Google Cloud Platform provides infrastructure as a service, platform as a service, and server-less computing environments.

Or

Google Cloud Platform is a set of Computing, Networking, Storage, Big Data, Machine Learning and Management services provided Google that runs on the same Cloud infrastructure that Google uses internally for its end-user products, such as Google Search, Gmail, Google Photos and YouTube.

Features of GCP:

So now look at some of the features of GCP what really gives it an upper hand over other vendors.

What are Google Cloud Platform (GCP) Services?

Google offers a wide range of Services. Following are the major Google Cloud Services:

1. Compute

2. Networking

3. Storage and

Databases

4. Big Data

5. Machine Learning

6. Identity & Security

7. Management and

8. Developer Tools

1. Compute: GCP provides a scalable range of computing options you can tailor to match your needs. It provides highly customizable virtual machines. and the option to deploy your code directly or via containers.

1. Google Compute Engine

2. Google App Engine

3. Google Kubernetes Engine

Kubernetes Engine (GKE):-Kubernetes Engine (GKE) is a managed, production-ready environment for deploying containerized applications. It brings our latest innovations in developer productivity, resource efficiency, automated operations, and open source flexibility to accelerate your time to market.

Launched in 2015, Kubernetes Engine builds on Google’s experience of running services like Gmail and YouTube in containers for over 12 years. Kubernetes Engine allows you to get up and running with Kubernetes in no time, by completely eliminating the need to install, manage, and operate your own Kubernetes clusters.

4. Google Cloud Container Registry:- Container Registry is a single place for your team to manage Dockers images, perform vulnerability analysis, and decide who can access what with fine-grained access control.

A Docker image is a file, comprised of multiple layers, used to execute code in a Docker container. … When the Docker user runs an image, it becomes one or multiple instances of that container. Docker is an open source OS-level virtualization software platform primarily designed for Linux and Windows.

5. Cloud Functions: – Google Cloud Functions is a server less execution environment for building and connecting cloud services. With Cloud Functions you write simple, single-purpose functions that are attached to events emitted from your cloud infrastructure and services.

2. Networking: The Storage domain includes services related to networking, it includes the following services

1. Google Virtual Private Cloud (VPC)

2. Google Cloud Load Balancing

3. Content Delivery Network

4. Google Cloud Interconnect

5. Google Cloud DNS

1. Google Virtual Private Cloud (VPC):-A virtual private cloud is an on-demand configurable pool of shared computing resources allocated within a public cloud environment, providing a certain level of isolation between the different organizations using the resources.

OR

Virtual Private Cloud (VPC) gives you the flexibility to scale and control how workloads connect regionally and globally. When you connect your on-premises or remote resources to GCP, you’ll have global access to your VPCs without needing to replicate connectivity or administrative policies in each region.

A VPC network, sometimes just called a “network,” is a virtual version of a physical network, like a data center network. It provides connectivity for your Compute Engine virtual machine (VM) instances, Kubernetes Engine clusters, App Engine Flex instances, and other resources in your project.

2. Google Cloud Load Balancing:-Cloud Load Balancing includes support for the latest application delivery protocols. It supports HTTP/2 with gRPC when connecting to backends and also is the control traffic related issues.

• There are two types of load balancers in Google Cloud Platform:
• Network Load Balancer and
• HTTP(s) Load Balancer.

 Note: – gRPC is a modern open source high performance RPC (Remote Procedure call) framework that can run in any environment. It can efficiently connect services in and across data centers.

3. Content Delivery Network:-A content delivery network (CDN) refers to a geographically distributed group of servers which work together to provide fast delivery of Internet content. A CDN allows for the quick transfer of assets needed for loading Internet content including HTML pages, javascript files, stylesheets, images, and videos. The popularity of CDN services continues to grow, and today the majority of web traffic is served through CDNs, including traffic from major sites like Facebook, Netflix, and Amazon.

Why Use a Content Delivery Network?-

CDNs (Content Delivery Networks) have changed the web hosting during the recent years. Rather than hosting your website on one server, the load is distributed across multiple systems. You can host static content such as videos, images, audio clips, CSS and JavaScript files.

Not every website needs a CDN but once you start getting more traffic, you should consider using a CDN that suit your needs. Google’s ranking factor also includes website loading time. Using a CDN not only reduces user waiting time but also increases your search engine rankings.

4. Google Cloud Interconnect:-Cloud Interconnect extends your on-premises network to Google’s network through a highly available, low latency connection. You can use Google Cloud Interconnect – Dedicated (Dedicated Interconnect) to connect directly to Google or use Google Cloud Interconnect – Partner (Partner Interconnect) to connect to Google through a supported service provider. 

5. Google Cloud DNS: –    Publish your domain names using Google’s infrastructure for production-quality, high-volume DNS services. Google’s global network of any cast name servers provide reliable, low-latency authoritative name lookups for your domains from anywhere in the world.
Notes:-Low latency describes a computer network that is optimized to process a very high volume of data messages with minimal delay (latency). These networks are designed to support operations that require near real-time access to rapidly changing data.

3. Big Data: – Big data is a term that describes the large volume of data – both structured and unstructured. Big data can be analyzed for insights that lead to better decisions and strategic business moves.

Big Data is also data but with a huge size of data. Big Data is a term used to describe a collection of data that is huge in size and yet growing exponentially with time. In short such data is so large and complex that none of the traditional data management tools are able to store it or process it efficiently.

The Storage domain includes services related to big data, it includes the following services

1. Google Big Query:–

Storing and querying massive datasets can be time consuming and expensive without the right hardware and infrastructure.

Big Query is an enterprise data warehouse that solves this problem by enabling super-fast SQL queries using the processing power of Google’s infrastructure. Simply move your data into Big Query and let us handle the hard work. You can control access to both the project and your data based on your business needs, such as giving others the ability to view or query your data.

Or

Big Query is a RESTful web service that enables interactive analysis of massive datasets working in conjunction with Google Storage. It is a serverless Platform as a Service that may be used complementarily with MapReduce.

Representational State Transfer (REST) is a software architectural style that defines a set of constraints to be used for creating Web services. Web services that conform to the REST architectural style, called RESTful Web services (RWS), provide interoperability between computer systems on the Internet.

2. Google Cloud Dataproc:–Google Cloud Dataproc is a cloud-based managed Apache Spark and Hadoop service offered on Google Cloud Platform.

3. Google Cloud Datalab:-Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models on Google Cloud .

4. Google Cloud Pub/Sub:-Cloud Pub/Sub brings the flexibility and reliability of enterprise message-oriented middleware to the cloud. At the same time, Cloud Pub/Sub is a scalable, durable event ingestion and delivery system that serves as a foundation for modern stream analytics pipelines.

5. Cloud AI:- The Storage domain includes services related to machine learning, it includes the following services-

1. Cloud Machine Learning:-Cloud Machine Learning Engine is a managed service that lets developers and data scientists build and run superior machine learning models in production. Cloud ML Engine offers training and prediction services, which can be used together or individually.

