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Most of us recognise that the Earth is warming and that — despite our planet’s temperatures having dramatically risen and fallen before — we humans must accept some measure of responsibility for the current changes.

Already consuming at least 1.1-1.5% of global power, and only forecast to grow ever-more rapacious, the data centres that power our information economy are surely one area in which we can, should, and must find ways to reduce consumption. And, although by no means perfect, data centre builders, operators and suppliers are paying attention. Individual servers are becoming more efficient. Buildings are being cooled by the wind and by toilets. Waste heat is warming homes. Newer facilities are being sited to save the planet (and money) by drawing power from hydro-electric schemes rather than coal, oil, gas, or the once-again-unpopular-and-scary Nuclear.

And then there’s solar. On the face of it, the ultimate renewable. The sun shines. It does so every day. It will continue to do so every day for millions of years to come. Every watt diverted to a data centre has absolutely no effect whatsoever upon the sunlight that the rest of us receive today, or that we shall receive tomorrow. There’s certainly a location trade-off to be made, as the sunshine rarely reaches the ground for much of the day in locations where the air is cool and damp enough for all that fresh air cooling to work, but there should certainly be a case to be made for both. If you’re in Iceland or Ireland or Oregon, sunlight is not something to rely upon for meeting your ravenous appetite for energy. But if you’re in sunnier climes, surely it’s a no-brainer?

Apple, for one, is constructing a 171 acre (69 hectare) solar farm next to its North Carolina data centre. That’s big. It’s apparently the biggest commercial deployment in the United States and — with some help from WolframAlpha — it’s also equivalent to 1.6 Vatican Cities or 13 Great Pyramids.

More tellingly, it’s also a lot of fields and trees.  If all those mirrors reduce the impact of Apple’s data centre on the environment, then maybe — just maybe — the loss of forest and farmland and open space is a cost worth paying. But Amazon’s James Hamilton does some maths, which he shares in a recent blog post, and he reckons that all the mirrors in that 69 hectares contribute around 3.2 MW to the data centre’s power requirements; requirements that Hamilton calculates to be around 78 MW. That’s 4%, which really is not that much at all. It’s worth noting that the figures for the solar array’s power output and the data centre’s consumption are only Hamilton’s estimates, but he tends to know what’s he’s talking about. In the absence of solid numbers from Apple, you can do a lot worse than believe the maths of someone like Hamilton.

So… why the enthusiasm for solar? Are data centre operators taking reductions where they can get them, and calculating that a 4% contribution to the fuel bill is worth 69 hectares? They might be right. Maybe. Or are they being more callous and calculating than that? Are the ‘savings’ on energy bills and greenhouse emissions essentially negligible, and are trees and fields being turned over to big mirrors simply so that companies can look good? They get a tick in the “green” box. They get a mention from Greenpeace. Customers, consumers and law makers think they care. Whilst actually, they don’t care at all.

Related articles

• The Switch SuperNAP data centre – one of the most impressive I’ve been in (greenmonk.net)
• Apple slaps mega-solar panel field on new ENORMO data centre (go.theregister.com)
• In cooler climates, outdoor air systems can save energy dollars for data centres, retailers, warehouses (cleanbreak.ca)
• Colt Telecom and Verne Global’s dual renewably sourced data centre in Iceland (greenmonk.net)
• Facebook Data Centre Uses As Much Power As The Entire County It’s In (gizmodo.com.au)
• Greenpeace, Facebook in truce over energy (news.smh.com.au)
• Solar power gets public vote (evoenergy.co.uk)
• The revenge of Thomas Edison (business.financialpost.com)
• California’s Military Bases Could Generate 30x More Electricity From Solar Power Than They Consume (treehugger.com)
• Apple’s iCloud Has Solar Lining (wired.com)

Piyush Lumba, Director of Product Management for Azure Data Services at Microsoft, talks about what the Marketplace can do today and shares some of his perspectives on ways that the nascent data market space could evolve.

Following up on a blog post that I wrote at the start of 2012, this is the eighth in an ongoing series of podcasts with key stakeholders in the emerging category of Data Markets.

