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What is Infrastructure Cloud Computing Posted: 04 Jul 2022 05:40 AM PDT What is cloud infrastructure? Cloud infrastructure is the combination of hardware and software components such as storage, networking, virtualization, management tools, and servers that meet the computing needs of a cloud computing model. Cloud infrastructure also includes an abstraction layer that virtualizes resources and services for users via program programming interfaces or API-enabled command-line and graphical interfaces. Cloud computing is based on cloud infrastructure, which disaggregates the functions and features of these hardware and software components. A cloud service provider (or information technology department in the case of private clouds) hosts these virtualized resources and distributes them to users via the internet or the network. These resources include virtual machines (VMs) and their components such as servers, memory and network switches, firewalls, and load balancers. These resources are often used to support complex and task-specific services such as machine learning and artificial intelligence (AI). What are the cloud infrastructure's components? Cloud infrastructure is the back-end technology elements that are found in most enterprise data centers, such as servers, persistent storage, and networking equipment, but on a larger scale. Large cloud providers such as Facebook or LinkedIn have formed partnerships with vendors to create custom infrastructure components that meet specific requirements such as power efficiency, workloads that incorporate big data and/or AI. Servers Many major public cloud providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform offer services that are based on shared multi-tenant servers. This requires huge compute resources to manage unpredictable user demand changes and balance the demand across fewer servers. Cloud infrastructure is typically composed of high-density systems that share power. Often, these multisocket or multicore servers are used. Storage Cloud infrastructure uses attached storage, which is different from traditional data center infrastructure. This includes both hard-and solid-state drives (SSDs), as well as hard drives (HDDs), instead of shared arrays on a storage network. These persistent storage systems can be aggregated with a distributed filesystem (DFS), which is designed for a specific storage scenario such as object, block, or big data. A distributed file system allows for scaling by separating the management and storage control from the physical infrastructure. This helps cloud providers match their capacity with users' workloads. Instead of adding a lot of compute nodes at once through large storage chassis, it slowly adds compute nodes with the right number and type of local disks. Networking Cloud computing relies on high-bandwidth connectivity for data transmission. Therefore, cloud infrastructure includes the usual equipment for local areas, such as switches, routers, and virtual networking support. Hybrid cloud architectures: public vs. private Each of the three major cloud computing deployment models—private cloud, public cloud, and hybridcloud—has cloud infrastructure. Private cloud A private cloud is where an organization builds and owns cloud infrastructure components. It then houses them in its own data center. This is a single-tenant environment. It means that the organization uses the entire infrastructure and services. This architecture combines the best of both the cloud and the security and control that come with owning a data center. Because their computing requirements are unpredictable, organizations may opt for a private cloud infrastructure. They might need greater security and control over infrastructure assets, critical apps, or sensitive data. Public cloud A public cloud model is one where the cloud infrastructure components are owned and shared by customers. Customers pay for core infrastructure resources, such as CPU cycles, storage, bandwidth, and other services, but they do not own or manage these resources. These services are often sold by cloud providers on demand, usually per hour and sometimes with long-term commitments. Hybrid cloud A hybrid cloud is a combination of both public and private cloud models. It provides a single cloud that can be used by users. One business can use a private cloud for sensitive workloads, applications, or data hosting. The public cloud is used to host other apps. Public cloud resources can also be used to handle spikes or bursts in demand, which gives users more options and helps private clouds work better. Another related model is the multi-cloud model. This allows an enterprise to use multiple cloud providers. This could be used to migrate apps between providers or run services concurrently. What various cloud computing delivery