Journey to the self-managing data center
Data centers have become highly complex environments. Workloads are growing, on average, 26 percent year over year, while IT budgets are growing at a meager 3 percent. Add the fact that most organizations are complementing their on-premises infrastructure with multiple public clouds, and the challenge of complexity increases exponentially. With all this complexity, how do you decide what workloads to run where and why? How do you know if you are getting full utilization of your infrastructure? And how can you be confident that your applications will continuously perform at the level your business requires? In today’s multicloud world, managing all this complexity is beyond human capabilities.
In order to ensure that your applications continuously perform and your IT resources are fully optimized, you need full visibility across compute infrastructure and applications, across networks and clouds, across containers and microservices….and you need all this intelligence at your fingertips so you can quickly and easily make the right decisions, in real-time to assure application performance, operate efficiently and maintain compliance in your IT environment.
Consider this. What if your data center had a brain and could make decisions on where to place workloads to ensure maximum performance, while lowering operating costs and maintaining compliance?
Cisco Workload Optimization Manager is a real-time decision engine that drives continuous health in the IT environment. The intelligent software continuously analyzes workload consumption, costs, and compliance constraints and allocates resources in real time. It assures application performance by giving workloads the resources they need when they need them.
As we make final preparations for our annual Cisco Live US customer event coming up next week in Orlando, we’d like to share some news about a powerful new release of Cisco Workload Optimization Manager.
Cisco Workload Optimization Manager 2.0 has deep integrations with Cisco’s multicloud portfolio as well as with ecosystem partner solutions. It leverages the data that is already being gathered by these solutions to holistically understand the performance and interdependencies of your applications and infrastructure in order to determine the right actions, at the right time to continuously optimize your data center and cloud environments.
This feature-packed release has new integrations with Cisco HyperFlex, Tetration, AppDynamics as well as Kubernetes, AWS, and Azure. As a result of these integrations, Cisco Workload Optimization Manager now gathers even more data to inform its decisions, giving you broader visibility into how your applications and infrastructure are performing across the data center and into the cloud, and taking real-time actions based on that data to continuously optimize the IT environment.
Here’s a summary of just some of the new capabilities in Cisco Workload Optimization Manager 2.0.
- Cloud Elasticity On-Prem
Maximize cloud elasticity in Cisco HyperFlex & UCS environments with confidence. intelligently scales HyperFlex compute and storage independently, based on real-time workload consumption.
- Super Cluster Optimization
Quickly and easily create super clusters with what-if modeling & policies. Assure performance, while maximizing efficiency with continuous cross-cluster migration of workloads. Check out this Hyperflex white paper for more info:
Cisco HyperFlex and Cisco Workload Optimization Manager, Achieving Agility and Predictable Performance
Minimize network latency in distributed microservices applications with real-time localization of chatty workloads with the Cisco Tetration Analytics
- Cloud Migration and Dynamic Optimization
Manage resources across the data center and public cloud (AWS and Azure) from one platform. Get the most out of Reserved Instances (RIs) when these pre-purchased investments are intelligently utilized in real time.
Drive better optimization through the infrastructure with AppDynamics Accelerate & de-risk application migration with our holistic understanding of application topology, resource utilization, and the data center stack.
- Self-Managing Container Platforms
Accelerate cloud native projects for production-scale Kubernetes, Red Hat OpenShift & Cloud Foundry. Assure performance with pod rescheduling, mitigating contention due to noisy neighbors, resource starvation, and fragmentation.
In addition to the new integrations summarized above, Cisco Workload Optimization Manager supports a broad ecosystem of partner solutions that will continue to grow over time.
Learn more about Cisco Workload Optimization Manager 2.0 at Cisco Live 2018 in Orlando next week (June 10 – 14th). Please join us in the World of Solutions in the Cisco Booth (Platform for Digital Business Area) to see a demo of these powerful new capabilities. You can also visit our partner, Turbonomic in their booth # 1243 at Cisco Live to see demos as well.
For a deeper dive, attend these sessions at Cisco Live.
- Sean Mckeown, Technical Solutions Architect, Cisco
- Wednesday, Jun 13, 02:00 p.m. – 03:30 p.m.
- Jimmy Herbert, Solutions Engineer, Turbonomic
- Monday, June 10, 2:30pm, World of Solutions Campus Solutions Theater
Hope to see you in Orlando!