2. Vision API:-Cloud Vision API allows developers to easily integrate vision detection features within applications, including image labeling, face and landmark detection, optical character recognition (OCR), and tagging of explicit content. Cloud Auto ML Vision enables you to create a custom machine learning model for image labeling.

3. Speech API:–Google Cloud Speech-to-Text enables developers to convert audio to text by applying powerful neural network models in an easy-to-use API. The API recognizes 120 languages and variants to support your global user base. … It can process real-time streaming or prerecorded audio, using Google’s machine learning technology.

4. Natural Language API:–The Cloud Natural Language API provides natural language understanding technologies to developers, including sentiment analysis, entity analysis, entity sentiment analysis, content classification, and syntax analysis. … For information on which languages are supported by the Natural Language API.

5. Translation API:-Google Translate is a free multilingual machine translation service developed by Google, to translate text. It offers a website interface, mobile apps for Android and iOS, and an API that helps developers build browser extensions and software applications.

6. Jobs API:–Transform your job search and candidate matching capabilities with Cloud Talent Solution. …Talent Solution can interpret the vagueness of any job description, jobsearch query, or profile search query. … As Talent Solution learns what job seekers and employers are …

5. Machine Learning Identity & Security:- The Storage domain includes services related to security, it includes the following services-

1. Cloud Resource Manager:-Google Cloud Platform provides resource containers such as organizations, folders, and projects that allow you to group and hierarchically organize other GCP resources. This hierarchical organization lets you easily manage common aspects of your resources such as access control and configuration settings. Resource Manager enables you to programmatically manage these resource containers.

2. Cloud IAM (Identity and Access Management):-Cloud Identity and Access Management (Cloud IAM) enables you to create and manage permissions for Google Cloud Platform resources. Cloud IAM unifies access control for Cloud Platform services into a single system and presents a consistent set of operations.

A crucial part of cloud security involves managing user identities, their permissions, and resources they have access to.  This can be an extremely challenging task for organizations who may have users accessing public cloud resources from a number of different devices and networks.

Cloud IAM (Cloud Identity and Access Management) is a key part of an organization’s overall cyber security strategy when it comes to securing resources in the public cloud. Cloud IAM helps organizations manage access control by helping to define “who” has “what” access for “which” resource. The who are members, what are role and the resources are anything we want to grant permissions on in the public cloud.

3. Cloud Security Scanner:-

Cloud Security Scanner is a web security scanner for common vulnerabilities in App Engine, Compute Engine, and Google Kubernetes Engine applications. It can automatically scan and detect four common vulnerabilities, including cross-site-scripting (XSS), Flash injection, mixed content (HTTP in HTTPS), and outdated/insecure libraries. It enables early identification and delivers very low false-positive rates. You can easily set up, run, schedule, and manage security scans, and it is available at no additional charge for Google Cloud Platform users.

6. Management Tools: The Storage domain includes services related to monitoring and management, it includes the following services

1. Stack driver (Monitoring Tool):-Google Stack driver is a monitoring service that provides IT teams with performance data about applications and virtual machines running on the Google Cloud Platform and Amazon Web Services public cloud. … It is based on collected, an open source daemon that collects system and application performance metrics.

2. Logging: – Stack driver Logging allows you to store, search, analyze, monitor, and alert on log data and events from Google Cloud Platform and Amazon Web Services (AWS). Our API also allows ingestion of any custom log data from any source. Stack driver Logging is a fully managed service that performs at scale and can ingest application and system log data from thousands of VMs. Even better, you can analyze all that log data in real time.

 3. Error Reporting:–Error Reporting is a Beta feature for Google App Engine flexible environment, Google Compute Engine, and AWS EC2. You can report errors from your application by sending them directly to Stack driver Logging with proper formatting or by calling an Error Reporting API endpoint that sends them for you.

4. Trace Cloud Console:-Stack driver Trace is a distributed tracing system that collects latency data from your applications and displays it in the Google Cloud Platform Console. You can track how requests propagate through your application and receive detailed near real-time performance insights. Stack driver Trace automatically analyzes all of your application’s traces to generate in-depth latency reports to surface performance degradations, and can capture traces from all of your VMs, containers, or App Engine projects.

7. Developer Tools: The Storage domain includes services related to development, it includes the following services

• 1. Cloud SDK
  • 2. Deployment Manager
  • 3. Cloud Test Lab

1. Cloud SDK:-The Cloud SDK is a set of tools for Google Cloud Platform. It contains gcloud, gsutil, and bq command-line tools, which you can use to access Compute Engine, Cloud Storage, Big Query, and other products and services from the command-line. You can run these tools interactively or in your automated scripts.

2. Deployment Manager:-Deployment Manager is an infrastructure deployment service that automates the creation and management of Google Cloud Platform (GCP) resources.

3. Cloud Test Lab:- Google Cloud Test lab basically runs an automated tests in accordance with your app’s targeting criteria on several devices. Cloud Test Lab can run instrumentation tests that you write using Espresso or Robotium. You can also use the Cloud Test Lab Robo Test to simulate user actions and find crashes in your app

Azure is a cloud computing platform which was launched by Microsoft in February 2010. It is an open and flexible cloud platform which helps in development, data storage, service hosting, and service management. The Azure tool hosts web applications over the internet with the help of Microsoft data centers.

Types of Azure Clouds

There are mainly three types of clouds in Microsoft Azure are:

1. PAAS
2. SAAS
3. IASS

Azure as IaaS

IaaS(Infrastructure as a Service) is the foundational cloud platform layer. This Azure service is used by IT administrators for processing, storage, networks or any other fundamental computer operations. It allows users to run arbitrary software.

Advantages:

• It offers efficient design time portability
• It is advisable for the application which needs complete control
• IaaS offers quick transition of services to clouds
• The apparent benefit of laaS is that it frees you from the concerns of setting up many physical or virtual machines.
• Helps you to access, monitor and manage datacenters

Disadvantages of Iaas:

• Plenty of security risks from unpatched servers
• Some companies have defined processes for testing and updating on-premise servers vulnerabilities. This cannot be done with Azure.

Azure as PaaS

PaaS is a computing platform which includes an operating system, programming language execution environment, database or web services. This Azure service is used by developers and application providers.

As its name suggests, this platform is provided to the client to develop and deploy software. It allows the client to focus on application development instead of worrying about hardware and infrastructure. It also takes care of operating systems, networking and servers issues.

Advantages:

• The total cost is low as the resources are allocated on demand and servers are automatically added or subtracted.
• Azure is less vulnerable because servers are automatically checked for all known security issues
• The entire process is not visible to the developer, so it does not have a risk of a data breach

Disadvantages:

• Portability issues can occur when you use PaaS services
• There may be different environment at Azure, so the application needs to adapt accordingly.

