For most enterprises, hybrid infrastructure is emerging as the primary means of support for Big Data and the Internet of Things (IoT). Whether the field is manufacturing, healthcare, finance, e-commerce, or anything else that makes up the modern economy, leveraging key datasets in support of core business processes is one of the surest ways to enhance the bottom line.
But few organizations realize that Big Data can also be used to improve that same infrastructure. After all, Big Data is intended to produce clarity in complex environments, and hybrid infrastructure is nothing if not complex, particularly when it’s built atop virtual servers, storage, and networking architectures, and then populated with numerous mobile, sync/sharing, and data productivity apps.
According to Ken Won, director of cloud solutions marketing at Hewlett Packard Enterprise, optimizing hybrid infrastructure is one of the most crucial yet complicated facets of converting legacy infrastructure into a modern, abstract data environment. There’s a plethora of tools available to address the numerous automation and orchestration functions up and down the stack, but the entire ecosystem must be funneled through an intuitive albeit comprehensive user interface that allows knowledge workers to define their own data and infrastructure requirements (within limits, of course). “Enterprises are increasingly deploying automation and orchestration tools to become more agile, respond faster, and minimize human error,” Won said. All the while, data, resources, connectivity, and a host of other elements are in a constant state of flux as the management and automation systems seek to maximize performance and maintain high utilization.
Big Data analytics can be particularly useful when it comes to migrating workloads to the cloud. According to Alan R. Earls, the migration process is a lot more complicated than simply moving data from one storage farm to another. Issues like access, security, compliance, and configuration management must all be worked out in advance and will vary greatly from app to app and even workload to workload.