Building a Cloud Factory
A process empowering companies to more efficiently migrate workloads to the cloud
By: Andrew Hillier
Aug. 14, 2011 05:45 AM
Few areas of human endeavor can match the pace of change in IT. Even by IT standards, the change being driven by cloud computing sometimes seems surprising. To refer to a virtual environment that has only recently been deployed as "legacy," as some organizations are now doing, underscores the fact that the only thing constant in the data center is change. To deal with change of this magnitude, which can involve transforming the workload hosting model of an entire organization, some industrial-strength thinking is required.
In order to tackle this challenge, it's important to properly frame the cloud transformation problem. Many associate cloud with agility, flexibility, cost transparency and other end-user-oriented benefits. But many of these attributes are primarily associated with new infrastructure requests, and specifically, the use of self-service portals to "spin up" infrastructure to host new applications or host transient processing demands. When it comes to migrating hundreds or thousands of existing workloads into cloud infrastructure, agility is not a benefit that is typically experienced. In fact the opposite is often the case: because clouds require a higher degree of standardization (i.e., a finite catalog of sizes and software options), migrating existing physical and virtual servers into cloud models can actually be quite difficult. In other words, the very features that make clouds agile for new workload deployments can actually make them less agile from a transformation perspective.
This is where the notion of a factory comes in. In industrial processes, factories are the epitome of scalability, repeatability and productivity. Although they may take some effort to "tool up," once they are up and running they can handle a higher flow of activity, efficiently processing inputs to provide consistent output. This notion is also key to large-scale transformation. By applying a common approach that has been properly engineered to give repeatable results, organizations can greatly reduce the time and effort required to migrate to cloud infrastructure.
Within this concept, it is important to expand on what is meant by "properly engineered." Many organizations tackle these kinds of problems from a grassroots perspective, using spreadsheets and smart people to determine action. The problem with this approach is it rarely evolves to the point where it can generate truly accurate answers, mainly because the problem is too complex. Migrating workloads into clouds requires processing volumes of historical data, analyzing configuration information on the servers and applications being migrated, modeling target instance sizes and software stacks, enforcing corporate and regulatory requirements, honoring SLA and data protection rules, etc. Spreadsheets are not well suited to this, in much the same way that they are ill suited for use as corporate accounting platforms. Even if they can be coaxed into giving a decent answer for simple environments, they will not generate the reports needed to satisfy stakeholders, management, engineering, operations, etc., all of whom need significant detail surrounding the decisions being made in order to ensure benefits are achieved and risk is minimized.
Buried in the list of migration analysis requirements is a key concept linking them all together. This is the notion of policy, which represents the ground rules on how workloads should be hosted, where they should and should not go, how much resources they should be allocated, etc. Without properly modeled policies, hosting decisions are left to the practitioner performing the migration, and it can be hit-or-miss whether they do the right thing (or even follow the same policy twice in a row). Planning and managing cloud infrastructure without proper policies is like trying to fill out a tax return without instructions - there are just too many variables to get it right.
With all of these concepts in mind, the exact nature of the cloud factory becomes clearer. It divides the problem into a series of logical steps that combine data, target models and cloud planning and management policies in order to automate the process of deciding exactly where things go and how big to make them. These steps that make up the factory are:
The result of applying these steps is a methodical, exhaustive and rapid process for planning cloud migrations. By taking a data-centric, policy-driven approach, fewer mistakes are made, less rework is required, and application owners and other stakeholders will have much higher confidence they will arrive on the other end unscathed. This transparency, combined with the detailed specifications and implementation details that emerge, can rapidly accelerate cloud initiatives. This not only reduces time-to-value, but also enables IT organizations to keep up with the pace of technology innovation, which shows no sign of letting up.
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