Victor Community Support Services Opts for Condusiv’s V-locity I/O Reduction Software

Condusiv Technologies Corp., in software-only storage performance solutions for virtual and physical server environments, announced that Victor Community Support Services (VCSS) has standardized on its V-locity I/O Reduction Software to deliver application performance improvements as the organization readied itself for a virtual desktop deployment.

As a result, the community services organization has been able to reduce the IO/s requirements from their underlying storage subsystem by nearly half during peak application usage on their heaviest workloads.

VCSS is a community-based agency that delivers mental health and family support services in the homes, schools and communities in which people live. VCSS delivers programs ranging from prevention and early intervention programs to intensive home-based services designed to prevent residential and other institutional placements. VCSS is focused on empowering people of all ages to build upon their strengths and capacities to address the problems and needs they have within their lives.

With a growing organization accessing a number of workload-heavy applications, VCSS needed to ensure that its systems and storage were performing optimally. Financial applications such as Great Plains and Paper Save running on MS-SQL were exceptional I/O consumers, driving up IO/s usage during peak times during the day while its other 100+ VMs – which also support all email; SQL apps; file services, print services, telephone services, and more – hit the same storage device. Additionally, its electronic health record application, Tier, was increasingly taking up more and more IO/s, making the organization’s storage system struggle to keep up.

With a VDI project on the horizon, VCSS wanted to optimize its storage resources so that the transition of all employees to a virtual desktop platform wouldn’t further impact overall infrastructure performance. That’s when VCSS turned to Condusiv to implement V-locity.

“Once we installed V-locity, we monitored our IO/s and saw a near 50% decrease in I/O from VM to storage according to our daily averages and peaks,” said Jamie Rabenstein, IT manager, VCSS. “Even when we added what equates to three times the workloads with our new VDI implementation, the IO/s demand from storage didn’t increase three-fold because of what V-locity is doing to reduce write I/O and read I/O at the VM layer. It has been truly impressive. I call it the ‘V-locity effect.’“

VCSS has had its V-locity software solution in place for more than a year and the results have been exciting. Reducing I/O requirements by half has led to a number of real-world benefits. For example, the financial team used to spend 30 minutes running a report in Great Plains that ran on MS-SQL. Since implementing V-locity, that report takes just three minutes to run.

“Now we roll out the V-locity red carpet for all of our systems,” added Rabenstein. “To not do that would be too painful for me to imagine. It truly can milk the hardware for everything it has. Anyone that needs low latency and high throughput loads should be using it.“

VCSS also rolled out a Nimble Hybrid Storage System to further ensure that IO/s would not become a choke point during the VDI implementation and guarantee that a growing number of machines could continue to be added to the platform.

“With V-locity and Nimble Storage together, it’s like having lightning performance at both ends of the spectrum,” commented Rabenstein. “The combined solution delivers multiple layers of speed for both read and write operations. First, V-locity ensures contiguous writes and subsequent reads with minimal I/O operations no matter where the data needs to be satisfied from, whether flash or disk. Second, if any data is requested, it might already be in available DRAM due to V-locity. If it’s not, Nimble might have it in its flash tier. But even if Nimble has to go to all the way down to spinning disk as a last resort to get the data, V-locity ensures minimum disk latency as the data is retrieved with the fewest number of I/O requests possible.“

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