Azure As SaaS

SaaS (Software as a Service) is software which is centrally hosted and managed. It is a single version of the application is used for all customers. You can scale out to multiple instances. This helps you to ensure the best performance in all locations. The software is licensed through a monthly or annual subscription. MS Exchange, Office, Dynamics are offered as a SaaS

Azure key Concepts

Azure Domains (Components)

Compute

It offers computing operations like app hosting, development, and deployment in Azure Platform. It has the following components:

• Virtual Machine: Allows you to deploy any language, workload in any operating system
• Virtual Machine Scale Sets: Allows you to create thousands of similar virtual machines in minutes
• Azure Container Service: Create a container hosting solution which is optimized for Azure. You scale and arrange applications using Kube, DC/OS, Swarm or Docker
• Azure Container Registry: This service store and manage container images across all types of Azure deployments
• Functions: Let’s you write code regardless of infrastructure and provisioning of servers. In the situation when your functions call rate scales up.
• Batch: Batch processing helps you scale to tens, hundreds or thousands of virtual machines and execute computer pipelines.
• Service Fabric: Simplify microservice-based application development and lifecycle management. It supports Java, PHP, Node.js, Python, and Ruby.

Storage

Azure store is a cloud storage solution for modern applications. It is designed to meet the needs of their customer’s demand for scalability. It allows you to store and process hundreds of terabytes of data. It has the following components:

• Blob Storage: Azure Blob storage is a service which stores unstructured data in the cloud as objects/blobs. You can store any type of text or binary data, such as a document, media file, or application installer.
• Queue Storage: It provides cloud messaging between application components. It delivers asynchronous messaging to establish communication between application components.
• File Storage: Using Azure File storage, you can migrate legacy applications. It relies on file shares to Azure quickly and without costly rewrites.
• Table Storage: Azure Table storage stores semi-structured NoSQL data in the cloud. It provides a key/attribute store with a schema-less design

Database

This category includes Database as a Service (DBaaS) which offers SQL and NoSQL tools. It also includes databases like Azure Cosmos DB and Azure Database for PostgreSQL. It has the following components:

• SQL Database: It is a relational database service in the Microsoft cloud based on the market-leading Microsoft SQL Server engine.
• DocumentDB: It is a fully managed NoSQL database service which is It built for fast and predictable performance and ease of development.
• Redis Cache: It is a secure and highly advanced key-value store. It stores data structures like strings, hashes, lists, etc.

Content Delivery Network

Content Delivery Network (CDN) caches static web content at strategically placed locations. This helps you to offer speed for delivering content to users. It has the following components:

• VPN Gateway: VPN Gateway sends encrypted traffic across a public connection.
• Traffic Manager: It helps you to control and allows you to do the distribution of user traffic for services like WebApps, VM, Azure, and cloud services in different Datacenters
• Express Route: Helps you to extend your on-premises networks into the Microsoft cloud over a dedicated private connection to Microsoft Azure, Office 365, and CRM Online.

Security + Identify sevices

It provides capabilities to identify and respond to cloud security threats. It also helps you to manage encryption keys and other sensitive assets. It has the following components:

• Key Vault: Azure Key Vault allows you to safeguard cryptographic keys and helps you to create secrets used by cloud applications and services.
• Azure Active Directory: Azure Active Directory and identity management service. This includes multi-factor authentication, device registration, etc.
• Azure AD B2C: Azure AD B2C is a cloud identity management solution for your consumer-facing web and mobile applications. It allows you to scales hundreds of millions of consumer identities.

Enterprise Integration Services:

• Service Bus: Service Bus is an information delivery service which works on the third-party communication system.
• SQL Server Stretch Database: This service helps you migrates any cold data securely and transparently to the Microsoft Azure cloud
• Azure AD Domain Services: It offers managed domain services like domain join, group policy, LDAP, etc. This authentication which is compatible with Windows Server Active Directory.
• Multi-Factor Authentication: Azure Multi-Factor Authentication (MFA) is two-step verification. It helps you to access data and applications to offers a simple sign-in process.

Monitoring + Management Services

These services allow easy management of Azure deployment.

• Azure Resource Manager: It makes it easy for you to manage and visualize resource in your app. You can even control who is your organization can act on the resources.
• Automation: Microsoft Azure Automation is a way to automate the manual, long-running, error-free, and constantly repeated tasks. These tasks are commonly performed in a cloud and enterprise environment.

Azure Networking

• Virtual Network: Perform Network isolation and segmentation. It offers filter and Route network traffic.
• Load Balancer: Offers high availability and network performance of any application. Load balance information Internet traffic to Virtual machines.
• Application Gateway: It is a dedicated virtual appliance that offers an Application Delivery Controller (ADC) as a service.
• Azure DNS: Azure DNS hosting service offers name resolution using Microsoft Azure infrastructure.

Web and Mobile Services:

• Web Apps: Web Apps allows you to build and host websites in the programming language of your choice without the need to manage its infrastructure.
• Mobile Apps: Mobile Apps Service offers a highly scalable, globally available mobile app development platform for users.
• API Apps: API apps make it easier to develop, host and consume APIs in the cloud and on-premises.
• Logic Apps: Logic Apps helps you to simplify and implement scalable integrations

Workflows in the cloud

It provides a visual designer to create and automate your process as a series of steps known as a workflow

• Notification Hubs: Azure Notification Hubs offers an easy-to-use, multi-platform, scaled-out push engine
• Event Hubs: Azure Event Hubs is data streaming platform which can manage millions of events per second. Data sent to an event hub can be transformed and stored using any real-time analytics offers batching/storage adapters.
• Azure Search: It is a cloud search-as-a-service solution which offers server and infrastructure management. It offers ready-to-use service that you can populate with your data. This can be used to add search to your web or mobile application.

Migration

Migration tools help an organization estimate workload migration costs. It also helps to perform the migration of workloads from your local data centers to the Azure cloud.

Traditional vs. Azure Cloud Model

Applications of Azure

Microsoft Azure is used in a broad spectrum of applications like:

• Infrastructure Services
• Mobile Apps
• Web Applications
• Cloud Services
• Storage, Backup, and Recovery
• Data Management
• Media Services

Advantages of Azure

Here, are advantages of using Azure:

• Azure infrastructure will cost-effectively enhance your business continuity strategy
• It allows you to access the application without buying a license for the individual machine
• Windows Azure offers the best solution for your data needs, from SQL database to blobs to tables
• Offers scalability, flexibility, and cost-effectiveness
• Helps you to maintain consistency across clouds with familiar tools and resources
• Allows you to extend data center with a consistent management toolset and familiar development and identity solutions.
• You can deploy premium virtual machines in minutes which also include Linux and Windows servers
• Helps you to scale your IT resources up and down based on your needs
• You are not required to run the high-powered and high-priced computer to run cloud computing’s web-based applications.
• You will not require processing power or hard disk space if you are using Azure
• Cloud computing offers virtually limitless storage
• If your personal computer or laptop crashes, all your data is still out there in the cloud, and it is still accessible
• Sharing documents leads directly to better collaboration
• If you change your device your computers, applications and documents follow you through the cloud

DisAdvantages of Azure

• Cloud computing is not possible if you can’t connect to the Internet
• Azure is a web-based application which requires a lot of bandwidth to download, as do large documents
• Web-based applications can sometimes be slower compared to accessing a similar software program on your desktop PC

