"Virtualization is a proven software technology that is rapidly transforming the IT landscape and fundamentally changing the way that people compute." - VMware

To paraphrase a well-known politician, when it comes to adoption of virtualization, there are things we know, things we know we don't know, and things we don't know we don't know. This is pretty apt when we look at where we are with this uniquely disruptive technology.

Factors such as consolidation, cost savings, dynamic provisioning, and migration are driving most IT shops to experiment with some form of virtual machine product today. In the U.S., this has moved from back-room toying and development environments into full, public-facing application infrastructure systems. In Europe, many medium to large companies are in early stage deployment and experimentation mode.

There is good reason for this. We are feeling our way in partial darkness in many ways. We know that there are clear benefits to be had, but Proof of Concepts and lab experimentation are only indicative on certain levels; we don't know how our networks will react once we scale up into full production.

Suddenly 40 physical servers become 400 virtual ones. How will your network react? How will you manage the traffic flow to all those new IP addresses? Will you rebalance manually every time you provision new servers? Of course not. And what about your underlying data? Will you rebind the new virtual servers to underlying storage assets every time you kick start a new virtual machine? No.

For all of their benefits, virtual machines also add complexity, scale, and management challenges. Implementing virtualization without considering its impact on surrounding IT resources can lead to unexpected results. These critical areas may appear either immediately or over time, potentially months or years later.

Knowledge is the first step to avoiding surprises and showstoppers during production. What follows are the seven challenges that accompany any major virtual platform implementation or migration. Often these issues aren't seen during staging and testing and only appear when the virtual machines are asked to take on the same production load as physical machines. These pain points represent two cornerstones of the data center: network and storage.

1. Lack of performance and availability. Virtualization moves many I/O tasks tuned for hardware back into software. I/O intensive applications, like cryptographic processing applications for SSL, don't fare well when virtualized. Performance issues and virtual machine saturation (too many virtual machines running on one physical host) caused by virtual sprawl can cause application and storage network resources to be depleted at a much faster, and often unanticipated, pace.
2. Lack of application awareness. One of the limitations of hypervisor-based virtualization is that it only virtualizes the operating system. OS virtualization does not virtualize, nor is it even aware of, applications that are running on the OS. By adding an extra software management layer between the application and the hardware, the applications may run into performance issues that are out of their control.
3. Additional, unanticipated costs. One of the primary drivers for virtualization is cost reduction, driven by consolidating devices in the data center. But, once virtualization hardware and software is acquired, operational expenses can grow unbounded: headcount can increase or existing staff may require training to administer the new virtual machine platforms.
4. Unused virtualization features. It is often the case where these new technologies perform flawlessly in development and staging but they are unable to scale to production levels once deployed. First and foremost, network storage is a requirement for virtual platforms that implement live machine migration; direct attached and local storage will only work for running local virtual machines.
5. Managing explosive and unexpected growth. Although converting physical machines to virtual machines is an asset for building dynamic data centres (fluidity, disaster recovery, backups) virtual hard drives become extremely large flat files -- a typical Vista Ultimate install consumes ~15 gigs of local storage for the OS alone, not counting data files -- and storing these files can quickly become unmanageable. In a recent report from Enterprise Strategy Group, 54 percent of the customers surveyed reported some increase in storage capacity specifically tied to OS virtualization and the installation of virtual platforms. Eighteen percent of responders reported an increase of physical storage greater than 20 percent beyond their storage needs for physical servers.
6. Congested storage network. Planning large virtual machine migration moves can be a challenge to keep from flooding the storage network, and is virtual sprawl and unmanaged virtual machines begin to appear in the data center, unplanned virtual machine migrations can literally bring the network to a stand-still, even on a LAN.
7. Management complexity. Overlapping all portions of the data center, managing virtual machines as part of the complete management solution can be a struggle at best. If you are already using tools to manage the application and operating environments of each physical machine, by either using clients on the systems or by measuring application metrics on the wire (such as latency, response time, etc), management of the virtual machines themselves doesn't have to change.

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