A multi-cloud strategy is the use of two or more cloud computing services. While a multi-cloud deployment can refer to any implementation of multiple software as a service (SaaS) or platform as a service (PaaS) cloud offerings, today, it generally refers to a mix of public infrastructure as a service (IaaS) environments, such as Amazon Web Services and Microsoft Azure. Common uses for multi-cloud computing Initially, many organizations pursued a multi-cloud strategy because they were uncertain about cloud reliability. Multi-cloud was, and still is, seen as a way to prevent data loss or downtime due to a localized component failure in the cloud. The ability to avoid vendor lock-in was also an early driver of multi-cloud adoption. While redundancy and vendor lock-in concerns still drive some multi-cloud deployments today, they are also driven largely by enterprises' broader business or technical goals. Those goals can include the use of more price-competitive cloud services or taking advantage of the speed, capacity or features offered by a particular cloud provider in a particular geography. In addition, some organizations pursue multi-cloud strategies for data sovereignty reasons. Certain laws, regulations and corporate policies require enterprise data to physically reside in certain locations. Multi-cloud computing can help organizations meet those requirements, since they can select from multiple IaaS providers' data center regions or availability zones. This flexibility in where cloud data resides also enables organizations to locate compute resources as close as possible to end users to achieve optimal performance and minimal latency. A multi-cloud strategy also offers the ability to select different cloud services or features from different providers. This is helpful, since some cloud environments are better suited than others for a particular task. For example, a certain cloud platform might handle large numbers of requests per unit time, requiring small data transfers on the average, while a different cloud platform might perform better for a smaller numbers of requests per unit time involving large data transfers. Some cloud providers also offer more big data analytics tools or other specialized capabilities, such as machine learning, than their competitors. |
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