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Reduce application discovery cycles by 40%

Sync your CMDB with your infrastructure to accelerate the data cleansing cycle and application discovery process.

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Reduce day-1 public cloud cost by 50%

Over half of public cloud cost comes from storage—and not all applications must move as-is. Make smarter decisions with cloud mapping and cost details that account for your real storage IO demand.

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Improve workload efficiency by 50%

Get AI-powered recommendations to ensure the highest possible hypervisor CPU and memory utilization at the lowest cost without affecting performance.

Crucial Workload Information to Determine the Optimal Target Destination for Your Applications

Virtana WP is the leading agentless solution that applies our unique data science algorithms to high-fidelity and time-series data so you can determine whether to retain applications on premises or migrate them to new hardware or private/public clouds.

Common Use Cases Organizations Turn to Virtana Workload Placement to Solve

  • Refresh Cycles – Deciding on workload placement.
  • Mergers and Acquisitions – Discovery of applications and dependencies.
  • Security audits – Infrastructure NetFlow discovery (Ports, IP etc.).
  • Migration to the cloud or to new hardware.
  • Decrease on-premises expenses and optimize workloads.
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Agentless Application Discovery

Reduce the time needed for the data cleansing cycle, application discovery, and CMDB updates.

  • Get inventory, network flows, and high-fidelity time-series data to accurately characterize the workloads supporting your applications.
  • Reveal unknown applications in your environment or applications that may be missing from your CMDB.
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Application Dependency Mapping (ADM)

Accelerate and improve decision-making with better and more comprehensive data.

  • Quickly identify application dependencies, separating business applications from shared services such as domain services and monitoring applications.
  • Get detailed application dependency information when the application is acting as a server, as well as when the application is acting as a client.
  • Enrich your decision-making data set with ingress and egress traffic, device IP addresses, network services, port usage, port number, number of dependent applications, external and internal IP endpoints, and more.
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Move Group (MG) Definitions

Reduce unplanned migration disruptions with powerful data science algorithms to identify groups of workloads and other application elements that should be moved together.

  • Use MGs to quickly separate application dependencies.
  • Leverage MG suggestions to test “what if” target environment scenarios.
  • Strategically design “move waves” or migration events.
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Rightsized Cloud Mapping and Cost

Accurately select the best placement option—private cloud, public cloud, or on-premises—for your applications.

  • Get cloud mapping and costs that include compute, disk storage, and egress traffic.
  • See results statistically grouped by the workload’s time-series demand characteristics, such as as-is, peak value, and 99th and 95th percentiles.
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Origin Baseline Assessment

Strengthen your strategy with an additional “go/no-go” cloud migration gate for candidate workloads.

  • Reveal rogue workloads that are naturally unfit to migrate to the cloud (e.g., bully or zombie virtual machines).
  • Understand the health, utilization, and performance of the targeted workload as a reference to preserve SLAs and reduce risk from the rest of the environment (e.g., some workloads may become on-premises dependencies to migrated workloads).
  • Uncover on-premises or private cloud rightsizing opportunities as well as decommissioning opportunities.
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WP - Origin Baseline Assessment