Related articles

• Data Market Chat: the podcasts are a-coming…(cloudofdata.com)
• Data Market Chat: Tyler Bell discusses Factual (cloudofdata.com)
• Data Market Chat: Hjálmar Gíslason discusses DataMarket.com (cloudofdata.com)
• Data Market Chat: Chris Hathaway discusses AggData (cloudofdata.com)
• Data Market Chat: Flip Kromer discusses Infochimps (cloudofdata.com)
• Data Market Chat: Nick Edouard discusses BuzzData (cloudofdata.com)
• Data Market Chat: Stephen O’Grady of RedMonk examines the bigger picture (cloudofdata.com)
• Data Market Chat: Shion Deysarkar discusses Datafiniti (cloudofdata.com)
• Big data in the cloud (radar.oreilly.com)
• ‘Roswell’: Another key component of Microsoft’s cloud strategy (zdnet.com)

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Last week, open standards body OASIS unveiled yet another shiny new standards effort. The OASIS Topology and Orchestration Specification for Cloud Applications (TOSCA) Technical Committee hopes to make it “easier to deploy cloud applications without vendor lock-in,” and to support moving from one cloud to another. The usual suspects — the likes of IBM, CA, and Cisco — are on board. The usual holdouts — Google and Amazon, of course — are not. So what is TOSCA trying to achieve? How does it fit alongside all the dead, dying, or ponderously deliberating cloud standardisation efforts that have gone before? And without the giants of the cloud, is there really any point bothering?

As I’ve probably mentioned before, involvement in various national and international standardisation efforts played a big part in my early career. I went to the working group meetings in odd (but often beautiful) locations. I participated in the conference calls. I engaged on the mailing lists. I drafted and edited and reviewed the documents. I completely buy into the idea that there is a place for foundational standards, developed through consensus-building and maintained for the long haul by organisations that stand apart from the vested interests and their competing agendas.

I also believe that there’s a time and a place for these standardisation efforts. Do it too soon, and we end up ossifying something that needs to be in a state of flux. When you don’t know what the best way to prepare a meal is, it’s too soon to print the recipe book. We need to try different approaches, and we need to be able to throw away the attempts that didn’t work out. More worryingly, standardisation efforts can be used for political ends. They can be little more than a rod with which to beat the (usually dominant) competition. At best a distraction, or a talking shop for those unwilling or unable to just get on and do something. At worst, one amongst a toolchest of dirty tricks in a broader war for hearts, minds, and — ultimately — wallets.

The cloud market is a fascinating place. There are leaders and there are followers. There is innovation, and there is competition. There is agreement, and there is debate. For all the rhetoric, and all the posturing, we really don’t yet know the right answer to many of the cloud’s questions.

Maybe TOSCA and the Open Data Center Alliance and IEEE and the rest are — still — too early, and should be content to let the market thrash out a few more of these issues before anyone tries to write anything down? And when it is time to write some stuff down, let’s make sure we focus on specific, finite, tangible, atomic tasks rather than “the cloud.” As Dave Roberts commented in regard to TOSCA’s scope;

“That goal is so large, that I think it’s probably unbounded. When problems get unbounded, the best you can ever hope to achieve is to solve a large enough subset of the problem that the solution is still interesting. If you can’t achieve that, people ignore the solution because it fundamentally doesn’t help them. There is always an ‘interesting’ part of the problem space that they have to solve a different way, and that undercuts the use of the partial ‘solution.’”

And as for Tosca? Things didn’t end well for her, did they? Might TOSCA’s fate, too, be sealed?

Related articles

• Tech giants back standard for cloud portability – InfoWorld (infoworld.com)
• Proposed spec aims to nix cloud lock-in (gigaom.com)
• On TOSCA and Cloud Standards. MyPOV (diversity.net.nz)

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British-born computer scientist Stephen Wolfram sees ongoing efforts to extend the Internet’s top-level domains (TLDs) beyond the familiar .com, .org, .uk etc as an opportunity to raise the profile of machine-readable data. In a blog post published yesterday, he argues that a new .data domain would increase “exposure of data on the internet—and [provide] added impetus for organizations to expose data in a way that can efficiently be found and accessed.” Whilst wholly in favour of Wolfram’s stated aim, I can’t help feeling that his suggested solution is at best unnecessary and at worst a worrying segregration of data from the ‘proper’ web that everyone else will continue to exploit.

