Which deployment models of cloud computing examples are the most popular? Public, private, hybrid, and communal clouds are the four basic varieties. There are additionally distributed clouds that aren’t as common. Such as multi-clouds, poly clouds, and other models.
Let us learn more about each one of these deployment models cloud computing examples below.
Cloud Computing Examples: Deployment Models
1. Public Cloud
A public cloud is a type of cloud computing that is provided by a third-party service provider, where cloud users share resources within the service provider’s infrastructure. The service provider manages the hardware and handles any required maintenance.
You can access public clouds using a web browser or an application programming interface. Public clouds are common and by-design for multiple organizations. So businesses that have many locations across the globe mostly choose this type.
Because you don’t need to worry about things like hardware maintenance, you can focus on your business’s core operations. The downside is that public clouds are usually more expensive than other cloud options. You also lose some level of control over your data security because it resides on someone else’s hardware.
2. Private Cloud
A private cloud is very similar to a public cloud. But it is maintained specifically for an organization rather than any individual user.
This means that you can customize it. Perhaps to meet the specific needs of the business or organization. For example for high security or compliance standards. Because you are not sharing the hardware with others, it is also more cost-effective than a public cloud.
However, without third-party providers to handle tasks like maintenance and updates, organizations will need to invest in in-house staff or contractors.
3. Hybrid Cloud
In a hybrid cloud environment, multiple cloud platforms work together for a single purpose. This could be two public clouds working together, two private clouds working together, or even one public and one private cloud working together.
A hybrid environment has the benefit of giving you access to both private and public resources in a single system at the same time. You may even have different types of clouds working in tandem in a hybrid environment, such as a private and a public model working together with a virtualized environment in between them.
If you want to keep your data secure while still being able to take advantage of resources from multiple vendors at once, this is probably your best option. It gives you greater flexibility when it comes to choosing resources from multiple vendors while also providing some level of security from third-party providers who may offer more advanced security features than what your own IT department has available.
However, it requires more integration between these different systems so it requires better planning and preparation before implementation can begin. It will also likely cost more money overall due to the need for planning, maintenance fees, and integration fees.
4. Communal Cloud
A communal cloud is typically for an organization that offers computing resources to other organizations within its network. It is very similar to a private cloud. For instance, it is designed for use by a single organization. But the difference is that the communal cloud is shared between multiple organizations.
This allows smaller organizations to share resources like computing power and storage with other organizations within the same network. Because this type of model doesn’t require much customization, it can be especially cost-effective for small businesses or organizations that want to get into cloud computing without having to invest in expensive infrastructure.
5. Distributed Cloud
A distributed cloud is one where different components of the system are spread across multiple locations. Rather than containing it in one centralized location.
This could be an individual server or some servers working together. Because there are multiple “clouds” working together, this type of system also has its unique issues with data synchronization and management.
Data synchronization refers to the process of moving data between these different locations so that they are all up-to-date with one another. Data management refers to the act of monitoring how data is in use across different locations to ensure that everything is running smoothly and efficiently.
