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Learning to love the complex multi-cloud

Multi-clouds come with complexity, but can offer a more cost-efficient and valuable environment. Will enterprise IT learn to love a multi-cloud approach?

Multi-clouds were the talk of the town last year and continued to be the subject of conversations in 2014 -- and there's good reason why. In most cases, the use of multi-model, multi-type and multi-brand cloud deployments are not only justified, they can also provide better value than single cloud deployments. But how do the multi-cloud pieces fit together?

In a multi-cloud scenario, an enterprise can use Amazon Web Services' (AWS) Simple Storage Service (S3) for storage, Rackspace OnMetal for cloud databases, Google for big data systems, and an OpenStack private cloud for sensitive on-premises data and applications. All of these resources work together to form one or many systems, allowing enterprises to mix and match public with private cloud services to fill a specific need. The tradeoff is complexity.

Enterprises adopt multi-cloud approaches and technologies for a few key reasons:

  • Single cloud installs typically don't provide the depth of functionality enterprises require.
  • The rise of cloud management platforms (CMPs), cost-governance systems and service/API governance gives enterprises a single interface to provision, manage and scale complex environments.
  • Usage-based pricing simplifies cloud computing cost evaluation for enterprise IT, including showback and chargeback.
  • The growing use of platforms, infrastructure and software in the cloud results in a variety of cloud flavors.

Driving force behind multi-cloud adoption

The need to rely on complex cloud architectures, as well as the ability to manage those environments, drives multi-cloud adoptions. Security topped the list of concerns, at 78%, for managed hybrid cloud, in a recent GigaOm Research study on IT leadership. But management concerns weren't far behind. Fifty-four percent of respondents need monitoring and management, while 34% want multi-cloud governance, or CMPs.

Even though a multi-cloud approach is complex and more expensive than single-cloud deployments, project reports show otherwise. Public clouds are usage-based, so you can assign the most cost-effective approaches to provision only those cloud services that provide good value. Companies can also monitor resource usage and costs with cloud financial management tools, and manage resources with CMPs.

Nothing in IT is free

Tools for monitoring multi-clouds aren't free to use. And enterprises sometimes need as many as four to six tools within a multi-cloud environment, including API management, CMPs, federated security, cost monitoring and reporting, among others. The architecture of the management layers is just as important as the architecture and interaction of underlying public and private cloud resources.

Additionally, multi-cloud architectures include traditional systems. So, private and public clouds, traditional mainframe-based applications, ERP systems, and local databases must all work and play in the multi-cloud architecture.

Public and private cloud providers are scrambling to align their technologies with the rise of the multi-cloud. So, assume it's here to stay. And while the tradeoff of multi-cloud is more complex, it can lead to greater value.

About the author:
David "Dave" S. Linthicum is senior vice president of Cloud Technology Partners and an internationally recognized cloud industry expert and thought leader. He is the author or co-author of 13 books on computing, including the best-selling Enterprise Application Integration. Linthicum keynotes at many leading technology conferences on cloud computing, SOA, enterprise application integration and enterprise architecture.

His latest book is Cloud Computing and SOA Convergence in Your Enterprise: A Step-by-Step Guide. His industry experience includes tenures as chief technology officer and CEO of several successful software companies and upper-level management positions in Fortune 100 companies. In addition, he was an associate professor of computer science for eight years and continues to lecture at major technical colleges and universities, including the University of Virginia, Arizona State University and the University of Wisconsin.

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