Back in June of last year, the body responsible for coordinating the global domain name system approved a plan to permit new top-level domains (the letters after the final dot in an internet address — the .com in cloudofdata.com, the .uk in bbc.co.uk, the .edu in harvard.edu). Until recently, these top-level domains have been tightly controlled, with a small set of generic domains (.edu, .gov, .mil, .org, etc), a larger set of country domains (.uk, .fi, .nz, etc) and one or two others such as .eu. From tomorrow, anyone with $185,000 will be able to submit a proposal to create and manage a new top level domain, and it’s possible that there could eventually be thousands of them. Wolfram is keen to ensure that data doesn’t miss out on the ‘opportunity.’

As Wolfram himself recognises, there is already an awful lot of machine-readable data on the web. Some of it sits embedded within the web pages that humans read, with specially formatted code waiting to be triggered by the calendars, the address books, or the browser plugins of site visitors. Some of it is packaged up in data files, offered for download. And some of it waits inside a database, ready to be delivered in response to an API call or a query typed into a web form.

There is a growing enthusiasm for exposing this data for reuse. Government transparency agendas have driven public sector data sites like data.gov.uk and data.gov. Similarly, efforts such as data.open.ac.uk and data.southampton.ac.uk see universities beginning to consciously collect data sets together and offer them up for reuse. Similar efforts in the commercial world are less easy to point to, but that reticence has nothing whatsoever to do with the lack of a ford.data, boeing.data, ge.data or astrazeneca.data domain!

In some ways, the convention for gathering significant chunks of data on a data.xxx.yyy site echoes Wolfram’s intention, but with a number of advantages. Data without context is far less valuable than data with context. Much of that context may be inferred from the domain in which the data lives, with data delivered from a .gov or .edu (or .gov.uk or .ac.uk) site perhaps interpreted differently to data hosted on .com, .biz, or .xxx. Southampton University, the Open University, and the US Federal Government are able to gather data up and make it available for download via their existing data. sites if they choose. This offers human visitors to their sites a degree of convenience, whilst retaining the power and brand attributes of their existing domain. Gov.data, gov.uk.data, open.ac.uk.data, southampton.ac.uk.data, though? All are messy, in ways that Wolfram’s own wolfram.data would admittedly not be, and all are simply additional registrations that the institutions would have to pay for in order to stop someone else grabbing the domain.

At the end of the day, the machines don’t actually care. The existing data.open.ac.uk-type sites are human conveniences, not machine enablers. The computers, and the software they run, are quite capable of crawling the public web and finding accessible data wherever it lies on a site. There are plenty of reasons to continue embedding little snippets of data inside human readable web pages, regardless of whether you have a data.wolfram.com or a wolfram.data site. Content negotiation is becoming increasingly capable, such that there really is no need for what Wolfram calls a ‘parallel construct to the ordinary web’ at all. A human being arriving at a web site sees human readable content, whilst various software tools would automatically be presented with very different data or functions, optimised to their capabilities and requirements.

By all means, let us show the curious some of the existing techniques that work in making data more easily accessible. By all means, let us identify the gaps, the issues, the problems (none of which a new TLD even begins to address). Yes, let us definitely and unambiguously set about “highlighting the exposure of data on the internet—and providing added impetus for organizations to expose data in a way that can efficiently be found and accessed.”

But please, let us not be distracted by the false hope that adding yet another TLD to the babel that ICANN is about to unleash can do anything more than consign data to some online ghetto, wallowing unwanted, unloved and unused as companies and their customers lavish love, attention, and clicks upon the .com domain over on the ‘proper’ web.

Thanks to Raphaël Troncy, whose tweet first drew the story to my attention.

Related articles

• Is It Time For Computers To Have Their Own .Data Domains? (techcrunch.com)
• ICANN Pushes Ahead With January 12 Launch For New Top-Level Domains (wired.com)
• The biggest change in DNS since Dot-Com (wired.com)

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I am in Madrid this week, as a guest of Hewlett Packard. The company’s European roadshow, Technology@Work, is in town for two days, showing existing and prospective customers some of the ways in which HP’s Converged Infrastructure can help them meet the growing challenge of continuing to grow IT capacity as data centres fill, power grids reach capacity, and budgets fall.

A few of us took the opportunity to sit down with Iain Stephen (VP Enterprise Storage and Servers, UK & Ireland) and Martin Riley (Programme Manager for Technology@Work) from HP yesterday evening, and the result is now available as a podcast. Also participating in the conversation were HP’s Becca Taylor,  Martin Macleod, Massimiliano Galeazzi, Patrick Husband, and Hans Vredevoort.

