Choosing the Right Cloud Services
Each cloud service and delivery model is designed to meet specific business requirements. Some offer greater cost savings, but may not provide the appropriate level of visibility and security. Others may offer higher levels of security, but at the expense of elasticity and costs. The key is to find the best fit for the business requirements and the IT service.
One method that may prove useful is a multi-criteria decision analysis (MCDA). In its simplest form, an MCDA is a discipline used to help support the decision making process in the absence of hard measurements. This method uses measurements based on the subjective strengths of various preferences. By aligning the preferences to the various IT services and applying some if-then logic, it becomes clearer which services may most benefit from which types of cloud offerings.
A simplified list of business preferences in un-weighted order might be:
- Cost (Low/Medium/High)
- Security (Low/Medium/High)
- Elasticity (Low/Medium/High)
- Availability (Low/Medium/High)
- Supportability (Low/Medium/High)
One can then apply these business preferences to the various cloud services. For example, a hypothetical private SaaS may support the following preferences:
- Cost – High
- Security – Low/Medium/High
- Elasticity – Low
- Availability – Low/Medium/High
- Supportability – Low/Medium/High
Conversely, a hypothetical public SaaS may support the following:
- Cost – Low/Medium/High
- Security – Low/Medium
- Elasticity – Low/Medium/High
- Availability – Low/Medium
- Supportability – Low/Medium
When evaluating Email and Collaboration services, the organization’s weighted preferences might be:
- Cost – Low
- Security – Medium
- Elasticity – Medium
- Availability – Medium
- Supportability - Medium
In this case, we could support our business preferences with a public SaaS for email and collaboration, as the public cloud capabilities meet or exceed the business preferences. In the example, a private cloud service would be too costly and not meet theelasticity preferences.
An example of multiple services with high level business preferences can be seen in table below
Admittedly, this is an oversimplified example, but applying a more rigorous MCDA can help point the compass in the right direction when exploring options. Additionally, the actual technical details will further filter through the technology options until the best fit is determined.
Using an MCDA can be an excellent tool to determine which IT services are most appropriate for ”cloudification” in support of the “Cloud First” policy.
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