can have as much impact as contention on a shared host, or more. Consider the case where a rogue VM overloads shared storage: hundreds or thousands of VMs will be slowed down.

Functionality that allows isolating and managing contention when it comes to networking and storage elements is only now reaching maturity and entering the mainstream virtualization scene. Designing a virtualization technology stack that can take advantage of such features requires engineering work and a good amount of networking and storage expertise on behalf of the enterprise customer. Some do that, combining exotic network adapters that provide the right cocktail of I/O virtualization in hardware with custom rack, storage, and network designs. Some opt for the riskier but easier route of doing nothing special, hoping that system administrators will cope with any contention issues as they arise.

GUIs. Graphical user interfaces work well when managing an email inbox, data folder, or even the desktop of a personal computer. In general, it is well understood in the human-computer interaction research community that GUIs work well for handling a relatively small number of elements. If that number gets large, GUIs can overload the user, which often results in poor decision making. 7 Agents and automation have been proposed as solutions to reduce information overload. 6

Virtualization solutions tend to come with GUI-based management frameworks. That works well for managing 100 VMs, but it breaks down in an enterprise with 100,000 VMs. What is really needed is more intelligence and automation; if the storage of a virtualized server is disconnected, automatically reconnecting it is a lot more effective than displaying a little yellow triangle with an exclamation mark in a GUI that contains thousands of elements. What is also needed is interoperability with enterprise backbones and other systems, as mentioned previously.

In addition, administrators who are
accustomed to the piecemeal systems
management of the previrtualization
era—managing a server here and a
storage element there—will discover
they will have to adapt. Virtualiza-
tion brings unprecedented integra-
tion and hard dependencies among
components—a storage outage could
mean that thousands of users cannot
use their desktops. Enterprises need
to ensure that their operational teams
across all silos are comfortable with
managing a massively interconnected
large-scale system, rather than a col-
lection of individual and independent
components, without GUIs.

conclusion

Virtualization holds promise as a solution for many challenging problems. It can help reduce infrastructure costs, delay data-center build-outs, improve our ability to respond to fast-moving business needs, allow a massive-scale infrastructure to be managed in a more flexible and automated way, and even help reduce carbon emissions. Expectations are running high.

Can virtualization deliver? It absolutely can, but not out of the box. For virtualization to deliver on its promise, both vendors and enterprises need to adapt in a number of ways. Vendors must place strategic emphasis on enterprise requirements for scale, ensuring that their products can gracefully handle managing hundreds of thousands or even millions of VMs. Public cloud service providers do this very successfully. Standardization, automation, and integration are key; eye-pleasing GUIs are less important. Solutions that help manage resource contention end to end, rather than only on the shared hosts themselves, will significantly simplify the adoption of virtualization. In addition, the industry’s ecosystem needs to consider the fundamental redesign of components that perform suboptimally with virtualization, and it must provide better ways to collect, aggregate, and interpret logs and performance data from disparate sources.

Enterprises that decide to virtual-
ize strategically and at a large scale
need to be prepared for the substantial
engineering investment that will be
required to achieve the desired levels
of scalability, interoperability, and op-
erational uniformity. The alternative
is increased operational complexity
and cost. In addition, enterprises that
are serious about virtualization need a
way to break the old dividing lines, fos-
ter cross-silo collaboration, and instill
an end-to-end mentality in their staff.
Controls to prevent VM sprawl are key,
and new processes and policies for
change management are needed, as
virtualization multiplies the effect of
changes that would previously be of
minimal impact.

acknowledgments

Many thanks to Mostafa Afifi, Neil Allen, Rob Dunn, Chris Edmonds, Rob-bie Eichberger, Anthony Golia, Allison Gorman Nachtigal, and Martin Vazquez for their invaluable feedback and suggestions. I am also grateful to John Stanik and the ACM Queue Editorial Board for their feedback and guidance in completing this article.

 

Related articles on queue.acm.org

Beyond Server Consolidation

Werner Vogels

http://queue.acm.org/detail.cfm?id=1348590

CTO Roundtable: Virtualization

http://queue.acm.org/detail.cfm?id=1508219

The Cost of Virtualization

Ulrich Drepper

http://queue.acm.org/detail.cfm?id=1348591

References

1. Bailey, M., Eastwood, M., Gillen, A., Gupta, D.

Server virtualization market forecast and analysis, 2005–2010. IDC, 2006.

2. Brodkin, J. Virtual server sprawl kills cost savings, experts warn. Network World. Dec. 5, 2008.

3. Goldberg, R.P. Survey of virtual machine research. IEEE Computer Magazine 7, 6 (1974), 34–45.

4. Humphreys, J. Worldwide virtual machine software 2005 vendor shares. IDC, 2005.

5. IDC. Virtualization market accelerates out of the recession as users adopt “Virtualize First” mentality; 2010.

6. Maes, P. Agents that reduce work and information overload. Commun. ACM 37, 7 (1994), 30–40.

7. Schwartz, B. The Paradox of Choice. HarperCollins, NY, 2005.

 

Evangelos Kotsovinos is a vice president at Morgan Stanley, where he leads virtualization and cloud-computing engineering. His areas of interest include massive-scale provisioning, predictive monitoring, scalable storage for virtualization, and operational tooling for efficiently managing a global cloud. He also serves as the chief strategy officer at Virtual Trip, an ecosystem of dynamic start-up companies, and is on the Board of Directors of NewCred Ltd. Previously, Kotsovinos was a senior research scientist at T-Labs, where he helped develop a cloud-computing R&D project into a VC-funded Internet start-up. A pioneer in the field of cloud computing, he led the XenoServers project, which produced one of the first cloud-computing blueprints.