The conversation was recorded on a shiny new Ivy Worldwide Blue Snowball microphone that none of us had ever used before, in a room that was a little bigger than we’d have liked. All in all, though, I’m pleasantly surprised by the result. Have a listen, and see what you think.

Disclosure: our expenses were covered by Ivy Worldwide, on behalf of HP.

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With apologies to Zanussi for the corny title, I had an interesting conversation with Axcient CEO Justin Moore and HP’s VP for Channel Strategy & SMB Meaghan Kelly about the issues of helping small and medium businesses cope with backup, disaster recovery, and business continuity.

Yesterday’s conversation was taking place in the context of today’s announcement from HP and Axcient; Axcient’s US data centres are moving to HP servers, networking and storage, and the appliance that the company puts on-site with customers will be an HP ProLiant server moving forward.

According to Moore, most SMBs use “4 or more” vendor solutions to “cobble together” a data protection solution. Basic application and data backup, disaster recovery from off-site backup, and business continuity in the event of hardware failure are all addressed separately, and it can be difficult to stitch the pieces together without dedicated — and expert — effort. I wonder how many companies, especially at the ‘S’ end of ‘SMB,’ simply give up on attempting anything but the most rudimentary on-site backup… and hope that nothing goes wrong?

Axcient’s solution is different, as the company offers a single appliance (an HP server, running Axcient’s applications) that can be deployed locally. There is no up-front cost for the appliance, with both it and the ongoing service being billed on a recurring monthly subscription. Software on the appliance handles backing up applications and data on servers, desktops and laptops across the business, and securely replicates changed data to one of Axcient’s US data centres for backup and disaster recovery. Should critical hardware fail within the business, a virtual machine can be started on the appliance to fulfil the role of the failed equipment until it is repaired or replaced. Indeed, Moore suggested that the ProLiant server they’ve selected would be capable of taking the place of up to seven servers if required; presumably with a perceptible loss of performance. Slow responses from a straining appliance are no doubt preferable to no response at all from seven dead servers.

Axcient’s data centres are currently in the United States, raising the spectre of PATRIOT Act, European Data Protection legislation, data territoriality and more for those of us outside the US. Moore recognises this issue, and says that the company is in the process of opening a Canadian data centre. Sites in Europe and elsewhere may well follow.

Both HP and Axcient are pitching this solution to the entire SMB market; that’s everything from the lone consultant operating out of a home office up to businesses employing 1,000 staff. They’re certainly right to address the whole market and the top end is probably more lucrative, especially for HP’s channel partners. I was particularly interested, though, in the value that this might deliver to small businesses struggling to do much more than replicate core data to an external hard drive under their desk. Here, the $150 per month ballpark that Moore mentioned is expensive, but perhaps a sound investment if data and systems are key to business success.

With their reliance upon asynchronous data connections and effectively consumer-grade connectivity, one significant issue for small businesses is the practicality of trickling all of their on-premise data slowly up to an Axcient data centre before they can begin to reap benefits. With their ‘rapid seeding service,’ Axcient appear to have thought of this. If connectivity issues mean that network-based methods to replicate all your on-premise data are going to be too slow, it’s possible to transfer the data to a storage device attached to the appliance, “ship that in a locked container” to an Axcient data centre, and have the data loaded there to be available within 48 hours. The incremental backups of new and changed blocks then take place over the network without causing issues. Simple, obvious, but a sign that Axcient appears to be considering the needs of their smaller customers.

Cukier – Strata so far been focussed on the tools and toolmakers. Real-world applications will actually lead to biggest changes, but we haven’t really heard from them here. Big Data – big, fast, smart, messy.

Varia – Big Data Clouds. 3 case studies from AWS customers. Razorfish… cost of storing and analysing data. Best Buy wanted to analyse clickstream logs and predict patterns etc to aid advertising placement. 3.5bn records, 71 million cookies, 1.7 million targeted ads per day. Using AWS allowed move from upfront $500k CapEx to $0, ‘significant’ recurring OpEx to manageable costs, etc. Led to 500% increase in return on ad spend… but led to huge data quantities.

Yelp – 8 countries, 50 cities, 100GB of logs per day… 200 Elastic MapReduce jobs per day on Amazon, processing 3TB of data.

Etsy – >500GB web logs per day, 400K sellers.

Use cases useful… but I’d rather have heard them from the customer than from Amazon.

