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Easing storage woes with virtual infrastructure performance management

Dave Bartoletti

As virtualization is deployed in production environments, experienced users are demanding production-quality performance management and optimization technologies to maintain service levels. The

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Taneja Group has identified a new category of emerging technologies -- which we have labeled virtual infrastructure optimization, or VIO to address these demands.

For more on optimizing virtual infrastructure management:
Virtual performance management tools' must-have features

Evaluating virtualization management diagnostic tools

The first tip of this three-part series on VIO discusses Taneja Group research on how the dynamic nature of virtualization necessitates advanced performance management technologies in production environments, especially when virtual storage is involved.

Traditional server consolidation planning
In the past, server consolidation for development and testing generally improved performance because larger, more powerful physical servers were used, shared storage was implemented and test and development virtual machines (VMs) were often idle. Sharing created better service because shared resources were often overprovisioned. Server consolidation ratios (enabled by more efficient use of available CPU cycles) were adequate and saved enough money to justify excess storage and memory capacity.

As a result, server virtualization planning to date has been mainly capacity driven. Performance gains experienced by users are often a coincidence as opposed to having been engineered. When contention issues arise, they're usually resolved manually by moving a VM or resizing it. Planning solely in terms of capacity - - coupled with reactive troubleshooting - - in a virtualized production environment can mask serious underlying architectural problems and become operationally overwhelming. Enterprises that have deployed mission-critical applications on virtualized infrastructures have exposed some hidden, complex contention problems. As virtualization continues to evolve, it demands a new class of performance planning and optimization tools.

Enterprise virtualization demands advanced management technologies
In IT operations, it's well-known that you can't manage what you can't measure. Traditional IT operations have focused on element management tasks such as measuring the behavior of servers, switches, storage arrays and network devices. Virtualization changes the game drastically because these elements are now mobile, dynamically reconfigured and connected to one another on the fly. The runtime interaction of elements has become as important as their individual operating profiles. As a result, a VIO approach must cross domains and focus on the performance of the entire virtual infrastructure.

VIO technologies enhance element management and server capacity planning. As discussed, the mobility of virtual machines and the nature of their connections to other physical and virtual resources in an infrastructure create capacity problems. Existing technologies –often designed for static environments-- haven't adequately addressed these capacity issues.

Taneja Group research validates this premise. The research reveals that a lack of virtual infrastructure visibility leads more than 85% of enterprise customers to rely on initial conditions testing and internal best practices to estimate and construct proper configurations. Moreover, lack of runtime visibility leads some VMware customers to limit their use of live migration (or VMware VMotion) in production because they have no way of determining its effect on storage performance. These restrictions diminish the benefits of virtualization, reduce consolidation rates and increase the overall cost of virtualized applications.

Contention issues with virtualized storage
One area where virtualization compounds these management and monitoring issues is at the virtual storage level. When server virtualization and storage virtualization are combined, new contention issues arise that expose a lack of end-to-end visibility across the server and storage domains. More than 70% of VMware deployments use storage virtualization -- most often with a Fibre Channel storage area network (SAN) -- making performance at the storage level integral to overall application performance. Storage I/O latencies are 10 to 100 times greater than server CPU and memory latencies, and are more likely to impact overall infrastructure performance.

Also, in many enterprises, storage is managed by a specific operations team with unique skills and special tools. As a result, there may be adequate element visibility in both the server and storage domains, but if the data isn't integrated there isn't a clear picture of who "owns" a performance issue. Add to this a complex, multivendor storage infrastructure and VM architectures that virtualize the I/O path, and it's clear that storage optimization is essential.

In part two of the series, we'll explore solutions to the lack of visibility and instrumentation in virtual environments and how they can deliver an optimized virtual infrastructure.

 
Dave Bartoletti is a senior analyst and consultant in the virtualization practice at Taneja Group. Bartoletti covers companies, trends and technologies in the server, storage, and network virtualization markets with a focus on management tools and strategies. Prior to joining Taneja Group, Bartoletti was the vice president of marketing at Enigmatec, a pioneering virtualization management vendor. Bartoletti has more than 20 years of technical, operational and marketing experience as an executive at Tibco, IBM and Fidelity Investments. He can be reached at dave@tanejagroup.com.
 


 

This was first published in May 2009

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