Elastic Compute Delivers Real Cost Savings
Workloads are forecasted to grow 26% over the next three years. Yet the business is only funding increases of 3% to IT budgets. How will your business address this gap?
Organizations are turning to automation, digitalization of processes and intent-based analytics to support year over year workload growth. Automation simplifies your data center’s operating model by translating infrastructure provisioning, configuration and management services into standardized processes that are delivered on-demand. Automation delivers the speed and accuracy your organization needs. But how can your environment scale to accommodate growth?
Intelligent scaling requires intent-based solutions that deliver elastic resources to on premise or multi-cloud environments in real time. Not just deploying resources but also decommissioning idle underutilized ones.
Cisco IT manages over 30M watts of raised floor space – that’s $B’s in hardware spread across multiple labs and data centers. The team was challenged to deliver innovation and an improved user experience while at the same time supporting 20% growth, improve utilization and increase workload density.
Watch this video to learn how they tackled these challenges.
Built on Cisco programmable infrastructure, Cisco IT was able to create self-managing elastic environments by teaming with Turbonomic. The results have been amazing:
- 40% improvement in operational efficiency
- Recovery of 54 TB of RAM and 4,800 virtual CPU cores
- 49% increase in headroom with elastic scaling efficiency
- $17M in cap ex savings along with floor space savings of $2.8M/year
“Turbonomic’s dynamic model is really the secret sauce to how you get everything out of that data center that you can,” says Michael Myers, Sr. Director, Cloud Orchestration and Platform Services. “After installing Turbonomic and optimizing our data center, we were able to deploy 2,200 servers for free.”
The primary difference between Turbonomic and Workload Optimization Manager is the deeper level of inspection of Cisco UCS chassis, blades, IO modules and fabric interconnects to deliver granular allocation decisions, increased workload density and assured workload performance on Cisco UCS. This is the first of many planned integrations across Cisco’s hybrid cloud stack.
How do you close the gap between workload growth and IT staffing levels? With comprehensive automation and intent-based analytics that can turn your data center into a self-managing environment. Contact your Cisco sales representative or partner to learn more about Cisco Workload Optimization Manager.