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The Yin and Yang of Memory Overcommitment in Virtualization

White Paper Published By: Kingston
Kingston
Published:  Feb 15, 2011
Type:  White Paper
Length:  22 pages

Today's IT departments are challenged to understand the dichotomy between the positive and negative aspects-or "Yin and Yang"-of virtualization. In this informative new report, co-branded by Kingston Technology and VMware, virtualization architects, consultants, or any IT executive involved on an enterprise scale initiative will learn how to balance the positive and negative effects of memory utilization in virtual infrastructures to better handle system workload and priority--while improving server utilization. High consolidation ratios can improve server utilization, reduce energy consumption, and give IT departments fewer physical servers to manage. However, the quest for these high consolidation benefits can lead to memory overcommitment, a common occurrence when memory consumed exceeds the physical server memory-and which can negatively impact workload performance. In this white paper, you'll learn: .How VMware ESX 4.0 allocates and optimizes memory for efficient utilization, while balancing performance and memory reclamation .How memory overcommitment issues caused by memory ballooning and VMkernel swapping can affect performance-and why capacity planning and performance monitoring are key .Why striving for a balance between memory performance and memory reclamation is the key to driving higher consolidation ratios This white paper is a must-have for professionals working with virtualization. It offers insights into controlled tests to show how VMware ESX 4.0 manages memory while under memory pressure.



Tags : 
virtualization, memory overcommitment, memory performance, memory reclamation, vmware, memory utilization, consolidation ratios, server memory, server utilization, memory ballooning, vmkernal swapping, capacity planning, vmware esx 4.0, corporate governance, analytical applications, business intelligence, database development, data integration, data mining, data quality

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