Big Data. Big Decisions
InformationWeek
Special Coverage Series

Commentary

George Crump

How Server-Side Storage Memory Impacts VDI Costs

Server-side storage memory can provide a cost-effective solution to VDI projects if you overcome challenges in mobility and data protection. Here's how.

In my last column I posited that advances in storage technology -- mostly innovative use of memory-based storage -- is making virtual desktop infrastructure (VDI) projects more likely to generate a return on investment beyond just an operational one.

Moving beyond operational VDI project justification is critical for the large-scale deployment of VDI projects. It is simply easier to justify to non-IT decision makers something that will save the organization dollars than it is to rationalize something that will save IT department time or increase security.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

I see three key areas where flash and DRAM (as storage) are being used to significantly increase virtual desktop density (which saves money and improves user acceptance by increasing performance): server-side storage memory, network caching and shared SSD appliances/arrays. In this column I'll discuss server-side storage memory, and I'll cover the other methods later.

I'm avoiding the use of server-side flash intentionally. Much of the innovation we are seeing involves the use of DRAM as the first tier of caching for virtual desktop images. VDI typically has a very mixed read/write workload, and because DRAM is ideal for writes it is a perfect complement to VDI.

[ For more on VDI and storage solutions, read Is Storage Saving Virtual Desktop Infrastructure? ]

Thanks to the capacity-savings capabilities of the hypervisors, thousands of persistent desktop images can be stored in a very small storage space, which overcomes DRAM's cost challenges. But these capacity-saving techniques typically have a high level of latency caused by their need to dynamically allocate writes. DRAM's aforementioned write performance capability overcomes the write performance penalty of the capacity-saving techniques. Further, some products perform compression and/or deduplication in the RAM cache space itself, making RAM utilization even more efficient.

The challenge with DRAM is its volatility. To maintain performance, these products must cache both reads and writes, which risks data loss until the write is flushed to permanent storage. This may be a generally acceptable risk since this is desktop data, but some users will likely push back.

One solution is a non-volatile DRAM solution, as discussed in this article. A more common approach for users who don't want to take that risk is server-side flash, in either in PCIe or SSD form. As we'll discuss in the upcoming webinar Is PCIe Dead?, while PCIe is considered the performance leader, drive form factor SSDs are gaining ground and certainly have a cost advantage.

Challenges to Server-Side Storage Memory

There are several challenges to server-side storage memory. First, it inherits all the challenges of any directly attached storage device. Data protection like RAID is not typically built in as it is on a shared storage system, and the capacity of the SSD or DRAM is isolated to the server in which it is installed. It might be too big or too small, and it can't be easily allocated to other servers. As mentioned above, however, the actual capacity needs per server should be relatively small, so this may not be a significant issue.

The greater challenge is that VDI mobility is hampered. More software caching solutions are now integrated with the hypervisor so that they know to evict the cache prior to a VM migration. But this means that the Virtual Desktop may see decreased performance until its unique data is re-cached on the new server. How big a problem this is depends largely on how often you migrate virtual desktops between hosts.

In my next column I'll discuss network-based caches and shared flash arrays, both of which overcome the challenges discussed here, but with the added cost of an appliance and/or storage system. They also, of course, add the potential latency of the network. I'll also provide some guidance on how to choose between the three options.

Attend Interop Las Vegas May 6-10 and learn the emerging trends in information risk management and security. Use Priority Code MPIWK by March 22 to save an additional $200 off the early bird discount on All Access and Conference Passes. Join us in Las Vegas for access to 125+ workshops and conference classes, 300+ exhibiting companies, and the latest technology. Register today!



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.