The ability to continuously deliver application performance while minimizing costs is critical. It enables development teams to innovate and run applications efficiently. Cisco Workload Optimization Manager is intelligent software that assures application performance by giving workloads the resources they need, when they need them.
Get application-aware infrastructure (pdf download)
Cisco AppDynamics and Cisco Workload Optimization Manager provide visibility and insight into application and infrastructure interdependencies and business performance.
Optimize hyperconverged workloads (pdf download)
Get predictable performance and IT agility with Cisco Workload Optimization Manager and HyperFlex.
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Intelligent automation addresses the complexity that your organizations face, taking the time and guesswork out of allocating IT resources.
Cisco Workload Optimization Manager can ensure application performance across your data centers and into public clouds, and tracks, reports, and views trendsfor compute, storage, and database consumption metrics (CPU, memory, IOPs, latency, and Database Transaction Unit (DTU)) across regions and zones. A summary of the types of reports, grouped by category are shown below.
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VM Over/Under Provisioning 90 Days
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| This report shows Virtual Machines that are over and under provisioned as indicated by their utilization of CPU and Memory |
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VM Rightsizing Recommendations
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| This report shows rightsizing recommendations for Virtual Machines based on time range and threshold settings |
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VM Top Bottom Capacity
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| Shows a capacity-centered view of VCPU and VMemory utilization, providing actual quantities both used and in reserve. |
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Storage Associated with Dormant VMs
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| This report shows the amounts of storage used by virtual machines that have been dormant for several days. This storage has the potential to be reclaimed, depending upon the final disposition of such VMs. |
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Individual VM Monthly Summary
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| This report shows a monthly summary of Virtual Machines CPU, Memory and Storage measurements |
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Monthly Top Bottom 15 VMs Capacity
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| Shows a capacity-centered view of CPU and Memory utilization, providing actual quantities both used and in reserve. |
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VM Over/Under Provisioning 30 Days
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| This report shows Virtual Machines that are over and under provisioned as indicated by their utilization of CPU and Memory |
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Monthly VMem Capacity
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| This report shows the VMem capacity over the last month, that was assigned to the VMs in the environment. Where the capacity for a VM was increased or decreased during the month, the higher value is used for the entire month. This report also lists all the clusters that were active in the month. |
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VM Group Summary
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| VM Group Summary |
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Virtual Machine Summary
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| Virtual Machine Summary |
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VM Group Summary (Physical Resources)
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| Monthly Virtual Machine summary of Physical Resources |
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Individual VM Monthly Summary by VM Group
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| Monthly Virtual Machine Group Summary Breakdown by Individual VM |
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Month Based VM Group Over Under Provisioning
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| Month Based VM Group Over Under Provisioning |
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VM 15 Top Bottom Capacity
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| Shows a capacity-centered view of CPU and Memory utilization, providing actual quantities both used and in reserve. |
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VM Group RightSizing Info
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| VM Group RightSizing Info |
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Host/VM - 30 Days Stats vs Thresholds
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| This report shows daily average utilization measurements for the past 30 days. Averages are grouped into two sections. One rolled up for physical machines and another rolled up for virtual machines. |
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Monthly Overview with Cluster Summary
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| This report shows monthly statistics for the enterprise as a whole, and a monthly summary for each cluster. |
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Monthly Overview
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| This report shows monthly statistics for the enterprise. |
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Host/VM - Top Bottom Utilized
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| This report shows the top and bottom physical and virtual machines by their Price Index measurements. Price Index is a derived value that reflects the consumption levels of key compute resources taken in combination. Larger values indicate machines on which resources are most utilized. |
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Host/VM - Resource Utilization Heatmap
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| This report shows the hottest physical and virtual machines according to their Price Index measurements. Price Index is a derived value that reflects the consumption levels of key compute resources taken in combination. Larger values indicate machines on which resources are most utilized. |
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Host Top Bottom Capacity
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| Shows a capacity-centered view of CPU and Memory utilization, providing actual quantities both used and in reserve. |
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Host Top CPU Ready Queue
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| Shows top machines by CPU ready queue utilization |
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Top Host Utilization by Resource
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| Shows top machines by utilization of each resource type |
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Host/VM Groups - 30 Day Stats vs Thresholds
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| Shows a roll-up of average utilization values per day for 30 days for each grouping of machines. Values are highlighted where they cross certain threshold values that may indicate a condition of over utilization of resources. |
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Monthly Top Bottom 15 Hosts Capacity
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| Shows a capacity-centered view of CPU and Memory utilization, providing actual quantities both used and in reserve. |
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Weekly Socket Audit Report
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| This report gives a socket count per PM for licensing purposes |
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Host Group Summary
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| Host Group Summary |
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Host Summary
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| Host Summary |
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Hosting Summary by Host Group
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| Hosting Summary by Host Group |
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Host Monthly Individual Cluster Summary
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| Monthly Individual Cluster Summary |
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Host Top Bottom Capacity Grid Per Cluster
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| Host Top Bottom Capacity Grid Per Cluster |
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Host/VM Group - Resource Utilization Heatmap
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| Heatmap report per cluster |
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Storage Top Bottom Capacity
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| This report shows the top and bottom data stores based on their level of consumption as of the date indicated. |
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Storage Associated with Dormant VMs
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| This report shows the amounts of storage used by virtual machines that have been dormant for several days. This storage has the potential to be reclaimed, depending upon the final disposition of such VMs. |