Summary

• Cloud computing is a term referred to storing and accessing of data over the internet
• Azure is a cloud computing platform which was launched by Microsoft in February 2010
• There are mainly three types of clouds in Microsoft Azure: 1)PAAS 2) SAAS 3) IASS
• IaaS(Infrastructure as a Service) is the foundational cloud platform layer.
• PaaS is a computing platform which includes an operating system, programming language execution environment, database or web services
• SaaS (Software as a Service) is software which is centrally hosted and managed.
• Datacentres and regions, Azure portal, Resources, Resource groups, Resource Manager templates, Azure PowerShell, Azure command-line interface(CLI) are some of the key terms used in Azure
• Important components of Microsoft Azure are Compute, Storage, Database, Monitoring & management services, Content Delivery Network, Azure Networking, Web & Mobile services, etc.
• Traditional model used purpose-built hardware while Azure cloud model uses Industry-standard hardware
• Important applications of Microsoft Azure are: Infrastructure Services, Mobile Apps, Web Applications, Cloud Services, Storage, Backup, and Recovery, Data Management, and Media Services
• The biggest advantage of Microsoft Azure infrastructure is that it will cost-effectively enhance your business continuity strategy
• Web-based applications like Azure can sometimes be slower compared to accessing a similar software program on your desktop PC

Big Data and Cloud Computing are some of the important leading technologies which are used in today’s scenario. With the help of these technologies, business, education, research, healthcare, and development, etc. are leading rapidly and will offer different advantages to enhance their areas with tricks and techniques. So, in the Big Data Vs. Cloud computing, we will study about the difference between Big data and Cloud computing.

What is Big Data

Big Data is defined as a set of large data (structured or unstructured) that is used to collect information from it.

In Big Data, there is a large amount of data produced by the companies in every second which needs to be processed so, big data will gather, store and organize data, which will be further analyzed by the data analysts.

In other terms, we can say that Big data is the huge amount of data, which can process valuable information.

What is Cloud Computing

Cloud computing offers a virtual environment in which the information is gathered via the internet. This reduces the use of a physical server like most of the data can be stored in cloud separately in the cloud with the help of virtualization. The cloud also provides platforms that are used to share a computer competency for running programs.

Big Data vs Cloud Computing

1. Concept: – In cloud computing, we can fetch and store the data from anywhere at any time, means it is available 24/7.

However, Big data is the huge amount of data that will process to extract the important information.

• Characteristics: – Cloud computing offers service over the internet, which can be:
• Software as a service (SaaS)
• Platform as a service (PaaS)
• Infrastructure as a service (IaaS)

Whereas the important characteristics of Big Data are Velocity, Variety, Volume.

• Accessibility: – Cloud computing offers universal access to services. 

However, big data solves technical problems and offers better results.

• When to use: – A customer can move to cloud computing when they require rapid deployment and scaling of the applications. The application deals with highly sensitive data and needs strict consent; one should keep things on the cloud.

Big data solve specific problem statement, which is related to huge data sets and does not deal with small data sets.

• Cost: – Cloud computing requires less maintenance cost due to the centralized platform no upfront cost and disaster safe implementation.

However, Big Data is a robust ecosystem, highly scalable, and cost-effective.

• Job roles and responsibility: – The developers and office workers in an organization are the users of the cloud. Whereas, in Big data, the data analyst is responsible for analyzing the data and possible future trends
• Types and trends: – Cloud computing are of many types:
• Public cloud
• Private cloud
• Hybrid cloud
• Community cloud

          Trends in Big Data technology are Hadoop, HDFS, and MapReduce.

• Vendors: – Cloud computing vendors are:
• Amazon web service
• Microsoft
• Dell
• Apple
• IBM

However, Big data Vendors are:

• Apache
• Cloudera
• MapR
• Hortonworks

Big Data vs Cloud Computing: Comparison Chart

Grid computing is a distributed structure of a large number of computers connected to solve a complicated problem. In grid computing, servers and computers run independently and are loosely connected by the Internet. Computers may connect directly or through scheduling systems.

In other words, Grid Computing involves a large number of computer which are connected parallel and makes a computer cluster.

Grid computing is used in various types of applications such as mathematical, scientific, and educational tasks via various computing resources.

Grid computing is a processor architecture that integrates computer resources from various domains to achieve a primary goal. The computers on the network will work together in grid computing on a project, thus acting as a supercomputer.

Grid systems are mainly designed for resource sharing by Distributed and cluster computing on a large scale. It divides the complex tasks into smaller pieces that are distributed to the CPUs and keeps in the grid.

What is Cloud Computing?

 Cloud Computing is defined as the on-demand facility of computer power, database storage, applications, and other IT resources through the internet. It provides a solution for IT infrastructure at a low price.

In simple words, cloud computing means storing and accessing the data via the internet instead of the computer’s hard drive.

Cloud computing is a pay-per-use model.

Grid Computing Vs Cloud Computing

1. Main objective: – The main objective of cloud computing is to offer the Service at a lower rate. It also offers scalability and flexibility so that the customer efficiently uses cloud computing with increased security and availability.

However, the grid computing objective is to focus on the network to solve complicated problems; it also provides a computer as a utility.

2. Types and Division: – The types of cloud computing are public clouds, private clouds, community clouds, and hybrid clouds.

However, Grid computing is a distributed computing system so its types are distributed information system and distributed pervasive systems.

• Use and Security: – ALarge amount of data is stored in the cloud. So it offers security according to it. The data which is stored on the cloud is secured and only be access with the help of credentials.

Grid computing relates to idol energy in computers and is mainly used for something sensible.

• Basis of Dependency: – Cloud Computing is totally dependent on the internal. The cloud offers high security along with high performance.

Grid computing can do its work continuously, even if a computer stops or failure. The other computer will pick the working and make the system more efficient and reliable.

• Difference and Similarity: – cloud computing and grid computing are different from each other in some terms like architecture, business model, and interoperability.

The similarity between cloud computing and grid computing is both are network-based technologies

   .6. Space and Storage: –  In cloud computing, backup and restores the data is easy due to of its fast data processors. The updation in cloud computing are automatic   and efficient.

However, in grid computing, space is saved, and access to additional resources can be done.

7.Remote Usage: – In cloud computing, management of computing resources are within a single location, which is located at a different place.

 However, in grid computing, there is a distributed system where the resources are allocated at various locations, and can be located from various sites.

8. Resource Requirements: – Grid computing requires more resources, and cloud computing doesn’t access the resource directly; it gets resources via the internet.

9. Problem-Solving Techniques: – For job scheduling, grid computing uses all kinds of computing resources. In grid computing, the big task is split into multiple tasks, which is solved by various computers as the work assigns to a particular computer.

Cloud computing has resources that are pooling via grouping resources and needs a base from a cluster of servers.

10. Services and Capabilities: – Academic researchers mainly used Grid computing and have the ability to handle a large set of job that are complex and includes a large collection of data.

Cloud computing is totally internet-based computing. The cloud offers various types of services like management of data, job queries, the security of data, etc. It removes the cost of purchasing new hardware and software which are required to build applications.

11. Interoperability: – In grid computing, interoperability can be handled quickly, but cloud computing does not support interoperability.

