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CiRBA Unveils Version 4.5

TORONTO -- CiRBA Inc., a leader in Data Center Intelligence, today announced the release of Version 4.5 of its leading virtualization and consolidation analysis software. With Version 4.5, CiRBA introduces Proactive Resource Placement capabilities that enable data center managers to make more efficient and optimized use of virtualized infrastructure. Also with Version 4.5, CiRBA announces its support of Unicode, enabling the organization to offer its in-depth analysis to data centers worldwide.

Proactive Resource Placement

A critical aspect of successful virtualization and consolidation planning is thorough workload analysis for both the initial placements of consolidated resources and the ongoing optimization of utilization and performance. CiRBAs Proactive Resource Placement capability advances workload planning and management by leveraging historical utilization patterns and personalities, business rules and configuration constraints to proactively place VM’s to best serve the coming workload. This unmatched proactive analysis combined with integrations to virtual infrastructure management software such as VMware virtual center offers organizations the safest, most accurate way to truly take advantage of resource pools.

This new capability includes options for analyzing day-of-week and day-of-month activity level patterns for any selected historical period including the last quarter, the last year, or even several years of operational history. This is enhanced through CiRBA’s underlying flexibility in gathering data, which includes support for CiRBA-supplied instrumentation, as well as importing of existing data from sources such as MS MOM, Perfmon, SAR, Compuware Vantage, HP Measureware, BMC and others.

“Currently data center managers or management software use short-term utilization trends to make decisions on where to place resources,” said Andrew Hillier, CiRBA Co-Founder and CTO. "Proactive Resource Placement enables organizations to leverage historical data to prepare for changes in workloads in advance. This enables optimal decisions about where to place important resources to maximize utilization and performance throughout the data center.”

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