How can stakeholders use the three key operations phases of autonomic hyperconvergent management?
In order to really take advantage of all of the benefits of autonomic hyperconvergent platforms, businesses should know how to move into an autonomic virtualization process and use it effectively. This involves three key operational phases that some vendors refer to as “run, plan and build.”
In the initial “run” phase, companies are learning to actually implement resources for an autonomic data setup. This can involve using particular vendor tools and provisioning or decommissioning resources for components. It may involve placing containers, or changing or configuring systems for optimization. In addition, engineers will be looking at workload provisioning and how to move different types of workloads and tasks in and out of a public or private cloud or other virtual system. Companies will also need to choose the right storage structure and make sure it's working effectively – here's one point where hyperconvergence can come in handy, integrating storage rather than attaching it as an external structure.
In the second “plan” stage, companies are looking at accommodating changes to data handling. One of the most common ones is planning for peak time demands – many businesses have certain models in which there are peak demand times where systems need to scale. Planning can include trial runs to accommodate these peak times and adding resources in dynamic ways that help make sure the system can handle the stresses that are on it. Budgeting can also be a part of this particular operational step.
In the “build” phase, companies are often working on automating some of the above items, and making virtual administration less labor-intensive. Engineers may look at the demand profiles on workloads and put pieces in place to make sure that the system hums along with the right sort of resource allocation. Placement of components in a hyperconverged environment is a key consideration. Businesses will also have to reserve some capacity for new workloads as well. All of this can require some specific vendor partnerships and support.
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