Grid Computing Vs. Cloud Computing: Comparison Chart                              

Introduction to Cloud Cube

The Cloud cube model helps to categorize the network of cloud-based on the four-dimensional factor. The main motive of the cloud model is to secure and protect the cloud network. The cloud model supports to choose cloud creation for the security association. It also helps IT managers, organizations, and business leaders by offering a safe and protected network.

Security is an essential aspect for cloud users, and most of the cloud providers understand it. The customer should also take care of that; the selected cloud formation fulfills the regulatory and location needs. They also need one thing in their mind that if cloud providers stop offering the services, where else they can move.

There are three service models which consists of:

• SaaS
• PaaS
• IaaS

There are four deployment models also.

• Public cloud
• Private cloud
• Community cloud
• Hybrid cloud

The models are flexible, user-friendly, and offer many benefits to cloud users.

The following figure shows the cloud layers when the clouds operates.

How is Data Secured in the Cloud Cube Model?

There are various steps and points you should keep in your mind while securing your data in a cloud cube model.

1. The categorization of the data, the user must know what rules must be applied to secure and protect it.
2. It should make sure that the data exist only in particular trust levels.
3. It should examine that what regulatory compliance and constraints are applicable. For example: – The data is kept in a specific limit and whether it has to stay in the secure harbor or not.

  When the data is categorized and can put in the needed zone, the assigned person is in a position to decide the following aspects-

• The processes and data, which are to be shift in the cloud.
• At what level the customer wants to operate in the cloud. Maybe it is infrastructure, platform, and software.
• The cloud formations fulfill the requirements.
• In a cloud, the level of operation can be different as per the requirement.

The following figure shows the cloud layers, where the cloud operates:

Dimensions of Cloud Cube Model 

There are following four dimensions in the Cloud cube model.

• Internal/External
• Proprietary/open
• De-perimeterized/perimeterized
• Insourced/outsourced dimension

Internal/External: – Internal/External is the most common form of the cloud. It describes the physical location of the data. It agrees whether the data exists inside or outside of your organization’s limit. In this, the data that is stored by the help of private cloud deployment will be referred to as internal, and the data outside the cloud will be referred to as external.

Proprietary/Open: – The second dimension of cloud formation is proprietary/open. It defines the state of ownership of the cloud technology and interfaces. It also defines the level of incomparability while enabling data transportability between the system and forms of cloud.

The meaning of proprietary dimension means that the organization is offering the service in a secure and protected manner under their ownership.

The open dimension using such type of technology in which more suppliers are allowed. In addition to that, the user is not constrained in being able to share the data and cooperate with selected partners using open technology.

De-perimeterized/Perimeterized: – To reach de-perimeterized/perimeterized form, the user requires Jericho forum and collaboration oriented architecture commandments. It defines whether you are working inside your traditional mindset or outside it.

 The meaning Perimeterized dimension is continuing to work within the traditional boundary, orphan signaled by network firewalls. With the support of VPN and the operation of the virtual server in your IP domain, the customer can expand the organization’s boundary into the external cloud computing domain.

De-perimeterized is the system which is designed on the principles outlined in the Jericho forum’s commandments. In this, data is encapsulated with metadata and structure, which will again support to secure the data and control the inappropriate usage.

Insourced/Outsourced: – Insourced/outsourced is the fourth dimension of the cloud cube model. In the outsourced dimension, services are offered by the third party, and in the insourced dimension, the services are offered by the own staff.

In some organizations with traditional bandwidth software or hardware, providers will run smoothly when they become cloud service providers.

Organizations exploring to process cloud services should have the capability to set a legally binding collaboration agreement. In this, an organization must ensure that the data is removed from the service provider’s infrastructure.

• MCC refers to an infrastructure where both the data storage and data processing happen outside of the mobile device.
• Mobile cloud applications move the computing power and data storage away from the mobile devices and into powerful and centralized computing platforms located in clouds, which are then accessed over the wireless connection based on a thin native client.
• MOBILE CLOUD COMPUTING = MOBILE COMPUTING + CLOUD COMPUTING
  • Mobile devices face many resource challenges (battery life, storage, bandwidth etc.)
  • Cloud computing offers advantages to users by allowing them to use infrastructure, platforms and software by cloud providers at low cost and elastically in an on-demand fashion.
  • Mobile cloud computing provides mobile users with data storage and processing services in clouds, obviating the need to have a powerful device configuration (e.g. CPU speed, memory capacity etc), as all resource-intensive computing can be performed in the cloud.

PRINCIPLES OF MOBILE CLOUD COMPUTING

• Mobile cloud computing is a combination of mobile computing, cloud computing and mobile Internet. It can be stated as availability of cloud computing facilities in the mobile environment. It integrates the advantages of all the three technologies and can thus be called as cloud computing for mobiles. Mobile cloud computing is a new model where the data processing and storage is moved from mobile devices to powerful and centralized computing platforms located in clouds. These platforms can then be accessed through wireless connections via web browsers on the mobile devices. This is similar to cloud computing, but the client side has changed to make it viable for mobile phones, but the main concept behind it is still cloud computing.

APPLICATIONS:-

• Mobile Commerce.
  • Mobile HealthCare.
  • Mobile Learning.
  • Mobile Gaming.

ADVANTAGES:-

• Extending battery lifetime
  • Improving data storage capacity and processing power
  • Improving reliability and availability
  • Dynamic provisioning
  • Scalability
  • Multi-tenancy
  • Ease of Integration

Mobile communication issues:

• Low bandwidth: One of the biggest issues, because the radio resource for wireless networks is much more scarce than wired networks
  • Service availability: Mobile users may not be able to connect to the cloud to obtain a service due to traffic congestion, network failures, mobile signal strength problems
  • Heterogeneity: Handling wireless connectivity with highly heterogeneous networks to satisfy MCC requirements (always-on connectivity, on-demand scalability, energy efficiency) is a difficult problem

Cloudlet Host

The Cloudlet Host is a physical server that hosts

• 1) a discovery service that broadcasts the cloudlet IP address and port to allow mobile devices to find it.
•  2) The Base VM Image that is used for VM synthesis
• 3) a Cloudlet Server that handles code offload in the form of application overlays, performs VM synthesis and starts guest  VM instances with the resulting VM images, and
•  4) a VM Manager that serves as a host for all guest VM instances that contain the computation-intensive server component of the corresponding mobile app.

Mobile Client

The Mobile Client is a handheld or wearable device that host

1) the Cloudlet Client app that discovers cloudlets and uploads application overlays to the cloudlet and

2) a set of Cloudlet-Ready Apps that operate as clients of the server code running in  the cloudlet. The Mobile Client stores an application overlay for each cloudlet-ready app that a user would conceivably want to execute and for which computation offloading is appropriate. Each application overlay is generated from the same Base VM Image that resides in the cloudlet

The management of the cloud means the management of the data with the help of software technologies which are used to design and monitors application. There are several tools which we can use for managing the cloud computing based resources. These resources are working properly with users and other services.

There are several strategies of cloud management which involves many tasks such as performance monitoring, security and, compliant.  IT services include complex management tasks such as maintaining the availability of resources and providing completely functional software it also helps to implement standardized security controls and procedures. For higher security company provides some specific tools which help to manage the cloud.

