Blockchain applications a handson approach pdf

VMware software does not emulate an instruction set for different hardware not physically present. This significantly boosts performance, but can cause problems when moving virtual machine guests between hardware hosts using different instruction sets such as found in bit Intel and AMD CPUs , or between hardware hosts with a differing number of CPUs.

Software that is CPU agnostic can usually survive such a transition, unless it is agnostic by forking at startup, in which case, the software or the guest OS must be stopped before moving it, then restarted after the move. VMware's products predate the virtualization extensions to the x86 instruction set, and do not require virtualization-enabled processors.

On newer processors, the hypervisor is now designed to take advantage of the extensions. However, unlike many other hypervisors, VMware still supports older processors. In such cases, it uses the CPU to run code directly whenever possible as, for example, when running user-mode and virtual mode code on x When direct execution cannot operate, such as with kernel-level and real-mode code, VMware products use binary translation BT to re-write the code dynamically.

The translated code gets stored in spare memory, typically at the end of the address space , which segmentation mechanisms can protect and make invisible. VMware's approach avoids some of the difficulties of virtualization on xbased platforms.

Virtual machines may deal with offending instructions by replacing them, or by simply running kernel code in user mode. Replacing instructions runs the risk that the code may fail to find the expected content if it reads itself; one cannot protect code against reading while allowing normal execution, and replacing in place becomes complicated.

Running the code unmodified in user mode will also fail, as most instructions which just read the machine state do not cause an exception and will betray the real state of the program, and certain instructions silently change behavior in user mode. One must always rewrite, performing a simulation of the current program counter in the original location when necessary and notably remapping hardware code breakpoints.

The VMware product line can also run different operating systems on a dual-boot system simultaneously by booting one partition natively while using the other as a guest within VMware Workstation. VMware ESXi , [85] an enterprise software product, can deliver greater performance than the freeware VMware Server, due to lower system computational overhead.

VMware ESXi, as a "bare-metal" product, runs directly on the server hardware, allowing virtual servers to also use hardware more or less directly. The VMware Workspace Portal was a self-service app store for workspace management.

Workspace ONE allows mobile users to access to apps and data. From Wikipedia, the free encyclopedia. Campus headquarters, Palo Alto, California. The New York Times. Accelerate Data Center Virtualization". Virtzilla beats the street, fires , crimps vCloud Air, doubles down on new products". VMware gobbles Virsto for software-ruled arrays". Is your next desktop going to live in the cloud?

The Wall Street Journal. Retrieved 6 March Retrieved 11 March Retrieved 5 April Retrieved April 27, Retrieved May 3, Virtualizing entire data centers, including admins for systems and networks". Retrieved from " https: Pages using deprecated image syntax Official website different in Wikidata and Wikipedia. Views Read Edit View history. In other projects Wikimedia Commons. This page was last edited on 7 May , at A consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with each service provider.

Capabilities are available over the network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms e. The provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to consumer demand.

Capabilities can be elastically provisioned and released, in some cases automatically, to scale rapidly outward and inward commensurate with demand. To the consumer, the capabilities available for provisioning often appear unlimited and can be appropriated in any quantity at any time. For example, one can provide SaaS implemented on physical machines bare metal , without using underlying PaaS or IaaS layers, and conversely one can run a program on IaaS and access it directly, without wrapping it as SaaS.

Pools of hypervisors within the cloud operational system can support large numbers of virtual machines and the ability to scale services up and down according to customers' varying requirements. Linux containers run in isolated partitions of a single Linux kernel running directly on the physical hardware. Linux cgroups and namespaces are the underlying Linux kernel technologies used to isolate, secure and manage the containers.

Containerisation offers higher performance than virtualization, because there is no hypervisor overhead. Also, container capacity auto-scales dynamically with computing load, which eliminates the problem of over-provisioning and enables usage-based billing.

The NIST 's definition of cloud computing describes IaaS as "where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, and deployed applications; and possibly limited control of select networking components e. IaaS-cloud providers supply these resources on-demand from their large pools of equipment installed in data centers.

For wide-area connectivity, customers can use either the Internet or carrier clouds dedicated virtual private networks. To deploy their applications, cloud users install operating-system images and their application software on the cloud infrastructure. In this model, the cloud user patches and maintains the operating systems and the application software. Cloud providers typically bill IaaS services on a utility computing basis: The capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages, libraries, services, and tools supported by the provider.

The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, or storage, but has control over the deployed applications and possibly configuration settings for the application-hosting environment.

PaaS vendors offer a development environment to application developers. The provider typically develops toolkit and standards for development and channels for distribution and payment. In the PaaS models, cloud providers deliver a computing platform , typically including operating system, programming-language execution environment, database, and web server. Application developers can develop and run their software solutions on a cloud platform without the cost and complexity of buying and managing the underlying hardware and software layers.

