The cloud has become a key component in the successful running of many modern businesses, making it possible for companies to transfer some of the burdens of storing and processing large amounts of data on the local network into the hands of cloud providers.

However, as the way we use technology evolves so too do cloud services, and there are now several cloud computing methods that are evolving to help businesses manage their assets efficiently.

To address some of the confusion surrounding the naming conventions for cloud models, we’ve put together a mini-glossary that should help you navigate from Cloud to Multi-cloud, past the Hybrids, through the Fog and out to the Edge.

Cloud Computing

Also known as simply ‘the cloud’, traditional cloud computing is a term used to describe the on-demand delivery of a range of services, including applications, media and data, via the internet. This process has been designed to both simplify and protect the data storage process for businesses, reducing storage costs, preventing the need for costly updates and releasing in-house resources (such as IT staff) for use elsewhere in the company.

Multi-Cloud Computing

Delivering the service its name promises, multi-cloud computing describes the use of multiple cloud services from more than one provider for different tasks. For very small companies or independent contractors this may feel excessive, but as cloud adoption grows, many companies are beginning to appreciate the different types of cloud available, along with their varied benefits.

For instance, while one team may require a cloud provider capable of safely sharing sensitive data, another may need a cloud service more suited to sharing and collaboration involving large data, such as media files. This can occur within the company, department or branch office. A multi-cloud approach can often provide the best option when the respective requirements are largely mutually exclusive.  For example, a company’s payroll, customer relationship management, human resources and inventory management may all be run on different cloud platforms. The most widely accepted benefit of this approach is that companies can mix and match best-in-class technologies.

Hybrid Cloud Computing

Hybrid means something formed or composed of two or more elements and in the cloud computing world, that’s no less true.

[easy-tweet tweet=”A hybrid solution will often combine the flexibility and scalability of public clouds” hashtags=”CloudComputing, Hybrid”]

Although often confused with multi-cloud computing, hybrid cloud computing has one significant difference: where multi-cloud uses different cloud providers for different tasks, hybrid computing uses different cloud services for the same task or process. In other words, hybrid cloud solutions can make use of any combination of multiple public or private infrastructures to access or perform certain tasks, with the orchestration of data between them. A hybrid solution will often combine the flexibility and scalability of public clouds with the security and accessibility of private clouds.

Fog Computing

While cloud computing is an ideal data solution when you’re lucky enough to have uninterrupted, fast cloud access, it’s unable to reliably support the rapid development of the Internet of Things (IoT). Referring to the obtaining, analysing and delivering of data to and from things previously disconnected from the internet, the concept of the IoT has necessitated the development of a new form of the cloud solution that keeps the information a little closer to home.

Enter fog computing, a term coined by Cisco to describe a localised cloud solution that collects, processes and stores data within a local area network via an IoT gateway or fog node. The power and advantages of cloud computing are moved closer to where the data is being generated.

Data can be sent to the gateway from various local sources in the same network, processed to assess the relevance and to create any necessary reply, and delivered back along with commands to solicit the correct response from the device. This system is particularly beneficial thanks to its ability to process data from multiple sources and respond only where required, using a local network to avoid the need for constant connection to external servers.

Edge Computing

Although it is a term often swapped interchangeably with fog computing, edge computing is its unique solution. Taking localised data processing one step further, edge computing moves analysis even closer to the data sources, requiring each device on a local area network to play a part in the processing of the information. To achieve this, each data source is connected to programmable automation controllers (PAC), which take care of the processing and communication systems for each device.

Edge computing has the distinct advantage of removing unnecessary communication, and thus reducing the potential for failure. Instead, each item works almost independently, determining what, if any, information should be stored and what should be passed forward, and all without consulting with any other points in the network.

According to Ericcson, there will be a worldwide total of around 28 billion connected devices by 2021, with nearly 16 billion related to IoT.  As a growing proportion of transmitted data emanates from IoT, it is important that as much as possible is primarily dealt with at the edge of the network.

Where is the Cloud headed?

Though there is overlap between cloud computing naming conventions, without question, we see a move away from centralised computing wherever its infrastructure may lie. As IoT proliferates, not only is there a need to communicate with these billions of devices sitting on the edge but to provide secure, fast processing and decision-making capabilities.  This needs to happen even in areas of poor (or no) internet coverage and with the help of local data intelligence. A lot of the data will be used and processed on the spot and as it will never be needed again, doesn’t need to be stored.

This will shift company’s focus from traditional cloud computing out to the edge, decentralising decision intelligence and data technologies while still retaining a holistic overview.