In an analogy to the power grid, grid computing proposed a new approach to access large computational power, huge storage facilities, and a variety of services. Grids initially developed as aggregations of geographically dispersed clusters by means of Internet connections. These clusters belonged to different organizations, and arrangements were made among them to share the computational power.
Several developments made possible the diffusion of computing grids: a clusters became quite common resources; b they were often underutilized; c new problems were requiring computational power that went beyond the capability of single clusters; and d the improvements in networking and the diffusion of the Internet made possible long-distance, high-bandwidth connectivity.
All these elements led to the development of grids, which now serve a multitude of users across the world. It defines a. Cloud computing is often considered the successor of grid computing. In reality, it embodies aspects of all these three major technologies. Computing clouds are deployed in large datacenters hosted by a single organization that provides services to others.
Clouds are characterized by the fact of having virtually infinite capacity, being tolerant to failures, and being always on, as in the case of mainframes. In many cases, the computing nodes that form the infrastructure of computing clouds are commodity machines, as in the case of clusters. The services made available by a cloud vendor are consumed on a pay-per-use basis, and clouds fully implement the utility vision intro-duced by grid computing.
Virtualizationis another core technology for cloud computing. It encompasses a collection of solu-tions allowing the abstraction of some of the fundamental elements for computing, such as hard-ware, runtime environments, storage, and networking. Virtualization has been around for more than 40 years, but its application has always been limited by technologies that did not allow an efficient use of virtualization solutions.
Today these limitations have been substantially overcome, and vir-tualization has become a fundamental element of cloud computing. This is particularly true for solutions that provide IT infrastructure on demand.
Virtualization confers that degree of customiza-tion and control that makes cloud computing appealing for users and, at the same time, sustainable for cloud services providers. Virtualization is essentially a technology that allows creation of different computing environ-ments.
These environments are called virtual because they simulate the interface that is expected by a guest. The most common example of virtualization ishardware virtualization.
This technology allows simulating the hardware interface expected by an operating system. Hardware virtualization allows the coexistence of different software stacks on top of the same hardware. These stacks are contained inside virtual machine instances, which operate in complete isolation from each other. High-performance servers can host several virtual machine instances, thus creating the opportunity to have a customized software stack on demand. This is the base technology that enables cloud computing solutions to deliver virtual servers on demand, such as Amazon EC2, RightScale, VMware vCloud, and others.
Together with hardware virtualization,storageandnetwork virtualiza-tioncomplete the range of technologies for the emulation of IT infrastructure. Virtualization technologies are also used to replicate runtime environments for programs. Applications in the case ofprocess virtual machines which include the foundation of technologies such as Java or. NET , instead of being executed by the operating system, are run by a specific pro-gram called avirtual machine.
This technique allows isolating the execution of applications and pro-viding a finer control on the resource they access. Process virtual machines offer a higher level of abstraction with respect to hardware virtualization, since the guest is only constituted by an applica-tion rather than a complete software stack. This approach is used in cloud computing to provide a platform for scaling applications on demand, such as Google AppEngine and Windows Azure.
The Web is the primary interface through which cloud computing delivers its services. At present, the Web encompasses a set of technologies and services that facilitate interactive information shar-ing, collaboration, user-centered design, and application composition.
This evolution has trans-formed the Web into a rich platform for application development and is known asWeb 2. This term captures a new way in which developers architect applications and deliver services through the Internet and provides new experience for users of these applications and services.
These capabilities are obtained by integrating a collection of standards and technologies such as. These technologies allow us to build applications leveraging the contribution of users, who now become providers of content.
Furthermore, the capillary diffusion of the Internet opens new opportunities and markets for the Web, the services of which can now be accessed from a variety of devices: mobile phones, car dashboards, TV sets, and others. These new scenarios require an increased dynamism for appli-cations, which is another key element of this technology. There is no need to deploy new software releases on the installed base at the client side.
Users can take advantage of the new software features sim-ply by interacting with cloud applications. Lightweight deployment and programming models are very important for effective support of such dynamism. Loose coupling is another fundamental property. This way it becomes easier to follow the interests of users.
Finally, Web 2. Twitter, YouTube, de. In particular, social networking Websites take the biggest advantage of Web 2. Moreover, community Websites harness the collective intelligence of the community, which provides content to the appli-cations themselves: Flickr provides advanced services for storing digital pictures and videos, Facebook is a social networking site that leverages user activity to provide content, and Blogger, like any other blogging site, provides an online diary that is fed by users.
This idea of the Web as a transport that enables and enhances interaction was introduced in by Darcy DiNucci5and started to become fully realized in Today it is a mature plat-form for supporting the needs of cloud computing, which strongly leverages Web 2. From a social perspective, Web 2. Service orientationis the core reference model for cloud computing systems.
