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Essential Elements in Building an Agile Data Center




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Scale-Out Manageability

As their virtual infrastructure grows to tens and hundreds of thousands of VMs, IT admins need to simplify storage management and avoid constant manual configuration of LUNs and volumes.
Managing storage at the VM-level enables IT to automate and optimize placement of VMs constantly across their pool of storage, taking into account space savings, resources required, and the cost in time and data to move VMs. When a VM is moved, the associated snapshots, statistics, protection and QoS policies should migrate as well using a compressed and deduplicated replication protocol.

The automation and storage intelligence provided by policy-based VM management combined with advanced analytics and QoS allows enterprises and service providers to often triple or quadruple their virtualized infrastructure without adding a corresponding number of dedicated storage personnel.

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.

 

Related Topics : IBM Looks to Redefine Industry Standard Servers, APC, Brocade, Citrix Systems, Data Center

 
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