Building better products with speed and consistency requires using reliable cloud solutions to rapidly scale to meet sudden demand. When businesses rely on a single vendor for cloud computing, they risk experiencing downtime and data loss if the cloud services provider is unable to meet a sudden uptick in demand. Customers expect dependable applications and few outages, making the reliance on a single cloud a risky decision for organizations looking to meet both business and market demand.
Outages can happen, but organizations must find ways to minimize the occurrence or they risk losing customers. A multicloud approach decreases the risk of data loss and downtime by spreading computing across multiple cloud solutions, such as Google Cloud Platform, Microsoft Azure, and Amazon Web Services.
In cloud computing, a multicloud strategy is the use of at least two cloud computing services from different cloud vendors in a single network architecture. A multicloud deployment enables teams to select the best providers for every technical and business need. A multicloud environment increases the available storage, computing power, and cost savings. Organizations can choose between multiple deployments of the same type of cloud (public or private) to leverage the best cloud solutions.
Private clouds are dedicated to one organization, so specific provisions can be made to ensure security and compliance. Private clouds can either be sold as a Platform-as-a-Service (PaaS) or offered as Infrastructure-as-a-Service (IaaS). A public cloud offers cloud solutions to multiple customers who share the cloud environment. Because they are automatically provisioned, they are considered less secure and not an option to store sensitive and confidential data.
Approximately 85% of organizations → use multicloud environments, but not every organization is at the same level of maturity. As teams work through the multicloud maturity model, they increase portability by insulating cloud services from underlying infrastructure, such as processors, operating systems, and virtualization software, through layers of abstraction.
All applications are in one cloud. With this strategy, a company goes “all-in” with one cloud provider for the ease of use, or because the services offered meet current business needs. The organization is locked in with a single vendor.
There may be separate teams within the same organization, and each is working out of different cloud providers, but each team is working in its own mono-cloud environment. This structure uses multiple clouds but is not technically multicloud.
Workflow portability is what makes deploying anywhere possible. Instead of having to tailor certain workflows to certain clouds, developers can have one workflow with cloud-independent DevOps processes and frameworks for making deployment decisions.
In this scenario, applications can run on any cloud, and cloud-specific services are abstracted. Application portability is hard to attain, because it requires engineering interfaces as abstractions. It also leaves organizations using only the features that are common to all clouds, so they miss out on any specialty capabilities that could improve their processes.
In this scenario, applications can fail over to another cloud with limited downtime. If a cloud provider’s data center should go down, organizations have the ability to switch to another provider.
The goal of workload portability is for organizations to shift application workloads between multiple clouds dynamically (e.g. autoscaling servers for background jobs). Workload portability makes it possible to migrate elements of a business service to the appropriate infrastructure so that it can service the needs of the user.
Data portability is a feature that lets users take their data from a service and transfer or “port” it elsewhere, typically through an API.
Ready to learn more about multicloud? Here are a few resources to help you get started on your journey.
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