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Storage Top Disk Consumption
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| This report presents two independent views of information related to VDisk storage. The first highlights data stores that possess the largest amounts of VDisk storage. The second lists Virtual Machines organized most to least in terms of their consumption of VDisk storage. |
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Storage Top Log Consumption
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| This report presents two independent views of information related to Log storage. The first highlights data stores that possess the largest amounts of Log storage. The second lists Virtual Machines organized most to least in terms of their consumption of Log storage. |
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Storage Top Snapshot Consumption
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| This report presents two independent views of information related to Snapshot storage. The first highlights data stores that possess the largest amounts of Snapshot storage. The second lists Virtual Machines organized most to least in terms of their consumption of Snapshot storage. |
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Storage Top Swap Consumption
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| This report presents two independent views of information related to Swap storage. The first highlights data stores that possess the largest amounts of Swap storage. The second lists Virtual Machines organized most to least in terms of their consumption of Swap storage. |
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Storage Wasted Allocations
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| This report presents data stores that possess the largest amounts of wasted storage. Wasted storage is taken as storage used for purposes not directly associated with supporting the operation of a VM. |
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Storage Access IO Latency
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| This report presents two independent views of information related to Latency in accessing storage. The first highlights data stores having the largest amounts of storage access latency. The second lists Virtual Machines organized most to least in terms of latency in accessing storage. |
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Storage Access IOPS
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| This report presents two independent views of information related to IOPS for storage. The first highlights data stores that possess the largest usage of IOPS. The second lists Virtual Machines organized most to least in terms of their use of IOPS related to storage. |
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Storage Access IO Latency - 30 Days
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| This report presents two independent views of information related to Latency in accessing storage. The first highlights data stores having the largest amounts of storage access latency. The second lists Virtual Machines organized most to least in terms of latency in accessing storage. |
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Storage Access IOPS - 30 Days
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| This report presents two independent views of information related to IOPS for storage. The first highlights data stores that possess the largest usage of IOPS. The second lists Virtual Machines organized most to least in terms of their use of IOPS related to storage. |
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Storage Access IO Latency - 7 Days
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| This report presents two independent views of information related to Latency in accessing storage. The first highlights data stores having the largest amounts of storage access latency. The second lists Virtual Machines organized most to least in terms of latency in accessing storage. |
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Storage Access IOPS - 7 Days
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| This report presents two independent views of information related to IOPS for storage. The first highlights data stores that possess the largest usage of IOPS. The second lists Virtual Machines organized most to least in terms of their use of IOPS related to storage. |
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Datastore Group Summary
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| Datastore Group Summary |
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Data Store Summary
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| Data Store Summary |
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Monthly Overview with Cluster Summary
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| This report shows monthly statistics for the enterprise as a whole, and a monthly summary for each cluster. |
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Host Monthly Individual Cluster Summary
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| Monthly Individual Cluster Summary |
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Host Top Bottom Capacity Grid Per Cluster
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| Host Top Bottom Capacity Grid Per Cluster |
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Utilization Day Over Day by Hour
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| This report shows average hourly utilization measurements compared day-over-day for the two days indicated. All machines in the infrastructure are included in the averages. |
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Utilization Levels by Hour
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| This report shows by-hour averages for CPU and Memory utlization measurements for Physical and Virtual machines. Averages are rolled up for all machines. |
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Utilization Week Over Week by Day
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| This report shows average daily utilization measurements compared week-over-week for the two weeks indicated. All machines in the infrastructure are included in the averages. |
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CLOUD
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Optimize Cloud
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| Scale workloads and buy reserved instances |
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Migrate to Cloud
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| Migrate workloads to the Cloud as IaaS or PaaS |
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ON-PREM
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Optimize On-prem
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| Scale or move virtual machines and consolidate hardware |
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Add Virtual Machines
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| See the impact of adding more virtual machines to your environment |
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Virtual Machine Growth
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| Add Virtual machines in a projection plan |
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Hardware Refresh
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| See how many new hosts you need when you upgrade |
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Host Decommission
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| See whether you can support your current load if you shut down a host |
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Virtual Machine Migration
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| Move virtual machines from one cluster to another |
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Merge Clusters
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| Create a super cluster to leverage your hardware |
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Alleviate Pressure
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| Move virtual machines from a hot cluster to a cold cluster |
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Custom Plan
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| Create your own plan |
| Workload Optimization Manager plans run simulations for what-if scenarios that explore possibilities such as: |
| Migrating on-prem workloads to a public cloud |
| Optimizing the costs and performance you see on the public cloud |
| Optimal workload distribution across existing resources |
| Changing hardware supply |
| Impact of downsizing, or removing resources |
| To run these scenarios, Workload Optimization Manager creates a snapshot copy of your real-time market. It then uses the Economic Scheduling Engine to perform analysis on that snapshot market. You can modify the snapshot by changing the workload, adding or removing hardware resources, or eliminating constraints such as cluster boundaries or placement policies. |
| As it runs a planning scenario, Workload Optimization Manager continuously analyzes the snapshot market until it arrives at the optimal conditions that market can achieve. |
For further information or to book a demo, contact us today.