This approach adopts the concept of services as the main building blocks of application and system development. Service-oriented computing SOC supports the development of rapid, low-cost, flexible, interopera-ble, and evolvable applications and systems [19].
Aserviceis an abstraction representing a self-describing and platform-agnostic component that can perform any function—anything from a simple function to a complex business process. Virtually any piece of code that performs a task can be turned into a service and expose its func-tionalities through a network-accessible protocol. A service is supposed to beloosely coupled, reus-able, programming language independent, and location transparent. Loose coupling allows services to serve different scenarios more easily and makes them reusable.
Independence from a specific platform increases services accessibility. Thus, a wider range of clients, which can look up services in global registries and consume them in a location-transparent manner, can be served. Services are composed and aggregated into aservice-oriented architecture SOA [27], which is a logical way of organizing software systems to provide end users or other entities distributed over the network with services through published and discoverable interfaces.
Service-oriented computing introduces and diffuses two important concepts, which are also fun-damental to cloud computing:quality of service QoS andSoftware-as-a-Service SaaS. These could be performance metrics such as response time, or security attributes, transactional integrity, reliability, scalability, and availability. QoS requirements are established between the client and the provider via an SLA that identifies the minimum values or an acceptable range for the QoS attributes that need to be satisfied upon the service call.
Next, we describe the two extensions to the Cilk language and runtime that are required by our model: versioned objects, a new type of hyperobject [5], that automatically manages.
For example, a computer model for risk of complications of diabetes Eastman et al. Since the Java compiler verified that BankAccount implements BankAccountSpecification , the my account object can be an argument to the constructor method of MortgageCalculator..
With the cloud computing technology, users use a variety of devices, including PCs, laptops, smartphones, and PDAs to access programs, storage, and. After the memory mode has been activated, camera parameters that influence the image size can..
The public sector in the European Union has advanced a lot in terms of e-government and digital transformation initiatives during the last 20 years, both in developing examples on an. Messages use an address table to establish the message destination unless a binding already exists to reference the destination. Since the binding table exists as a separate library,. Nowadays, the amount of data in many applications has been increased from TB level to PB level, and even higher level. Various fields have accumulated massive data.
On the other hand,. Show more Page. Download now Page. You'll learn how to rethink your approach from a technology, process, and organizational standpoint to realize the promise of cost optimization, agility, and innovation that public cloud platforms provide.
Learn the difference between a working in a datacenter vs operating in the cloud Explore patterns and anti-patterns for organizing cloud operating models Get best practices for making the organizational change required for a move to the cloud Understand why Site Reliability Engineering is essential for cloud operations Improve organizational performance through value stream mapping Learn how companies are proactively ensuring compliance in the cloud.
Just as building a house requires a clear understanding of the blueprints, architecture, and costs of the project; building a cloud-based data center requires similar knowledge.
The authors take a theoretical and practical approach, starting with the key questions to help uncover needs and clarify project scope. They then demonstrate probability tools to test and support decisions, and provide processes that resolve key issues.
After laying a foundation of cloud concepts and definitions, the book addresses data center creation, infrastructure development, cost modeling, and simulations in decision-making, each part building on the previous. In this way the authors bridge technology, management, and infrastructure as a service, in one complete guide to data centers that facilitates educated decision making. Explains how to balance cloud computing functionality with data center efficiency Covers key requirements for power management, cooling, server planning, virtualization, and storage management Describes advanced methods for modeling cloud computing cost including Real Option Theory and Monte Carlo Simulations Blends theoretical and practical discussions with insights for developers, consultants, and analysts considering data center development.
Score: 4. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications.
These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues. Covers computational platforms supporting Big Data applications Addresses key principles underlying Big Data computing Examines key developments supporting next generation Big Data platforms Explores the challenges in Big Data computing and ways to overcome them Contains expert contributors from both academia and industry.
The move to cloud computing is no longer merely a topic of discussion; it has become a core competency that every modern business needs to embrace and excel at. It has changed the way enterprise and internet computing is viewed, and this success story is the result of the long-term efforts of computing research community around the globe. It is predicted that by more than two-thirds of all enterprises across the globe will be entirely run in cloud.
These predictions have led to huge levels of funding for research and development in cloud computing and related technologies. Accordingly, universities across the globe have incorporated cloud computing and its related technologies in their curriculum, and information technology IT organizations are accelerating their skill-set evolution in order to be better prepared to manage emerging technologies and public expectations of the cloud, such as new services.
This practical hands-on introduction shows you how to increase your operational efficiency by automating day-to-day tasks that now require manual input. Throughout the book, author Peter McGowan provides a combination of theoretical information and practical coding examples to help you learn the Automate object model.
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