As the line between storage attached to a server and a network continues to blur, IT organizations are looking for a way to manage both resources in tandem.
To address that specific issue, DataCore has released an upgrade to its SANsymphony-V storage virtualization software that extends the reach of its storage management capabilities beyond storage on the network to include magnetic and Flash storage that are attached directly to a server.
According to Augie Gonzalez, director of product marketing for DataCore, as commodity-based storage gets deployed on servers and attached to the network, IT organizations want to be able to manage the resources as one logical pool of resources. Gonzalez says SANsymphony-V R 9.0.4 extends the reach of DataCore’s approach to software-defined storage (SDS) at a time when IT organizations are plugging more storage directly into servers to optimize the performance of mission-critical applications.
At the same time, the capacity growth demands are creating requirements for pools of storage that can logically scale out over time using commodity-based storage attached to the network. Rather than treating both of those instances as separate instances of storage, Gonzalez says SANsymphony is now optimized to handle a full spectrum of storage deployment scenarios.
Performance close to application servers and shared capacity and services in the SAN
Other new features in SANsymphony-V include support for up to 16 storage nodes, synchronous mirroring between storage nodes, the ability to more easily move data between diverse virtual machine environments, and a service that makes it easier to reclaim unused storage space.
With the advent of storage virtualization coupled with the rise of SDS, the storage landscape is rapidly transforming. Driving that transition, says Gonzalez, is a desire to replace expensive storage systems based on proprietary controllers with industry-standard systems based on x86 server architectures. As that trend continues to gain momentum, Gonzalez says it’s only a matter of time before storage is seen as a challenge to be solved more by software than with the underlying hardware used to physically store the data.