What is the Difference between Cloud Computing and Grid Computing?
Hi Manish,
Cloud computing is where an application accesses the resources that it requires through a service.
The service then maps any requests for resources to its physical resources and provides it to the application. The service can dynamically allocate physical resources as they are needed.
Cloud computing can scale up to high capacities immediately without investing in new infrastructure.
Grid computing is where more than one computer coordinates to solve a problem together.
To build and manage a Grid requires huge capital and operational expenses.
Cloud computing refers to a client server architecture where typically the servers (called “the cloud”) reside remotely and are accessed via the internet, usually via a web browser. Applications like word processors that have traditionally run locally or on a server and accessed via a dumb terminal are instead run on the remote servers and accessed via a web browser. The same goes for services, such as file storage. Often, the servers are run by a third party and host a set of applications for a variety of clients. One example is Google Docs. Microsoft and Amazon have similar offerings, as do many others.
Grid computing refers to a distributed computing architecture where a set of networked computers (“the grid”, typically PCs) are utilized en masse for large computational tasks, typically ones that are embarrassingly parallel. For example, a bank might use such a network to price all their holdings each night. From the point of view of the application doing the calculations, it’s just submitting a large number of independent jobs to the grid, and receives the results back. The grid infrastructure handles forwarding each job to a computer, balancing loads, etc.
With cloud computing, companies can scale up to massive capacities in an instant without having to invest in new infrastructure, train new personnel, or license new software. Cloud computing is of particular benefit to small and medium-sized businesses who wish to completely outsource their data-center infrastructure, or large companies who wish to get peak load capacity without incurring the higher cost of building larger data centers internally. In both instances, service consumers use what they need on the Internet and pay only for what they use.
The service consumer no longer has to be at a PC, use an application from the PC, or purchase a specific version that’s configured for smartphones, PDAs, and other devices. The consumer does not own the infrastructure, software, or platform in the cloud. He has lower upfront costs, capital expenses, and operating expenses. He does not care about how servers and networks are maintained in the cloud. The consumer can access multiple servers anywhere on the globe without knowing which ones and where they are located.
With cloud computing, companies can scale up to massive capacities in an instant without having to invest in new infrastructure, train new personnel, or license new software. Cloud computing is of particular benefit to small and medium-sized businesses who wish to completely outsource their data-center infrastructure, or large companies who wish to get peak load capacity without incurring the higher cost of building larger data centers internally. In both instances, service consumers use what they need on the Internet and pay only for what they use.
The service consumer no longer has to be at a PC, use an application from the PC, or purchase a specific version that’s configured for smartphones, PDAs, and other devices. The consumer does not own the infrastructure, software, or platform in the cloud. He has lower upfront costs, capital expenses, and operating expenses. He does not care about how servers and networks are maintained in the cloud. The consumer can access multiple servers anywhere on the globe without knowing which ones and where they are located.
Similarities and differences between Cloud Computing and Grid Computing
Cloud computing and grid computing are scalable. Scalability is accomplished through load balancing of application instances running separately on a variety of operating systems and connected through Web services. CPU and network bandwidth is allocated and de-allocated on demand. The system’s storage capacity goes up and down depending on the number of users, instances, and the amount of data transferred at a given time.
Both computing types involve multitenancy and multitask, meaning that many customers can perform different tasks, accessing a single or multiple application instances. Sharing resources among a large pool of users assists in reducing infrastructure costs and peak load capacity. Cloud and grid computing provide service-level agreements (SLAs) for guaranteed uptime availability of, say, 99 percent. If the service slides below the level of the guaranteed uptime service, the consumer will get service credit for receiving data late.
The Amazon S3 provides a Web services interface for the storage and retrieval of data in the cloud. Setting a maximum limits the number of objects you can store in S3. You can store an object as small as 1 byte and as large as 5 GB or even several terabytes. S3 uses the concept of buckets as containers for each storage location of your objects. The data is stored securely using the same data storage infrastructure that Amazon uses for its e-commerce Web sites.
While the storage computing in the grid is well suited for data-intensive storage, it is not economically suited for storing objects as small as 1 byte. In a data grid, the amounts of distributed data must be large for maximum benefit.
A computational grid focuses on computationally intensive operations. Amazon Web Services in cloud computing offers two types of instances: standard and high-CPU
I think that is the same.
Grid computing is where more than one computer coordinates to solve a problem together.
Cloud computing is where an application doesn’t access resources it requires directly, rather it accesses them through something like a service.