The Evolution of the Data Center to the Cloud
Most discussion surrounding Big Data and the cloud involves how advanced analytics can be augmented by deploying them on either internal or external cloud architectures, or sometimes both. The idea is that the cloud provides a low-cost, highly scalable environment capable of handling the massive number-crunching necessary to find patterns in structured and unstructured data.
But it is also possible that Big Data can be used to optimize cloud infrastructure itself—that is, by leveraging Big Data analytics, an enterprise can learn to make its own cloud deployments more efficient and effective.
According to Vikas Aggarwal, CEO of network management firm Zyrion, the sheer complexity of modern data environments will soon make Big Data analytics a necessity, particularly as organizations strive for real-time performance. Where once applications, platforms and hardware were closely linked, today’s infrastructure is a mix of constantly shifting interdependencies, with various components up and down the stack generating constant flows of operational data. Only by capturing and correlating this information Big Data-style can the enterprise hope to keep track of this swirling environment, both as a means to maintain service levels and lower costs.
To be sure, though, Zyrion is not the only software company to hit upon this notion. A startup called StackDriver utilizes a multi-layer data collection system that pulls from on-premise and external cloud infrastructure and applications and runs the data through a proprietary analytics engine to hunt for anomalies, such as over- or under-burdened resources. In this way, the company hopes to improve the enterprise’s ability to scale its cloud presence up or down to more closely match fluctuating workloads.
Even plain old virtual environments could use a dose of Big Data as well. A company called CloudPhysics has turned its intelligent IT management service toward VMware workloads, with the notion that Big Data analytics can help IT manage cloud traffic the way Google uses GPS data to analyze highway conditions. As virtualization increases the density of hardware configurations, resource contention and network bottlenecks naturally rise as well. The company’s SaaS-based platform performs health monitoring, reporting, analysis and resource planning for network, storage, CPU and the many other IT components that require higher visibility once they are tasked with supporting virtual environments.
Big Data is also being used to give the enterprise and service providers a better idea of how various cloud and on-premise infrastructure configurations will pan out in the real world. CA recently updated its Capacity Management platform with advanced data gathering and analysis tools to foster high-level efficiency planning and modeling capabilities. In this way, organizations can not only experiment with various cloud deployments, but can also price-check services against each other to determine who really offers the best deal.
It is safe to say that virtualization and the cloud have led to the era of “Big Infrastructure.” And standard enterprise management platforms like Tivoli and BMC simply do not have the chops to handle the vagaries of dynamic infrastructure on their own.
Big Data is quickly becoming the enterprise’s best friend when it comes to identifying and capitalizing on business opportunities with their own data environments. But it is also poised to become a vital tool in maintaining the environment itself.