models are there? Three models of cloud computing services are available, each one reflecting the resources that have been accessed and those that have been provided. Infrastructure as a Service An infrastructure as a service (IaaS) model allows organizations to use cloud infrastructure components over dedicated internet connections. This model typically has recurring monthly costs for the user but allows providers to make revenue by renting out equipment or other pay-as-you-go models. Providers offer a variety of specialized services in addition to the basic cloud infrastructure services. Some examples include container infrastructure, service fabric, serverless functions, and managed network services—virtual private clouds, load balancers, domain name services, application delivery control controllers, firewalls, and others. IaaS is typically priced on a per-use basis by cloud providers. Rates correspond to the level of usage. Here are some examples: An increment of the standard virtual CPU size and the corresponding memory. storage service type (object, block), performance level (SSD or HDD), and availability. Capacity is measured in units of time, usually per month. IaaS vendors offer discounts for continued usage or the consistent use of a certain amount of compute capacity for a specific period of time. Customers can also save with reserved capacity, where they prepay a set amount of capacity for a specific period (month, year, or multiple years). Platform as a Service The lines between IaaS (PaaS) and platform as a service (PaaS) have blurred in recent years. This adds additional capabilities to those infrastructure resources. These functions include load balancing and autoscaling, as well as application development frameworks, automated deployment mechanisms, and automatic deployment. The cloud provider's services should be able to meet customers' IT and business needs. Software as a Service Software as a Service (SaaS) is a third type of cloud delivery model. It does not directly involve customers using cloud infrastructure resources, as they do with IaaS or PaaS models. SaaS is a service that hosts and manages an application. This type of architecture is often multi-tenant. Customers can log in to the service using a browser. Customers' data can be saved locally, in the cloud, or both. Cloud infrastructure versus cloud architecture The blueprint for a cloud environment that includes components and services on a large scale A provider can offer a wide range of cloud services from this cloud architecture. These services are delivered via isolated locations, each with multiple connected data centers. The physical representation of these plans is cloud infrastructure. It includes hardware, operating systems, and virtual resources that provide services for computing, storage, networking, and middleware. The abstracted capabilities and services of these physical resources are made available to the public cloud to allow them to scale easily to meet individual customer workloads. This allows you to separate control and management of those resources. For example, locally attached storage is preferred over shared disk arrays. Public cloud services are intended to support several thousand unique customers via multi-tenancy. Their architecture and infrastructure must provide sufficient performance, reliability, and security. What specifications must a cloud infrastructure meet? A public cloud provider is the best choice for organizations looking to adopt cloud computing. They have vastly greater resources and are better equipped to manage, design, and build a cloud infrastructure. These providers often acquire infrastructure components, sometimes with design input, and customers can select the levels of abstraction, such as compute, storage, virtualized instances, and other resources. These providers also offer higher-level services such as orchestration, integration, security, reporting, billing, and reporting. Some organizations may need their own cloud, and they may choose to manage the entire stack, from hardware to management to the apps and workloads that run on it. To build a private cloud infrastructure, they will need to follow these steps: A standard architecture that allows IT resources to be shared, workloads to grow and shrink, and configurations to be based on policies. hardware and software on-premises that can be used to abstract resource capabilities such as compute, virtualization, containers, storage, networking, and other functions; Additional management functions include integrations, orchestration, and security. Reporting and chargeback are also possible. The chosen provider will determine the tech stack required to create a private cloud. The choice of provider will determine the tech stack for a private cloud. A business can use the hardware and software it already has, or it can hire a