Storage getting cheaper. Analytics getting faster. Analytics getting smarter…

Pereira – ‘what happens when you turn on the lights?’ Capacity planning etc an increasingly complex issue for power companies. Smart algorithms, cloud computing and big data analysis creating opportunities to get better at these decisions. Deep modelling of resources. Model ‘every single generator in the country,’ etc. These models ‘give better results, because the situation changes dynamically.’

Hurwitz… big data ‘has been a game changer in the legal industry.’ ‘It’s a necessity if your legal department is to be successful.’ When a company gets sued, it goes through a discovery process; it gathers up all the relevant information and passes it to lawyers on both sides. It’s a complex process… and there are consequences if you miss things. SOLR, Lucene, Hadoop and a range of other tools used by legal teams to build searchable pools of the relevant data. Back-end works, but UIs struggle. Machine learning has been applied to classifying documents more quickly, accurately and affordably.

Cukier – data as by-product? Everyone using data internally, and using Big Data to do new things with old data. Has anyone taken data they’ve generated, used it internally, and then realised that it has tangible external value?

Pereira – Colombia sells their database to investors overseas. Energy companies exchange raw data in a marketplace.

Varia – amazon.com and amazon web services see value in DaaS. eg amazon.com products have lots of associated metadata… which is available through an API. Also companies like 80legs crawling the web, storing the data on AWS, and selling the crawl results to third parties.

Questions – how do you get a community (like legal) comfortable with using these tools?

Hurwitz – legal community was resistant. Economic reality that they had to embrace these tools to enable court-mandated e-discovery. A large case could include costs of millions of dollars, just to gather data before the case begins.

The notes that follow are a rather raw summary of some of the things I’m hearing. Later in the week, I’ll try to come back and extract the main issues in a rather more polished form.

Up first, Mike Driscoll of Metamarkets, talking about Mining the Tar Sands of Big Data.

Trying to frame conversation; why are we all here? Why is now the time that we’re all beginning to focus on ‘Big Data’ ? Drawing analogy with the tar sands in Alberta; lots of oil there, but it’s been expensive to extract.

If ‘information is the oil of the 21st century [as Gartner has suggested], then Big Data are the tar sands;’ lots of data, sitting in our data centres, waiting for us to invest in extracting usable data. Expensive, painful, but ultimately valuable.

‘Attack of the exponentials;’ cost of storage, bandwidth and compute falling exponentially. Number of nodes on the network rising exponentially. Intersection creates ‘data singularity.’

Unlike oil, data abundant and renewable. Like oil, extraction of data creates value. Cheaper and easier to extract value from data than ever before.

Three forces reshaping data landscape; sensor networks, cloud computing, and machine learning.

Sensor networks; now prevalent, all-pervasive, ubiquitous, and typically connected. Generating vast amounts of data.

Cloud computing; ‘used to mean everything and nothing.’ But real advantage is that it turns CapEx into OpEx.

Machine learning; gives us the capabilities to process the flood of data, intelligently. Smart Planet, Smart Grid, Smart Business, etc. Driverless cars, spam filters, recommendation engines all drawing upon Machine Learning ideas. All iterating and improving with increasing rapidity. Unlike Cloud and sensors (which are becoming commodities), machine learning algorithms are – and may remain – a competitive advantage.

Four consequences of all this; battle for finite number of good data scientists, changes in the way that data is published (and valued), the end of privacy (?), the rise of data startups.

Battle for data scientists; difficult to hire people who can munge, interpret, and tell stories with data. And everyone last night at bigdatacamp was ‘hiring’.

Retailers, banks, online publishers, etc have tended to hand over the keys of data management to third parties. Seeing pendulum shift the other way, as companies recognise the value of their data and seek to control it – and realise the value. Tension with ‘open data,’ data to the cloud, etc?

Privacy – not about shifting access to data, but about more accurately defining the ways in which it may be used.

Q&A

‘What sort of educational background does a data scientist need?’

knowing some stats helps. knowing some programming helps. But curiosity is key. Not sure there’s a degree out there. Pick up the skills if you have the right mindset. ‘You have to be a bit of a hacker,’ says Mike.

‘What are the three big problems that data science will solve?’

Making sense of the world around you; Freakonomics, for example. Taking data and making sense of how the world is working. Scaling up decision making, so that a data-powered story can be presented in a way that lets people make intelligent decisions.

