Cloud Computing Overview and Definitions

A distributed system where components are located on different networked computers and communicate by passing messages.

A type of distributed system where resources from different administrative domains are combined to solve a common task.

A model of computing where resources (like servers, storage, software) are accessed over the internet as a service, on demand.

A type of distributed system where components work together without a central authority, like a network where all computers are equal.

A type of distributed system combining centralized and peer-to-peer elements, for better control and efficiency.

The ability to quickly and easily adjust the amount of resources available, scaling up or down as needed.

Sharing physical resources among multiple tenants, allowing for efficient use of infrastructure.

The use of a shared pool of resources, such as storage, processing power, and memory, allowing for dynamic allocation based on demand.

The ability to access and manage resources without knowing or caring about their exact physical location.

The ability to automatically provision resources based on demand and scale up or down as needed.

A computing model where resources are provided as a metered service, similar to traditional utilities like electricity or water. Users pay only for what they consume.

Cloud computing models are characterized by five key features: on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service.

Cloud computing services can be categorized into three models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

Cloud computing deployments are classified into four models: public, private, community, and hybrid. These models relate to the ownership and management of the cloud infrastructure and services.

A way to break down large, complex problems into many smaller, independent problems, making them easier to solve.

A programming model where each small problem is solved by transforming input data using a function.

A computing approach where each small problem is solved independently and simultaneously, allowing for faster processing.

A programming paradigm where data is processed in batches, which are independent units of work.

A specific type of batch processing that uses map and reduce functions to analyze large datasets.

The ability for a platform as a service (PaaS) application to automatically adjust resources based on demand. This means scaling up or down the number of virtual machines or physical resources (at the infrastructure as a service or IaaS layer) to handle changes in workload.

The underlying infrastructure (IaaS layer) reacts to changes in demand for the PaaS application by automatically provisioning (creating) or de-provisioning (removing) virtual machines or physical resources.

The PaaS application itself can also adjust its resources based on demand. This is not always done automatically, but can be configured to scale up or down as needed.

An example of PaaS elasticity is a request-based web application using PaaS. The PaaS execution layer can automatically provision resources from the IaaS layer to handle the number of incoming requests. This means more resources (VMs, physical servers) become available as needed.

The billing model for PaaS services can differ from IaaS. PaaS can be billed based on higher-level metrics, such as the number of processed requests or execution time, instead of raw CPU usage, memory, and other IaaS-level resources.

The capability of a cloud service to adjust its resource allocation dynamically based on demand.

A software layer that allows you to create and manage virtual machines (VMs) on physical hardware. It enables you to run multiple operating systems on a single machine.

A type of cloud computing service that provides access to virtualized hardware resources like CPU, memory, storage, and networking. You get the flexibility to manage these resources as if they were your own physical infrastructure.

The ability of a cloud service to automatically increase or decrease the resources allocated to it based on current needs. It's like having a flexible budget that adjusts to your spending.

There are two main ways to achieve scalability in cloud computing: vertical scaling involves upgrading to more powerful hardware, while horizontal scaling involves adding more servers to handle increased load.

Virtualization technology at the hardware level allows a single physical machine to run multiple virtual machines as if each VM had its own dedicated hardware. It's like having several virtual computers within one physical machine.

Virtualization in the cloud offers a range of advantages, including increased resource utilization, improved server consolidation, flexibility, and cost savings.

Cloud computing services can be categorized into three main models: IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service). Each level offers different levels of abstraction and control over the underlying cloud infrastructure.

Cloud computing offers various advantages, such as scalability, flexibility, cost-effectiveness, and accessibility. It allows businesses to access computing resources on demand and pay only for what they use.

Cloud computing enables you to access and use a wide range of services over the internet. These include storage, database services, analytics, machine learning, and more. Essentially, it's the ability to access software and computing power without having to physically install or manage it yourself.