Think of any historical IT transformation and you'll likely recall the pain associated with change. For large organizations, change isn't easy and it certainly doesn't occur overnight. It requires a finessed combination of planning, validating, selling and a fair amount of political cajoling to get people signed up for the change. It also requires an incremental, stepwise progression that yields benefits along the way -- without this, stakeholders become fatiqued, enthusiasm wanes and projects lose steam. When merchandised effectively, these incremental wins become the kindling that stokes the fire, building the enthusiasm, conviction and confidence required for transformation.
This was true for ERP and SOA projects in years past, and it's true for cloud computing projects today.
Cloud computing promises to reduce operating costs by increasing infrastructure utilization and reducing server sprawl; to reduce the cost of software consumption by allowing business lines to align cost with value received; and to dramatically improve business agility by compressing deployment cycles and time to value for application functionality.
It's no surprise that cloud has attracted dozens of new entrants and forced incumbent vendors to articulate their own cloud strategy. This heightened level of interest has both advanced the thinking in this space and added to the considerable confusion today's enterprises face. If history is any prologue, this confusion will only continue and compound. The forecast for cloud: strong chance of fog.
This certainly doesn't help matters as organizations try to sort out their own cloud strategies.
For any large-scale IT transformation, the question becomes: How do you eat the elephant? The answer, of course, is quite simple: one bite at a time. This is the explicit goal of the Cloud Computing Adoption Model -- a graduated, stepwise approach for the adoption of cloud technologies. It helps to cut through the hype and lay out a clear game plan, incrementing toward cloud without putting projects, budgets and even careers at risk.
Loosely modeled after the Capability Maturity Model (CMM) from the Software Engineering Institute (SEI) at Carnegie Mellon University, the Cloud Computing Adoption Model proposes five steps:
Level 1: Virtualization. The first level of cloud adoption employs hypervisor-based infrastructure and application virtualization technologies for seamless portability of applications and shared server infrastructure.
Level 2: Cloud Experimentation. Virtualization is taken to a cloud model, either internally or externally, based on controlled and bounded deployments utilizing Amazon Elastic Compute Cloud (EC2) for compute capacity and as the reference architecture.
Level 3: Cloud Foundations. Governance, controls, procedures, policies, and best practices begin to form around the development and deployment of cloud applications. Initially, Level 3 efforts focus on internal, non-mission critical applications.
Level 4: Cloud Advancement. Governance foundations allow organizations to scale up the volume of cloud applications through broad-based deployments in the cloud.
Level 5: Cloud Actualization. Dynamic workload balancing across multiple utility clouds. Applications are distributed based on cloud capacity, cost, proximity to user, and other criteria.
For each level, the Model outlines the strategic goals, key investment requirements, expected returns, risk factors, and readiness criteria for graduating to the next step.
At the end of the day, architectural innovations like cloud have transformational potential for enterprises. But the reality is that transformation can't happen overnight -- and it certainly can't happen without a plan. While the Cloud Computing Adoption Model may not represent a panacea for enterprise cloud computing, it does provide a context for thinking strategically about the pace, pattern and sequence of investments and returns that will set organizations on a pragmatic path to cloud.