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Real-Time Optimization Ensures Workload Performance

- August 31, 2017 - 0 Comments

Everywhere you look, the industry is talking about applications. They generate revenue and run your business. Assuring your applications’ performance requires stable data center resources allocated in just the right size to meet demand.

How does your business allocate resources?  Most over provision for peak demand which leads to higher capex and idle resources once demand returns to everyday levels.  If this over provisioned workload lives in the cloud, you can see crazy high bills.

Allocating just the right amount of resource for workloads at the right time is a complex problem. Cloud infrastructure, containers, micro services and public cloud services have driven up both the number of workloads and the devices that need to be monitored and managed. It has become too much for humans to handle. A recent Storage Switzerland study indicated that an environment with 3,000 virtual machines would need to make 300 changes per day.  That’s one change every 5 minutes!

New solutions are available that solve this problem with advanced analytics and automation.  These solutions free humans from these complex decisions and let software do what it does best: manage these decisions in real-time. Watch this entertaining video to explore further.

Cisco Workload Optimization Manager delivers a real-time decision engine that automatically adjusts workload placement and resource allocations in response to changes in demand.  Your organization benefits from higher efficiency across your data center stack.  It assures performance while minimizing costs.  And it does this for any workload, on any platform, at any time.

The latest release of Workload Optimization Manager takes it one step further by integrating with Cisco UCS Director and CloudCenter to deliver true elastic infrastructure at scale.  When infrastructure capacity is insufficient to meet demand or house a new project, the solution leverages UCS Director’s workflows to turn up a blade, rack server or data store. It also decommissions idle resources or resizes data stores automatically. Not sure there is adequate capacity to deploy your application? CloudCenter integration automates this verification process preventing applications from being deployed into under powered instances.

When you move a workload to the cloud do you typically move the next instance size? Your not alone. As we already mentioned, on premise workloads are over provisioned to meet peak demand.  Moving to the next instance size simply duplicates over provisioning and results in higher bills.

Protect your cloud budget with Workload Optimization Manager’s built in modeling that ensures the right size instance for your workload.  As shown below, the modeling capability delivers an understanding of your costs before you migrate.

 

How do you ensure the performance of your workloads on premise or in the cloud?  Download Workload Optimization Manager and experience the power of software to manage your workload performance.

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