vendor to provide both software and hardware. You could also use the resources of cloud providers to set up a private cloud on your own property: A hosted private cloud is a cloud service provider that hosts and manages services for one customer using dedicated infrastructure, such as hardware, software, and networking. The managed private cloud is an extension of the hosted option. This means that the provider can also manage other services, such as identity management. A virtual cloud is an isolated environment within a public cloud that isolates workloads from other customers but still runs on multi-tenant servers. This concept can be extended to include on-premises infrastructure that is managed by the cloud provider. Examples of these are AWS Outposts and Azure Stack. Cloud infrastructure has many advantages Customers can enjoy many benefits from cloud infrastructure over managing and procuring in-house infrastructure. A public cloud provider offers many benefits, including security and cost savings. Flexibility: Customers have the ability to access resources quickly and manage them to meet their business needs. This makes it possible to move workloads from on-premises to the cloud and use additional resources. Reliability: The cloud providers' vast infrastructure and redundancy options via availability zones provide reliability at a scale that is beyond the capabilities of any customer's internal resources. Cloud outages are not common, but they do happen. Customers should plan how they will use the cloud based on how reliable their workloads are and how much uptime they need. Cost: Cloud infrastructure reduces upfront capital costs and follows a consumption-based model. Users pay only for the infrastructure services that they use, usually on an hourly basis, or weekly or monthly basis. The big capital investment needed to build infrastructure on site is also turned into a smaller, more predictable operational cost. Security: Initial concerns regarding the security of public cloud resources have decreased. Cloud providers continue to invest in their security capabilities and make improvements. Most cloud security problems can be traced back to user misconfigurations of individual service services rather than external bad actors. Cloud infrastructure's disadvantages However, cloud infrastructure can present many challenges. Shared security: Cloud providers are diligent in protecting their cloud infrastructure, but it is extremely difficult to manage such a large scale of services and infrastructure. The shared responsibility model does not allow providers to secure their infrastructure. Customers are in charge of keeping their data and workloads safe by setting up, controlling access to, monitoring, and maintaining their systems correctly. Management and visibility: Customers don't have access to the physical hardware on which their workloads are running. Even though public cloud providers offer dedicated hardware and bare metal servers, these tend to be more expensive and give you more control over the server stack. Uncontrollable costs: Cloud customers can use a pay-as-you-go model if they carefully allocate and monitor their services. Unexpected cloud costs can be quickly incurred by inactive resources, overprovisioning, and failure to recognize service dependencies. Cloud services are becoming more complex, granular, and integrated, so customers must be diligent in monitoring and managing cloud usage. Tools and processes for cloud infrastructure management Cloud infrastructure management tools are available in a variety of formats. Many cloud platform providers offer a variety of performance and pricing tiers for compute and storage, networking, monitoring and analytics, machine learning, and storage, as well as network and storage. AWS Elastic Compute Cloud, Simple Storage Service, and Glacier are examples of compute and storage services. Microsoft Azure VMs and Azure Files, as well as Blob Storage and Microsoft Azure Files, are also available. Examples include Google Compute Engine, File store, and Persistent Disk. Cloud infrastructure services that are more specific address container-based workloads as well as server less functions. These are some options for container management: Amazon EKS, Amazon ECR and AWS Fargate, Amazon ECS; Azure Kubernetes Service (AKS), Azure Container Instances and Azure Container Registry; Google Kubernetes Engine (GKE), Google Cloud Run and Google App Engine; Primary serverless cloud services, including Azure Functions AWS Lambda,  and GCF. AWS CloudFormation and Azure Automation are other examples of cloud infrastructure automation. There are also third-party options like Chef Automate and Puppet Enterprise and Red Hat Ansible Automation Platform. Similarly, third-party managed service provider providers offer public cloud services through Rackspace or DigitalOcean.