Next, Barry Devlin from 9sight Consulting talks about The Data-Driven Business and Other Lessons from History.

‘the old guy who has been brought along to talk about history,’ and ’illegitimate grandfather of data warehousing’

Address Past, Present, and Future.

Past – the origins of Data Warehousing

Data Warehouse architecture work at IBM in Europe in the mid-80s.

‘Big Data’ (a couple of hundred MB, at the time) created need to structure the Enterprise Data Warehouse in a particular way. Led to silos. ‘Hard information’ only, at the time. Warehouse designed in a well-architected fashion. Ensures that data flows in a single direction. Possibly too regimented for the 21st century?

Lessons?

Information quality and reliability are key; Master Data Management, etc. This is unlikely to change.

Data volumes and variety have presented big challenges over the years. Expectations and business demands outstrip technological capabilities. Organisational and political issues hamper progress. This is unlikely to change.

Exploration and analysis drives innovation.

Present – Business and technical challenges

3 key trends in business are driving rapid change; closed loop business, massive information volumes, collaboration driving innovation.

Really important to stop talking about ‘unstructured information;’ that’s just noise. Information has structure. Instead, hard information is data; tables, structure, computer-oriented. Meaning and values have been separated. Metadata explicit, and formally modelled. Soft information is not well defined, it is by and for people, it mixes meanings and values. Metadata is implicit, tacit, or non-existent.

Moving from information we understand – and control – to information outside the enterprise that we don’t. Implications for quality, meaning, etc.

Future – a new architecture?

current architecture 25 years old – time for a change?

Next, Bob Page from eBay, talking about Building the Data-Driven Organisation.

eBay “fascinated with numbers;” early 1999 screenshot of homepage, showing lots of stats.

What role does data play in the business? Using Analytics focussed on big buckets; velocity, efficiency, trust, etc.

Efficiency drive – lower insertion fees to list/sell new products by 99%. Decision based on analysis of data?

Trust – top-rated sellers constantly monitored to ensure algorithm is reflecting reality. 22% of sales from trusted sellers in 2009. Now 32%. Actually surprised it’s not higher…

eBay handled $2Bn of sales on mobile devices last year.

Analytics and continual data analysis drives all the apps, trust metrics, etc.

Some figures… 50 TB/day of new data, etc. Lots of other numbers on slide, but it was only up for seconds…

Analytics work in marketing, sales, product dev, and all areas of the business.

More than 85% of eBay’s analytial workload is new and unknown; design for the unknown. Enable exploration of the data, rather than just reporting of established metrics.

Machine Learning: Data trumps Algorithms. This is the promise of Big Data; existing algorithms get better as you throw more data at them. It’s cheaper to throw more data at an algorithm than to invest in developing new algorithms.

Enterprise Data Warehouse for transactional data; purchase history, etc. Behavioural data to track clickstreams, impulse purchases, etc… much larger than the amount of transactional data in traditional systems. No technology silver bullet for the behavioural data; optimise for concurrency, or TCO, or CPU usage, or flexibility, or storage, or governance? Those priorities change the tool you should use.

eBay built a 500-node Hadoop cluster in June 2010. Now they have a much bigger cluster.

Data Marts; ‘a reality for many of us,’ because businesses need to give control to the user. Don’t want infrastructure team/ data scientists as bottle neck. Totally opposite to attitude expressed by previous speaker. But Data Marts end up being very expensive and inefficient. eBay have built a virtual data mart; views onto a single pool of data. Far more efficient, in theory.

And then I had to slip away, and miss the final session before lunch…  More later…

San Jose-based Cirtas emerged from stealth back in September 2010 with a $10 Million (€7.86 Million then) Series A funding round, their novel Bluejet hardware appliance, and the backing of Amazon.

Today they’re back, with a new CEO and another $22.5 Million (€16.6 Million) in the bank. The Series A investors — New Enterprise Associates, Lightspeed Venture Partners and, unusually, Amazon — are joined by Shasta Ventures and Bessemer Venture Partners for a Series B round that positions the company for some rapid growth.

Cirtas’ Bluejet Cloud Storage Controller is a hardware appliance, deployed in the data centres of medium and large enterprises to simplify the task of integrating existing on-premise Tier 2 and Tier 3 storage with disparate Cloud-based solutions such as Amazon’s S3, EMC Atmos, Iron Mountain and AT&T’s Synaptic Storage as a Service.