2. Types of Cloud Provisioning

Here, is the list of Cloud computing provisioning:

• User self-Provisioning
• Dynamic Provisioning
• Advanced Provisioning

i. User self-provisioning

It is the cloud service purchase from the other provider. It can be made from a web, console interface.

ii. Dynamic provisioning

When the customer is in need of resources the provider allocates it. The provider has a right to discontinue when they are no longer in use, the customer is charged on a usage basis.

iii. Advanced provisioning

A pre-determined amount of resource contract by the customer in advance. Here the customer pays a flat fee or an advanced fee.

There are lots of tools which can use to manage the cloud services. These tools help to create a virtual pool of resources. Moreover, it provides a portal which will help to enhance the security services. There are several more benefits of it such as resource allocation, tracking, and billing. The cloud environment is highly virtualized and organized as private clouds are source driven.

Cloud Management Benefits

Following are the advantages of Cloud Computing Management:

Cloud Computing Benefits

i. Quick Delivery Time

Nowadays customers are in need of rapid delivery which provides with the help of proper management. The customer will choose the service only if it is quick and easy to use. The cloud computing team provides instant delivery so that their customers are satisfied and this is done with the help of proper management.

ii. Flexibility

Customers demand various facilities and want CPU, memory, disk space, or network configuration. These facilities should be customer friendly and should provide maximum flexibility to the customer. The customer can modify what they need to self-service provisioning and eliminates costly hardware. Cloud management also provides flexibility so that the customer has to pay only for what they have used.

iii. Security

For complete management there should be proper security otherwise the management is incomplete. Therefore, cloud companies provide proper security, firewall, and confidentiality. This makes all the files, programs, and other data secure on site. If the customer is remotely accessing the data there is a chance of some cybercrime. So the companies are also taking actions regarding this.

iv. Economical

With the help of problem management, cloud providers try to keep the price as low as possible. As Cloud Computing is for small-scale as well as large-scale organizations so the prices low to implement the cloud-based server.

Cloud Management Tools

For organized cloud management there are specialized tools which are helpful for the customer as well as the seller. These tools help to monitor, manage cost, provide security and improve the capabilities of the Cloud. There are various companies which use various tools for the management.

Some of the companies and their tools are mentioned below-

• AWS
• Google
• Microsoft Azure

i. Amazon Web Services

Amazon Web Services provides a facility for the user to access and modify the instances of the cloud with the help of command line interface.

ii. Google

It provides Google Cloud Platform (GCP) which is a monitoring and logging tools. In addition, Google Stackdriver provides performance data for virtual machines and applications.

iii. Microsoft Azure

Microsoft has an Azure site recovery tool which helps administrators to automatically replicate VMs.

There are several private cloud management tools which are beneficial too. The companies use these private cloud management tools which include specific management software. This software can be VM Turbo Operations Managers and Embotics VCommander. These tools offer sophisticated software framework to manage the private and hybrid cloud.

Components of Cloud Computing Management

There are several components which are used to manage the cloud for automation and orchestration such as application migration, instances, and configuration management. The components which use to monitor the performance are storage, network, application, and computer.

The components which use to govern and provide compliance for this are audits, service and resource governance, etc.

Cloud Management Security

The security is one of the important aspects in the cloud management. The security concern can be faced by either the customer or the cloud provider. Both the host and the customer have equal responsibility for securing data and proper management. The user can protect the data by putting strong passwords and authentication measures. While the Cloud provider can protect the data by ensuring that there is no unauthorized access.

Storage Devices

Storage devices are of two types:

1. Block storage device
2. File storage device

Block storage device: – The block storage devices permit raw storage to the clients. These raw storages are divided to create volumes.

• File storage device: – The file storage devices provide storage to the clients in the form of files, maintaining its file system. This is achieved as a network attached storage (NAS).

Cloud Storage Classes

Cloud storage can be classified into two categories

• Managed cloud storage
• Unmanaged cloud storage

Managed cloud storage: – Managedcloud storage provides online-space-storage. The cloud-managed storage system tends to be a blank disk for the user to be able to partition and format.

 Unmanaged cloud storage: – Unmanaged cloud storage ensures that the customer’s data is preconfigured. The consumer cannot format, install their own file system, or alter the properties of the ride.

Creating cloud storage system: – The cloud storage system holds various copies of data on multiple servers at multiple locations. If one system fails, then it is necessary only to change the pointer to the location, where the object is stored.

The cloud providers can use data virtualization software such as Storage-GRID to integrate storage resources into cloud storage systems. It designs a virtualization layer that fetches storage from various storage devices into a single management system. It can also handle information over the network from CIFS and NFS file systems. The following figure shows the storage-GRID virtualizing the storage into the storage cloud.

Virtual Storage Containers

The virtual storage container provides high-performance cloud storage systems. The machine, files, and other objects ‘ logical unit number (LUN) are generated in virtual storage containers.

 The figure below shows a virtual storage container that defines a domain for cloud storage.

Challenges

Storing the data in the cloud is not an easy task. Apart from its flexibility and convenience, it also has various challenges faced by the customers. The customer must be able to:

• Provide supplementary storage on demand.
• Know and limit the stored data’s physical location.
• Check how data erased.
• Have access to a recorded data storage hardware disposal system.
• Have administration access control over data.

Amazon web service is a platform that offers flexible, reliable, scalable, easy-to-use and cost-effective cloud computing solutions.

AWS is a comprehensive, easy to use computing platform offered Amazon. The platform is developed with a combination of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS) offerings.

History of AWS

• 2002- AWS services launched
• 2006- Launched its cloud products
• 2012- Holds first customer event
• 2015- Reveals revenues achieved of $4.6 billion
• 2016- Surpassed $10 billon revenue target
• 2016- Release snowball and snowmobile
• 2019- Offers nearly 100 cloud services

Important AWS Services

Amazon Web Services offers a wide range of different business purpose global cloud-based products. The products include storage, databases, analytics, networking, mobile, development tools, enterprise applications, with a pay-as-you-go pricing model.

Here, are essential AWS services.

AWS Compute Services

Here, are Cloud Compute Services offered by Amazon:

1. EC2(Elastic Compute Cloud) – EC2 is a virtual machine in the cloud on which you have OS level control. You can run this cloud server whenever you want.
2. LightSail -This cloud computing tool automatically deploys and manages the computer, storage, and networking capabilities required to run your applications.
3. Elastic Beanstalk —  The tool offers automated deployment and provisioning of resources like a highly scalable production website.
4. EKS (Elastic Container Service for Kubernetes) — The tool allows you toKubernetes on Amazon cloud environment without installation.
5. AWS Lambda — ThisAWS service allows you to run functions in the cloud. The tool is a big cost saver for you as you to pay only when your functions execute.

Migration

Migration services used to transfer data physically between your datacenter and AWS.

1. DMS (Database Migration Service) -DMS service can be used to migrate on-site databases to AWS. It helps you to migrate from one type of database to another — for example, Oracle to MySQL.
2. SMS (Server Migration Service) - SMS migration services allows you to migrate on-site servers to AWS easily and quickly.
3. Snowball — Snowball is a small application which allows you to transfer terabytes of data inside and outside of AWS environment.

