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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