Talking ahead of today’s announcements, new CEO Gary Messiana suggested that Cirtas’ decision to deliver a hardware appliance rather than a software-based solution reflects their deep understanding of both their customers and the sales channel. Messiana is not the first to suggest that buyers of enterprise storage are a conservative bunch, and he’s certainly not criticising that conservatism; when business continuity depends upon the decisions you make and the systems you buy, you’re hardly going to take unnecessary risks, now are you? A piece of physical hardware that you can see, touch (and even hug) delivers an element of familiarity that appears to appeal to enterprise-class customers taking the first steps to leverage Cloud-based storage within their existing solutions portfolio. With Bluejet, Messiana suggests, control continues to reside inside the data centre. The Cloud provider(s) to which the appliance directs data are simply (dumb?) utilities upon which the enterprise may choose to draw in a manner abstracted by Cirtas’ technology. A hardware solution also suits the channel-based (rather than direct sales) model by which these companies tend to buy. As Messiana notes,

“[much of] the money changes hands in the channel… and [channel partners] know how to sell tin.”

Formerly an entrepreneur in residence at Series B participant Bessemer, Messiana talks persuasively about the clarity of proposition and go to market strategy that drew him to Cirtas. Drawing upon pre-Bessemer experiences as CEO of traffic optimising Netli (acquired by Akamai in 2007), Messiana argues that the shift off-premise makes expertise in moving data just as critical as the data storage skills of incumbents. Might Akamai, Limelight and their ilk make inroads into this market, at the expense of EMC, HDS, 3Par et al, I wonder?

In storage as in so much else, big incumbent enterprises are very different from smaller or younger companies. Whilst startups and SMEs might be quick to embrace entirely virtual solutions — often starting in the Cloud rather than migrating to it from elsewhere — the ‘multi-billion dollar corporations’ served by Cirtas will almost inevitably follow a very different path. Across Pharma, HR, manufacturing, publishing, insurance and finance, Messiana reports that customers with market caps of $500 Million – $10 Billion and more are flocking to the company.

So why take more VC money, so soon, and dilute the company? Messiana insists that “plenty” of the initial $10 Million is still in the bank, and that VCs were falling over one another in their enthusiasm to invest. The deal was apparently closed rapidly, with an aggressive valuation that sees “minimal dilution” whilst giving Messiana the cash to expand sales, support, and other areas of the company.

Cirtas would appear to be off to a good start, but it would be dangerous to be complacent. The company is not alone in seeing hardware as a way to encourage enterprises toward the Cloud, and there are plenty of software-based cloud storage gateways waiting for the opportunity to demonstrate their capabilities as those conservative CIOs become more willing to trust the Cloud. And then there’s Amazon. What might they do next?

Related articles

• Nasuni grabs cloud development cash (go.theregister.com)
• Enterprise Poll: Do You Use Cloud Storage? (readwriteweb.com)
• F5 Friday: F5 ARX Cloud Extender Opens Cloud Storage (devcentral.f5.com)
• The $20 Million Club: 10 Well-Funded Cloud Startups (nytimes.com)

I’ve been a fan of Om Malik‘s boutique analyst site, GigaOM Pro, pretty much from the outset, and happily renew my subscription each year. The site covers a wide range of industry topics, and those Quarterly Wrap-ups are worth the fee all by themselves.

I’ve written a few reports for them in the past, but was delighted when Mike Wolf got in touch to see if I fancied trying my hand at curation on their Infrastructure/Cloud channel.

So next week (from 31 January) I’m going to be gathering and commenting upon links from around the web, writing a daily ‘Today in Infrastructure,’ and finishing off with a Weekly Update. If you’re not (yet!) a subscriber, why not sign up for a free seven day trial and join me for the start of my little adventure?

If there’s something you think I should be covering, do let me know.

Related articles

• Free GigaOM Pro Webinar: The Scalable Cloud (gigaom.com)
• GigaOm raises $2.5M, claims 10,000 Pro subscribers (venturebeat.com)
• The Cloud has a place, even inside heavily regulated industries (cloudofdata.com)
• Talking Scalable Clouds with GigaOM Pro and Limelight Networks (cloudofdata.com)
• GigaOM Structure 2011 (datacenterknowledge.com)
• Join GigaOM at Big Data on March 23 in New York City (gigaom.com)