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Get the power of reactive, balanced and predictive methods in a single solution:

vSphere with Operations Management

In a complex data center like yours, all three risk mitigation methods are required to

fully manage contention.

PREDICTMove Workloads Before Any Contention Occurs 3

With the game-changing capabilities of Predictive DRS, integrated

with vRealize Operations, solve performance problems

before they happen.

Sophisticated analytics

identify patterns and create a band of what is “normal”

for each metric/object combination

Balance workloads in advance of

demand spikes using Dynamic Thresholds and

forecasted utilization metrics

Predict future demand and determine when and where hot spots

will occur

Reduce moves for predictable VMs

over time by eliminating

potential resource contentions

Minimize overhead by only moving required

workloads

NEW!

VM VM

VM VM

BALANCESpread Workloads Across Clusters

Leverage Intelligent Workload Placement and Rebalance,

using DRS and VMware vRealize Operations together, to

achieve optimal balance across the entire environment.

Mitigate the risk of growing workloads

by balancing workloads across hosts and clusters

Control your overhead tolerance

by setting the amount of balance you want to drive

Avoid hot spots by spreading workloads

out evenly

2

VM VMVM VM VM

VM

Ensure workloads get the resources

they need and applications remain healthy

Minimize overheadby only moving VMs

as needed

Take controlby easily adjusting from

passive to aggressive load-balancing

Automatically move VMs whenever contention occurs

with VMware Distributed Resource Scheduler (DRS).

REACTAddress Unexpected Resource Demands1

Here are 3 ways to comprehensively and proactively manage resources in your data center:

Need to meet SLAs and manage workload

performance?

Dream of eliminating

resource contention

and mitigating risk

in your data center?

Eliminate Resource Contention

IN YOUR DATA CENTER

PROACTIVERESOURCE

MANAGEMENT=

HAPPYUSERS

HEALTHYAPPS

+

resourcedemand

time

Predicted Observed