Storage

1. Amazon Glacier- It is an extremely low-cost storage service. It offers secure and fast storage for data archiving and backup.
2. Amazon Elastic Block Store (EBS)- It provides block-level storage to use with Amazon EC2 instances. Amazon Elastic Block Store volumes are network-attached and remain independent from the life of an instance.
3. AWS Storage Gateway- This AWS service is connecting on-premises software applications with cloud-based storage. It offers secure integration between the company’s on-premises and AWS’s storage infrastructure.

Security Services

1. IAM (Identity and Access Management) —  IAM is a secure cloud security service which helps you to manage users, assign policies, form groups to manage multiple users.
2. Inspector — It is an agent that you can install on your virtual machines, which reports any security vulnerabilities.
3. Certificate Manager — The service offers free SSL certificates for your domains that are managed by Route53.
4. WAF (Web Application Firewall) — WAF security service offers application-level protectionand allows you to block SQL injection and helps you to block cross-site scripting attacks.
5. Cloud Directory — This service allows you to create flexible, cloud-native directories for managinghierarchies of data along multiple dimensions.
6. KMS (Key Management Service) — It is a managed service. This security service helps you to create and control the encryption keyswhich allows you to encrypt your data.
7. Organizations — You can create groups ofAWS accounts using this service to manages security and automation settings.
8. Shield — Shield is managedDDoS (Distributed Denial of Service protection service). It offers safeguards against web applications running on AWS.
9. Macie — It offers a data visibility security service which helps classify and protect your sensitive critical content.
10. GuardDuty —It offers threat detectionto protect your AWS accounts and workloads.

Database Services

1. Amazon RDS- ThisDatabase AWS service is easy to set up, operate, and scale a relational database in the cloud.
2. Amazon DynamoDB- It is a fast, fully managed NoSQL database service. It is a simple service which allow cost-effective storage and retrieval of data. It also allows you to serve any level of request traffic.
3. Amazon ElastiCache- It is a web service which makes it easy to deploy, operate, and scale an in-memory cache in the cloud.
4. Neptune- It is a fast, reliable and scalable graph database service.
5. Amazon RedShift - It is Amazon’s data warehousing solution which you can use to perform complex OLAP queries.

Analytics

1. Athena — This analytics service allows permSQL queries on your S3 bucket to find files.
2. CloudSearch — You should use this AWS service to create a fully managed search engine for your website.
3. ElasticSearch — It is similar to CloudSearch. However, it offers more features like application monitoring.
4. Kinesis — This AWS analytics service helps you to stream and analyzing real-time data at massive scale.
5. QuickSight —It is a business analytics tool. It helps you to create visualizations in a dashboard for data in Amazon Web Services. For example, S3, DynamoDB, etc.
6. EMR (Elastic Map Reduce) —This AWS analytics service mainly used for big data processing like Spark, Splunk, Hadoop, etc.
7. Data Pipeline — Allows you to move data from one place to another. For example from DynamoDB to S3.

Management Services

1. CloudWatch — Cloud watch helps you to monitor AWS environments like EC2, RDS instances, and CPU utilization. It also triggers alarms depends on various metrics.
2. CloudFormation — It is a way of turning infrastructure into the cloud. You can use templates for providing a whole production environment in minutes.
3. CloudTrail — It offers an easy method of auditing AWS resources. It helps you to log all changes.
4. OpsWorks — The service allows you to automated Chef/Puppet deployments on AWS environment.
5. Config — This AWS service monitors your environment. The tool sends alerts about changes when you break certain defined configurations.
6. Service Catalog — This service helps large enterprises to authorize which services user will be used and which won’t.
7. AWS Auto Scaling — The service allows you to automatically scale your resources up and down based on given CloudWatch metrics.
8. Systems Manager — This AWS service allows you to group your resources. It allows you to identify issues and act on them.
9. Managed Services—It offers management of your AWS infrastructure which allows you to focus on your applications.

Internet of Things

1. IoT Core— It is a managed cloud AWS service. The service allows connected devices like cars, light bulbs, sensor grids, to securely interact with cloud applications and other devices.
2. IoT Device Management — It allows you to manage your IoT devices at any scale.
3. IoT Analytics — This AWS IOT service is helpful to perform analysis on data collected by your IoT devices.
4. Amazon FreeRTOS — This real-time operating system for microcontrollers helps you to connect IoT devices in the local server or into the cloud.

Application Services

1. Step Functions — It is a way of visualizing what’s going inside your application and what different microservices it is using.
2. SWF (Simple Workflow Service) — The service helps you to coordinate both automated tasks and human-led tasks.
3. SNS (Simple Notification Service) — You can use this service to send you notifications in the form of email and SMS based on given AWS services.
4. SQS (Simple Queue Service) — Use this AWS service to decouple your applications. It is a pull-based service.
5. Elastic Transcoder — This AWS service tool helps you to changes a video’s format and resolution to support various devices like tablets, smartphones, and laptops of different resolutions.

Deployment and Management

1. AWS CloudTrail: The services records AWS API calls and send backlog files to you.
2. Amazon CloudWatch: The tools monitor AWS resources like Amazon EC2 and Amazon RDS DB Instances. It also allows you to monitor custom metrics created by user’s applications and services.
3. AWS CloudHSM: This AWS service helps you meet corporate, regulatory, and contractual, compliance requirements for maintaining data security by using the Hardware Security Module(HSM) appliances inside the AWS environment.

Developer Tools

1. CodeStar — Codestar is a cloud-based service for creating, managing, and working with various software development projects on AWS.
2. CodeCommit —  It is AWS’s version control servicewhich allows you tostore your code and other assets privately in the cloud.
3. CodeBuild — This Amazon developer service help you to automates the process of building and compilingyour code.
4. CodeDeploy — It is a way of deploying your code in EC2 instances automatically.
5. CodePipeline — It helps you create a deployment pipeline like testing, building, testing, authentication, deployment on development and production environments.
6. Cloud9 —It is an Integrated Development Environment for writing, running, and debugging code in the cloud.

Mobile Services

1. Mobile Hub — Allows you to add, configure and design features for mobile apps.
2. Cognito — Allows users to signup using his or her social identity.
3. Device Farm — Device farm helps you to improve the quality of apps by quickly testing hundreds of mobile devices.
4. AWS AppSync —It is a fully managed GraphQL service that offers real-time data synchronization and offline programming features.

Business Productivity

1. Alexa for Business — It empowers your organization with voice, using Alexa. It will help you to Allows you to build custom voice skills for your organization.
2. Chime — Can be used for online meeting and video conferencing.
3. WorkDocs — Helps to store documents in the cloud
4. WorkMail — Allows you to send and receive business emails.

Desktop & App Streaming

1. WorkSpaces — Workspace is a VDI(Virtual Desktop Infrastructure). It allows you to use remote desktops in the cloud.
2. AppStream — A way ofstreaming desktop applicationsto your users in the web browser. For example, using MS Word in Google Chrome.