With some PaaS offers like Microsoft Azure , Oracle Cloud Platform and Google App Engine , the underlying computer and storage resources scale automatically to match application demand so that the cloud user does not have to allocate resources manually. The latter has also been proposed by an architecture aiming to facilitate real-time in cloud environments. Some integration and data management providers have also embraced specialized applications of PaaS as delivery models for data solutions.

The capability provided to the consumer is to use the provider's applications running on a cloud infrastructure. The applications are accessible from various client devices through either a thin client interface, such as a web browser e. The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings.

In the software as a service SaaS model, users gain access to application software and databases. Cloud providers manage the infrastructure and platforms that run the applications. SaaS is sometimes referred to as "on-demand software" and is usually priced on a pay-per-use basis or using a subscription fee. Cloud users do not manage the cloud infrastructure and platform where the application runs.

This eliminates the need to install and run the application on the cloud user's own computers, which simplifies maintenance and support. Cloud applications differ from other applications in their scalability—which can be achieved by cloning tasks onto multiple virtual machines at run-time to meet changing work demand. This process is transparent to the cloud user, who sees only a single access-point. To accommodate a large number of cloud users, cloud applications can be multitenant , meaning that any machine may serve more than one cloud-user organization.

The pricing model for SaaS applications is typically a monthly or yearly flat fee per user, [71] so prices become scalable and adjustable if users are added or removed at any point. In addition, with applications hosted centrally, updates can be released without the need for users to install new software. One drawback of SaaS comes with storing the users' data on the cloud provider's server. As a result, [ citation needed ] there could be unauthorized access to the data.

In the mobile "backend" as a service m model, also known as backend as a service BaaS , web app and mobile app developers are provided with a way to link their applications to cloud storage and cloud computing services with application programming interfaces APIs exposed to their applications and custom software development kits SDKs. Services include user management, push notifications , integration with social networking services [73] and more.

This is a relatively recent model in cloud computing, [74] with most BaaS startups dating from or later [75] [76] [77] but trends indicate that these services are gaining significant mainstream traction with enterprise consumers. Serverless computing is a cloud computing code execution model in which the cloud provider fully manages starting and stopping virtual machines as necessary to serve requests, and requests are billed by an abstract measure of the resources required to satisfy the request, rather than per virtual machine, per hour.

Function as a service FaaS is a service-hosted remote procedure call that leverages serverless computing to enable the deployment of individual functions in the cloud that run in response to events.

Private cloud is cloud infrastructure operated solely for a single organization, whether managed internally or by a third-party, and hosted either internally or externally. It can improve business, but every step in the project raises security issues that must be addressed to prevent serious vulnerabilities. Self-run data centers [82] are generally capital intensive. They have a significant physical footprint, requiring allocations of space, hardware, and environmental controls. These assets have to be refreshed periodically, resulting in additional capital expenditures.

They have attracted criticism because users "still have to buy, build, and manage them" and thus do not benefit from less hands-on management, [83] essentially "[lacking] the economic model that makes cloud computing such an intriguing concept". A cloud is called a "public cloud" when the services are rendered over a network that is open for public use.

Public cloud services may be free. Generally, public cloud service providers like Amazon Web Services AWS , Oracle , Microsoft and Google own and operate the infrastructure at their data center and access is generally via the Internet. Hybrid cloud is a composition of two or more clouds private, community or public that remain distinct entities but are bound together, offering the benefits of multiple deployment models. It allows one to extend either the capacity or the capability of a cloud service, by aggregation, integration or customization with another cloud service.

Varied use cases for hybrid cloud composition exist. For example, an organization may store sensitive client data in house on a private cloud application, but interconnect that application to a business intelligence application provided on a public cloud as a software service. Hybrid cloud adoption depends on a number of factors such as data security and compliance requirements, level of control needed over data, and the applications an organization uses. Another example of hybrid cloud is one where IT organizations use public cloud computing resources to meet temporary capacity needs that can not be met by the private cloud.

A primary advantage of cloud bursting and a hybrid cloud model is that an organization pays for extra compute resources only when they are needed. A cross-platform hybrid cloud is usually powered by different CPU architectures, for example, x and ARM, underneath. Users can transparently deploy and scale applications without knowledge of the cloud's hardware diversity. Community cloud shares infrastructure between several organizations from a specific community with common concerns security, compliance, jurisdiction, etc.

The costs are spread over fewer users than a public cloud but more than a private cloud , so only some of the cost savings potential of cloud computing are realized. A cloud computing platform can be assembled from a distributed set of machines in different locations, connected to a single network or hub service.