How Search Engines Work Step-By-Step Posted: 04 Jul 2022 01:42 AM PDT A detailed explanation of how Google Search works Google Search is a fully-automated search engine that makes use of web crawlers, or software, that browses the internet regularly to discover pages that can be added into our database. Actually, the majority of sites listed in our search results aren't manually added to our index. Rather, they are discovered and added automatically as our web crawlers search the internet. This document provides the steps of the way Google Search is used in relation to your website. Knowing this basic information will help you resolve problems with crawling, get your site indexed, and understand how to optimize how your site will appear in Google Search. Some notes to make before we begin Before we dive deep into the intricacies of how search works, it is important to know that Google does not accept payments to crawl a website more often or make it rank higher. If someone claims otherwise, they're lying. Google cannot assure you that it will crawl or index or serve your site, regardless of whether your site is in line with the guidelines and policies of Google for owners of websites. Google Search has three levels Google Search works in three stages. Not every page can make it through each step. Crawling: Google downloads images, text, and videos from webpages it finds on the internet using automated programmed known as crawlers. Indexing: Google analyses the text, images, and video files displayed on the webpage, and then stores all the information inside the Google index, which is a huge database. Serving results from searches: When a user types in a query through Google, Google returns information pertinent to the query. Crawling  The first step is to find the pages that are on the internet. There isn't a single index of all the pages on the internet, so Google has to constantly search for new and up-to-date pages to include them in its list of known websites. This process is known as "URL discovery." Certain pages are recognizable due to the fact that Google has visited them before. Other pages are found by Google links from a well-known page to a brand new page, for instance, hub pages like an article page or hyperlinks to a blog post. Another type of page is found when you provide the list of websites (a sitemap) to Google to search. When Google detects a webpage's URL, it is able to go to (or "crawl") the page to see what's there. Google uses a vast collection of computers to search billions of pages across the internet. The programmed responsible for fetching is known as Googlebot (also called a bot, robot, or spider). The Googlebot utilizes an algorithmic method to determine which websites to visit, how often, and the number of pages it will get from each site. Google's crawlers are also designed so that they do not crawl the site too quickly in order to prevent overloading. This relies on results to the site (for instance, HTTP 500 errors refer to "slow down") and the settings within Search Console. But, Googlebot isn't able to crawl the entire pages that it discovers. Certain pages might not be allowed to be crawled by the owner of the website, while other pages might not be accessible if you sign in to the site, and some pages could be duplicates of visited pages. For instance, a lot of sites can be accessed via the web (www.example.com) as well as other than the www (example.com) version of the domain's name, even though the content is identical for both versions. When crawling, Google renders the page and it runs the JavaScript it discovers with the current version of Chrome, much like how your browser renders pages that you browse. It is essential to render since websites often depend on JavaScript for bringing content onto the page. Without rendering, Google may not be able to see the content. Crawling will depend on the ability of Google's crawlers to access the website. The most frequent issues related to Googlebot accessing websites include: Problems with the server that handles the website. Network Issues. The robots.txt directives block Googlebot from accessing the page. Indexing  After a page has been crawled, Google will attempt to determine what the content of the page is. This is known as indexing. It involves analyzing and processing the textual content as well as important attributes and tags of the content, like elements and alt attributes. images, videos, and much more. In the process of indexing, Google determines if a page is an actual duplicate of a web page or is canonical. The canonical page is the one that appears in the results of a search. To choose the canonical page, you first have to group the pages we've discovered on the internet that contain similar content. Then, we pick the one that's more representative of the entire group. The other pages within the group are variants that can be used in different ways, for instance, when a user is browsing using a mobile device or searching for a specific webpage from the cluster. Google also collects signals regarding the canonical website and its content, which can be used at the next stage, when we display the site in search results. Certain signals are the language used by that page's language, the nation the content is located in, and the accessibility of the site, among other factors. The information gathered regarding the canonical page as well as its cluster might be kept within the Google index, a massive database that is hosted on thousands of computers. The indexing process isn't 100% guaranteed. Every page Google processes will be included in the index. Indexing is also dependent on the contents of the page as well as the metadata associated with it. Common indexing issues are: The quality of the content on this page is poor. Robots' meta directives disallow indexing. The style of the website could hinder indexing. Search results for Serving When a user types in an inquiry, our systems scan the index for matching pages and then return the results we believe to be the most high-quality and relevant for the user. Relevance is determined by a variety of variables, which can include details such as the location of the user, their language, and the device (desktop or mobile). For instance, a search in the search engine for "bicycle repair shops" would give different results to users located in Paris compared to those from Hong Kong. The Search Console may inform you that a webpage has been indexed, but you won't find it in the search results. This could be due to: The content pages have no relevance to the users. The content is of poor quality. Robots' meta directives prevent serving.

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