Government



Turbonomic Customer Testimonial

Turbonomic helped us correctly target our purchases by telling us that we didn’t need a new host server; we needed more iops. We were thus able to diagnose and address the actual issue by improving the VDI-dedicated SAN rather than trying to throw more host resources at the problem.

Virtualization Architect, Federal Government

Turbonomic Customer Testimonial

Monitoring our VMware environment used to be a manual process and was reactive to the needs of the servers, manually increasing resources where the demand was high. By the time we could get to it, the end users were already feeling the need for it. Turbonomic has automated this, giving us time to focus on other things. Turbonomic has made us proactive instead of reactive. We do not get service requests complaining of performance problems anymore.

Eric Scott, Information Systems Manager, City of Lewiston, Idaho

Guarantee Performance

Turbonomic helps us guarantee the hosted application servers have the necessary resources to optimize performance.

Stefanie Thompson, Server/Storage Manager, City of Garland Texas

Case Study: City Of Scottsdale

Introduction

This case study of City of Scottsdale is based on a August 2015 survey of Turbonomic customers by TechValidate, a 3rd-party research service.

“Turbonomic identified and resolved resource underutilization and resource bottlenecks. It works well with minimal upkeep, well organized to extract meaningful information.”

Challenges

  • Solved the following challenges with Turbonomic:
    • Underutilized infrastructure
    • Performance for independent workloads sharing common infrastructure
    • Challenges with accurate capacity planning

Use Case

  • Virtual machines in their current environment: Fewer than 500
  • Currently has 60% to 79% of their production systems virtualized in their environment.
  • Automated action with Turbonomic:
    • Start

Results

  • Realized value within 1 to 3 months after deploying Turbonomic.
  • Used Turbonomic to complement VMware or another hypervisor management suite resulting in:
    • Reduced the time spent reviewing data to make decisions
    • Reduced number of alerts we receive
    • Achieved better densities on hosts
    • Improved accuracy in planning for and implementing changes
  • Increased the following since deploying Turbonomic:
    • Virtual workload performance: 20 to 39%
    • VM team productivity: 40 to 59%
    • Resource utilization: 40 to 59%
  • Decreased since deploying Turbonomic:
    • Monitoring alerts : 40 to 59%
    • False positive alerts: 60% or more
    • User generated tickets: 40 to 59%
    • Time to resolve issues: 40 to 59%

Case Study: City of Garland Texas

Introduction

This case study of City of Garland Texas is based on a August 2015 survey of Turbonomic customers by TechValidate, a 3rd-party research service.

“With Turbonomic, we’ve increased host capacity and server performances through resource optimization. It’s affordable, gives us everything we need and more, and has great customer support.”

Challenges

  • Solved the following challenges with Turbonomic:
    • Labor-intensive operational tasks
    • Underutilized infrastructure
    • Challenges with accurate capacity planning

Use Case

  • Virtual machines in their current environment: 500 to 999
  • Currently has > 80% of their production systems virtualized in their environment.
  • Automated action with Turbonomic:
    • Resize (e.g. vCPU or memory)

Results

  • Realized value within 1 to 3 days after deploying Turbonomic.
  • Used Turbonomic to complement VMware or another hypervisor management suite resulting in:
    • Reduced the time spent reviewing data to make decisions
    • Achieved better densities on hosts
    • Improved accuracy in planning for and implementing changes
  • Increased the following since deploying Turbonomic:
    • Virtual workload performance: 20 to 39%
    • VM team productivity: 40 to 59%
    • Resource utilization: 60% or greater
  • Decreased since deploying Turbonomic:
    • Monitoring alerts : less than 20%
    • False positive alerts: less than 20%
    • User generated tickets: less than 20%
    • Time to resolve issues: 20 to 39%