A multi-cloud strategy can create numerous complexities if not handled correctly. The cloud journey to a multi-cloud environment usually evolves from an initial cloud approach of using a SaaS solution, like a CRM or marketing application. Every organization is different with a different set of challenges and expectations. However, what remains consistent is a maturity lifecycle for their cloud journey.
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Four stages of multi-cloud maturity
The cloud journey for every organization can be classified into four distinct stages - Builder, Explorer, Operator and, finally, Broker.
Each of these stages of cloud maturity has its unique goals for the enterprise which are to be achieved with their own unique approach – no one-size fits all. Each stage has new things to offer, which an enterprise will discover only when it has arrived at that stage. On successful completion of each stage, the enterprise is ready to “graduate” to the next level. Assessing that readiness is key to success.
What typifies each stage is which the production workloads and non-production workloads of the enterprise are in the cloud.
- Builder - Few or no non-production workloads and no production workloads in the cloud
Cloud consumption is very basic at this stage. Mostly companies choose to run some of their non-production workloads and choose a SaaS solution. The first issue companies have but don’t realize, is that they choose how to use and buy cloud services without doing much analysis to determine best-fit for the workloads. That can start them down a path of future issues and suboptimal performance, greater cost and waste.
- Explorer - Some non-production workloads but few to no production workloads in the cloud
Companies are more familiar with cloud at this stage, where they have moved a few of their production workloads, but with greater experience with non-production workloads. At this stage companies begin to see rising cloud costs. They begin optimization and cost management initiatives, but have limited success due to not understanding or having access to the right “buy” models for their workloads
- Operator - Mostly non-production workloads and some production workloads in the cloud
As the companies reach a more mature stage, they move almost all of their non-production workloads to the cloud, followed by most of their production work. Organizations at this stage already have a well-developed optimization and cost-management strategy and tools in place, and understand the importance of policy and governance control. A challenges they face is how to consistently implement policy control of provisioning with budget control.
- Broker - ALL non-production workloads and MOST production workloads in the cloud
This is the stage where companies have moved nearly all of their production and non-production workloads into the cloud. They use more advanced optimization and cost management strategies with policy controls. Most importantly, companies at this stage are on software-defined intelligent “autopilot,” using core solutions with best-practices, creating an environment of self-management, self-healing and self-brokering.
Workload lifecycle management
A workload lifecycle management framework helps organizations efficiently use and buy cloud services better – matching workload requirements to the right public and private cloud solutions, just in time and as autonomously as the CIO is prepared for.
In a future post, we’ll introduce an online assessment method to place an enterprise in its proper stage in the journey, and suggest directions for the next leg of the journey.
Anthony Johnson is co-founder and principal at workload optimization firm Advanced Cloud Analytics (ACA)