This is an excerpt from the Gartner report "The Future Of Cloud Data Management Is Multicloud" which delves into how data and analytics leaders will prepare for a multicloud and intercloud world.


Developing a Multicloud and Intercloud Strategy

Multicloud means a given service can be operated on more than one cloud (see Note 1). For example, a data integration service can operate on two or more cloud infrastructure offerings. Multicloud is important for use cases where you are procuring cloud services and you want to ensure that offering works on different cloud platforms.

Intercloud means that integration has to take place between two services, with each service on a different cloud infrastructure. Intercloud is important for use cases where you are seeking to integrate data and analytics workflow across different services/clouds.

Developing a sound multicloud and intercloud data management strategy requires an understanding of the technology implications and associated challenges of each style of cloud deployment. The following research provides a solid grounding in the multicloud/intercloud problem space.

“Technology Insight for Multicloud Computing”

Most organizations will use more than one public cloud provider. Enterprise architecture and technology innovation leaders must select the multicloud strategy that best fits their business needs.

“Multicloud: Why It Matters”

A small group of megavendors dominates public cloud markets, which restricts new entrants’ ability to compete. To maximize available cloud opportunity, technology general managers must embrace and invest in multicloud.

“Are You Ready for Multicloud and Intercloud Data Management?”

The increased adoption of multicloud and intercloud deployments in support of data management solutions has important implications for data and analytics strategies. Data and analytics leaders must prepare for these impacts now in order to ensure optimal use of cloud resources.

Data Integration in a Hybrid and Multicloud/Intercloud Data Landscape

When data is split between multiple deployment environments, effective data integration becomes critical. The following research describes the hybrid cloud world, and presents comprehensive strategies to address data integration within it.

“3 Ways That Hybrid Cloud for DBMS Will Drive Your Data Management Strategy”

The majority of enterprises using cloud will be living in a hybrid deployment world for the foreseeable future. Data and analytics leaders must understand the risks and benefits in using the primary scenarios for hybrid cloud DBMS, and how these risks and benefits align with core use cases and architectures.

“‘Unlearn’ Existing Practices for Success in Multicloud and Hybrid Data Integration”

Data and analytics leaders must “unlearn” postimplementation data integration practices in order to succeed in multicloud or cloud and on-premises hybrid environments. Distributed data requires distributed integration that uses a combination of design approaches.

“How to Architect a Multicloud-Capable Hybrid Integration Platform”

As more applications and data move to the cloud, application leaders face increasingly complex integration requirements: within the same cloud, across different clouds and with on-premises endpoints. It has become crucial to support these diverse topologies in your hybrid integration platform strategy. 

Acronym Key and Glossary Terms

CSB
cloud service brokerage
IaaS
infrastructure as a service
PaaS
platform as a service

Evidence

Gartner’s Cloud Study 2018 (P-18029 Cloud Adoption). The survey was conducted online by an external partner, from October through November 2018. The full study surveyed 1,200 individuals. Of those surveyed, 628 reported that their organization was using the public cloud; and 507 of those respondents reported using more than one public cloud provider.

Results of this study do not represent “global” findings, or the market as a whole, but are a simple average of results for the targeted countries covered in this survey. 

Note 1

Hybrid Cloud, Multicloud and Intercloud Taxonomy

There is a lack of clarity in the market around the definition and meaning of these terms. Vendors will often refer to their product as “multicloud” — by which they mean it runs on more than one cloud. Gartner accepts this definition, but finds it incomplete. Below, we articulate a full taxonomy for hybrid cloud, multicloud and intercloud architectures.

  • Hybrid Cloud — Refers to implementations that span on-premises and cloud deployments. In “3 Ways That Hybrid Cloud for DBMS Will Drive Your Data Management Strategy,” we further define the subcases of:
    • Architecture Spanning Hybrid Cloud — Where components of a single logical deployment span on-premises and cloud.
    • Use-Case-Specific Hybrid Cloud — Where different components are segmented by their development life cycle function (for example, development, test and production).
  • Multicloud — Where a service or product runs on the infrastructure of more than one cloud service provider, and may also run on-premises.
  • Intercloud — Where data is integrated or exchanged between cloud service providers as part of a logical application deployment.

These definitions can also be combined; for example:

  • Architecture Spanning Intercloud — would refer to a logical deployment of a single application — where components were deployed on more than one cloud and regularly exchanged data between the clouds.
  • Use-Case-Specific Multicloud — would mean that a development environment was deployed in one cloud, and a production environment was deployed in another cloud.

However, you could not have a “use-case-specific intercloud,” because data is not exchanged actively between the environments in a use-case-specific scenario.


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