Artificial Intelligence

1. Lex — Lex tool helps you to build chatbots quickly.
2. Polly —  It is AWS’s text-to-speech service allows you to create audio versions of your notes.
3. Rekognition  — It is AWS’s face recognition service. This AWS service helps you to recognize faces and object in images and videos.
4. SageMaker — Sagemaker allows you to build, train, and deploy machine learning models at any scale.
5. Transcribe —  It is AWS’s speech-to-text service that offers high-quality and affordable transcriptions.
6. Translate — It is a very similar tool to Google Translate which allows you to translate text in one language to another.

AR & VR (Augmented Reality & Virtual Reality)

1. Sumerian — Sumerian is a set of tool for offering high-quality virtual reality (VR) experiences on the web. The service allows you to create interactive 3D scenes and publish it as a website for users to access.

Customer Engagement

1. Amazon Connect — Amazon Connect allows you to create your customer care centerin the cloud.
2. Pinpoint — Pinpoint helps you to understand your users and engage with them.
3. SES (Simple Email Service) — Helps you to send bulkemails to your customers at a relatively cost-effective price.

Game Development

1. GameLift– It is a service which is managed by AWS. You can use this service to host dedicated game servers. It allows you to scale seamlessly without taking your game offline.

Applications of AWS services

Amazon Web services are widely used for various computing purposes like:

• Web site hosting
• Application hosting/SaaS hosting
• Media Sharing (Image/ Video)
• Mobile and Social Applications
• Content delivery and Media Distribution
• Storage, backup, and disaster recovery
• Development and test environments
• Academic Computing
• Search Engines
• Social Networking

Companies using AWS

• Instagram
• Zoopla
• Smugmug
• Pinterest
• Netflix
• Dropbox
• Etsy
• Talkbox
• Playfish
• Ftopia

Advantages of AWS

Following are the pros of using AWS services:

• AWS allows organizations to use the already familiar programming models, operating systems, databases, and architectures.
• It is a cost-effective service that allows you to pay only for what you use, without any up-front or long-term commitments.
• You will not require to spend money on running and maintaining data centers.
• Offers fast deployments
• You can easily add or remove capacity.
• You are allowed cloud access quickly with limitless capacity.
• Total Cost of Ownership is very low compared to any private/dedicated servers.
• Offers Centralized Billing and management
• Offers Hybrid Capabilities
• Allows you to deploy your application in multiple regions around the world with just a few clicks

Disadvantages of AWS

• If you need more immediate or intensive assistance, you’ll have to opt for paid support packages.
• Amazon Web Services may have some common cloud computing issues when you move to a cloud. For example, downtime, limited control, and backup protection.
• AWS sets default limits on resources which differ from region to region. These resources consist of images, volumes, and snapshots.
• Hardware-level changes happen to your application which may not offer the best performance and usage of your applications.

Best practices of AWS

• You need to design for failure, but nothing will fail.
• It’s important to decouple all your components before using AWS services.
• You need to keep dynamic data closer to compute and static data closer to the user.
• It’s important to know security and performance tradeoffs.
• Pay for computing capacity by the hourly payment method.
• Make a habit of a one-time payment for each instance you want to reserve and to receive a significant discount on the hourly charge.

1. Amazon Web Service (AWS)
2. Microsoft Azure
3. Google Cloud Platform
4. IBM Cloud Services
5. Adobe Creative Cloud
6. Kamatera
7. VMware
8. Rackspace
9. Red Hat
10. Salesforce
11. Oracle Cloud
12. SAP
13. Verizon Cloud
14. Navisite
15. Dropbox

many more..

Amazon Web Services (AWS)

Amazon Web Services is a cloud computing platform which provides services such as compute power, database storage, content delivery and many other functions which will help to integrate a business. The Amazon Web Services is flexible, scalable, and reliable and due to this many companies are implementing it in their work. There is no upfront cost and the customer has to pay only for what they have used. It is one of the leading cloud service providers among all.

Cloud Service Providers – AWS

With the help of the internet, the customer can access highly durable storage such as Amazon Glacier, Amazon S3, and Amazon EBS. It also has a high-performance database such as Amazon Redshift, Amazon Dynamo DB, Amazon ElastiCache and Amazon RDS.

Microsoft Azure

Microsoft Azure is a cloud computing service which is used for building testing deploying and managing the application. This process is done in a global network of the Microsoft-managed data centre. It is private as well as a public cloud platform. It uses virtualization which differentiates the coupling between the operating system and CPU with the help of an abstraction layer known as a hypervisor.

This hypervisor emulates all the functionality of the physical machine such as hardware and server into a virtual one. There is numerous amount of virtual machine available and each virtual machine can run many operating systems.

In the data centre of Microsoft, there are many servers and each server consists of a hypervisor through which multiple virtual machines can operate. With the help of Azure, it is easy for developers and IT professionals to manage and deploy their applications and services.

Google Cloud Platform

Google cloud platform is one of the leading Cloud Computing services which are offered by Google and it runs on the same infrastructure that Google uses for its end-user products. The Google cloud platform is basically used for Google search and YouTube. There are various services offered by Google Cloud such as data analysis, machine learning, and data storage.

Cloud Service Providers – Google Cloud Platform

The data stored in Google Cloud is secure and can access easily. It offers varieties of services from infrastructure as a service to platform as a service. Google also provides a strong commitment to security and stability. With the help of the Google cloud platform, the user is free to think about the code and the feature which are needed to develop without worrying about the operations side.

Here most of the services fully manage and details quite easy for the customer to concentrate on their work. In this, machine learning and the use of API are very easy. The API also helps in speech detection language translation very easily. So it prefers among the customers.

IBM Cloud Services

IBM cloud offers services such as platform as a service and infrastructure as a service. This cloud organization can deploy and access its resources such as storage networking and compute power with the help of internet. There are several tools which help the customer to draw on deep industry expertise.

Cloud Service Providers – IBM Cloud Services

The speed and agility of the cloud fulfil the requirement of the customer and make them feel satisfied. A customer using IBM cloud can easily find growth opportunities, generating new revenue schemes and improving the operational efficiency. The uses of IBM cloud don’t have many barriers as compared to traditional technologies.

IBM cloud eliminates the complex problem and the problems which face by large companies. IBM Cloud computing services are also helping home appliance manufacturer, retailer, and medical supply businesses. It uses in because it offers the best services with the price as low as possible.

Adobe Creative Cloud

Adobe creative cloud provides the best experience of apps services design photography and web. The Adobe cloud services provide tutorials and templates with which a beginner can easily access the cloud and can start using it. It provides many facilities to the beginner as well as professionals for easy access to the cloud.

It consists of many applications and services that provide access to a collection of software which uses for video editing, web development, photography, and graphic designs. There are mobile applications as well as computer applications which can use by the customers.

Cloud Service Providers – Adobe Creative Cloud

Creative Cloud allows you to work from anywhere and from any device as the files can save to the cloud and can access at any time from anywhere. Creative Cloud was the first host on Amazon Web Services but as per the new agreement with Microsoft, the Adobe creative cloud now hosted on Microsoft Azure.

Services Provided by Cloud Providers

So, this was all about Cloud Providers. Hope you like our explanation.