Essential Elements in Building an Agile Data Center
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Speed
When it comes to running a data center, the last thing employees want is to be tied down with IO performance and latency concerns, even when using flash storage.
With conventional storage, IO requests are handled sequentially. So, a mission-critical test for the development team gets stuck behind a massive (and relatively unimportant) database update. And it's why boot storms and antivirus scans can cripple VDI user experience.
Within a LUN, if a single VM acts like a noisy neighbor and demands more than its share of performance, it can negatively affect the performance of other VMs in that same LUN. Fortunately, there's an alternative — more organizations are turning to VM-aware storage (VAS), which uses individual VMs as the unit of management.
With VM-aware storage, IT can give every VM its own performance lane. There are no LUNs, and so there are no neighbors. If an individual VM goes wrong, it doesn't affect any other VMs on the VAS storage platform. Rather than stack up actions sequentially, VM-aware storage handles them simultaneously to end the performance hiccups that can be so pervasive. Without the limitations of traditional, physical-first storage, virtualized applications perform (on average) six times faster.
Today, about 75 percent of all workloads in data centers are virtualized and this number is only expected to grow. The biggest challenge IT admins face is that conventional storage is ill-equipped to deal with virtualization because the storage is built for physical workloads.
Problems arise as legacy storage, with logical unit numbers (LUNs) and volumes that might house tens or hundreds of individual virtual machines (VMs), causes resident VMs to fight over limited resources. This is a phenomenon called the "noisy neighbor." While one common solution is to throw more high-performance flash storage at the problem, this alone cannot fix the problem. It simply postpones dealing with the underlying problem (LUNs). Costs can spiral out of control as an all-flash storage architecture dedicated to LUNs and volumes does not necessarily overcome the pain points of managing virtual workloads.
While many companies aspire to build cloud-scale infrastructures with agility and automation for diverse virtualized workloads, they have been forced to choose between limited scale-out that requires a large number of disks or expensive and inefficient scale-out. According to Chuck Dubuque, senior director of product and solution marketing for Tintri, five key areas that are critical for successful data center modernization efforts include speed, quality of service (QoS), disaster recovery, predictive data analytics, and manageability at scale.
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