It is possible to distinguish between two types of distributed clouds: Multicloud is the use of multiple cloud computing services in a single heterogeneous architecture to reduce reliance on single vendors, increase flexibility through choice, mitigate against disasters, etc.

It differs from hybrid cloud in that it refers to multiple cloud services, rather than multiple deployment modes public, private, legacy. The issues of transferring large amounts of data to the cloud as well as data security once the data is in the cloud initially hampered adoption of cloud for big data , but now that much data originates in the cloud and with the advent of bare-metal servers , the cloud has become [99] a solution for use cases including business analytics and geospatial analysis.

HPC cloud refers to the use of cloud computing services and infrastructure to execute high-performance computing HPC applications []. These applications consume considerable amount of computing power and memory and are traditionally executed on clusters of computers. Various vendors offer servers that can support the execution of these applications [] [] [] [].

In HPC cloud, the deployment model allows all HPC resources to be inside the cloud provider infrastructure or different portions of HPC resources to be shared between cloud provider and client on-premise infrastructure. The adoption of cloud to run HPC applications started mostly for applications composed of independent tasks with no inter-process communication. As cloud providers began to offer high-speed network technologies such as InfiniBand , multiprocessing tightly coupled applications started to benefit from cloud as well.

Cloud architecture , [] the systems architecture of the software systems involved in the delivery of cloud computing, typically involves multiple cloud components communicating with each other over a loose coupling mechanism such as a messaging queue.

Elastic provision implies intelligence in the use of tight or loose coupling as applied to mechanisms such as these and others. Cloud engineering is the application of engineering disciplines to cloud computing. It brings a systematic approach to the high-level concerns of commercialization, standardization, and governance in conceiving, developing, operating and maintaining cloud computing systems.

It is a multidisciplinary method encompassing contributions from diverse areas such as systems , software , web , performance , information , security , platform , risk , and quality engineering. Cloud computing poses privacy concerns because the service provider can access the data that is in the cloud at any time. It could accidentally or deliberately alter or even delete information.

That is permitted in their privacy policies, which users must agree to before they start using cloud services. Solutions to privacy include policy and legislation as well as end users' choices for how data is stored. Together, these form shared technology vulnerabilities. In a cloud provider platform being shared by different users there may be a possibility that information belonging to different customers resides on same data server.

Additionally, Eugene Schultz , chief technology officer at Emagined Security, said that hackers are spending substantial time and effort looking for ways to penetrate the cloud. Because data from hundreds or thousands of companies can be stored on large cloud servers, hackers can theoretically gain control of huge stores of information through a single attack—a process he called "hyperjacking".

Some examples of this include the Dropbox security breach, and iCloud leak. By having these passwords, they are able to read private data as well as have this data be indexed by search engines making the information public.

There is the problem of legal ownership of the data If a user stores some data in the cloud, can the cloud provider profit from it? Many Terms of Service agreements are silent on the question of ownership. This delivers great incentive to public cloud computing service providers to prioritize building and maintaining strong management of secure services.

There is the risk that end users do not understand the issues involved when signing on to a cloud service persons sometimes don't read the many pages of the terms of service agreement, and just click "Accept" without reading. This is important now that cloud computing is becoming popular and required for some services to work, for example for an intelligent personal assistant Apple's Siri or Google Now.

Fundamentally, private cloud is seen as more secure with higher levels of control for the owner, however public cloud is seen to be more flexible and requires less time and money investment from the user. According to Bruce Schneier , "The downside is that you will have limited customization options. Cloud computing is cheaper because of economics of scale , and — like any outsourced task — you tend to get what you get. A restaurant with a limited menu is cheaper than a personal chef who can cook anything you want.

Fewer options at a much cheaper price: Cloud providers often decide on the management policies, which moderates what the cloud users are able to do with their deployment. Privacy and confidentiality are big concerns in some activities.

For instance, sworn translators working under the stipulations of an NDA , might face problems regarding sensitive data that are not encrypted. Cloud computing is beneficial to many enterprises; it lowers costs and allows them to focus on competence instead of on matters of IT and infrastructure. Nevertheless, cloud computing has proven to have some limitations and disadvantages, especially for smaller business operations, particularly regarding security and downtime.

Technical outages are inevitable and occur sometimes when cloud service providers become overwhelmed in the process of serving their clients. This may result to temporary business suspension. Since this technology's systems rely on the internet, an individual cannot be able to access their applications, server or data from the cloud during an outage. Cloud computing is still a subject of research. The issue of carrying out investigations where the cloud storage devices cannot be physically accessed has generated a number of changes to the way that digital evidence is located and collected [].

New process models have been developed to formalize collection.