Several of the investors have returned from an earlier $35 million round that the nine-year-old business had raised when it was pursuing a slightly different business, one that also relied on boosting the performance of memory in the data center. Riccardo Badalone, a co-founder and CEO of Diablo, said the company wouldn’t get too specific about its plans, but he did say that it is working on a silicon product that will marry the processor and flash memory to help boost performance. This is yet another evolution in bringing the memory and processing power closer together to speed up applications. Fusion-io does this, only its business was built on putting the memory on the PCI express card.

Badalone says he can bring it closer. That would help get more data to the processor and in turn let the processor take on more information. And in today’s web-based business or cloud environments, the more your processors run, the more money you make. That sentiment is why flash memory and ways to increase its performance are rapidly gaining interest –and why Fusion-io has done so well.

Diablo is borrowing a tactic from Fusion-io in that it is working with equipment makers to put its technology — called Memory Channel Storage — inside servers. Its previous product was qualified on Dell, HP and IBM systems, which is one reason that investors ponied up for the latest round even as Diablo was switching strategies. Badalone anticipates using similar partnerships with its chip technology, although he declined to name any of those potential partners or existing customers.

The company has 40 employees and plans to grow to 50 or 60 in the coming year, and Badalone is optimistic about the performance of the systems when it eventually hits the market in 2013. “We will be the first company in the world to marry RAM and Flash in the memory subsystem and once you do that the performance of the I/O will be such that people will lok at the numbers, and frankly, they will not believe it,” Badalone said.

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Parnafes, who is based in Israel, was previously a partner who led Battery’s investment in Delphix, a company that makes software to virtualize databases. Parnafes was also on the board of XtremIO prior to its acquisition by EMC. “The guys keep asking me if our investment in enterprise IT is done yet, but there’s still a lot of opportunity here,” says Parnafes.

Itzik Parnafes

Battery has been one of the more active venture firms investing in the hardware and infrastructure side of our broadband-influenced and consumer web-obsessed culture with investments in Calxeda, the ARM-server company, Anobit, the flash memory firm that Apple purchased, and Cumulus Networks, a company rethinking switches. It has made more than 20 investments over the past five years in enterprise IT, and put more than $240 million in.

What’s going on in enterprise IT–or, frankly, IT.

For every Facebook and Pinterest there are hordes of servers and IT personnel trying to figure out how to scale these web-based businesses at costs that still enable them to make money. On the web, your infrastructure and software are the raw materials that comprise your cost of goods sold, so many of these firms are looking to make their infrastructure cheap and elastic.

Some buy from cloud providers like Amazon, while others graduate to hosting their own servers and building their own data centers. But this trend hasn’t exactly been a boon for the legacy IT guys as open-source software and commodity hardware have been deployed across hundreds of thousands of feet of raised floor inside data centers. Scale breaks things, and in the last five years venture firms have been investing in software and hardware that helps bridge the gap between legacy and a new hyperscale architecture.

But as Parnafes says, there is still opportunity, and that opportunity is in rethinking the architecture itself. Google is doing it with a team of secretive scientists, as are some in the cloud and high performance computing world. Once you build a compute architecture that’s elastic and on-demand, the physical infrastructure constraints — which remains inelastic and isn’t deployed on demand — become a source of pain.

Peace, love and interoperability in next-gen IT

It’s like once you move to a house in the suburbs you realize that you love the lawn and schools, but you hate the commute. Computing and data centers are now realizing the time they spend provisioning and futzing with the hardware is their equivalent of a long commute. Hence the current vogue for software-defined everything, the rise of Mellanox, which can support both Infiniband and Ethernet networks, and even the purchase of Xsigo by Orcale. The end goal here is a compute architecture that can be just as adaptive as the virtualized services built on top of them. What’s more, workloads and data will be able to flow from one data center (or cloud) to another seamlessly.

“These are the prime motives that direct our thinking: what will be in the next generation data center,” Parnafes says.”Look at every constraint you encounter today and try to eliminate them, and if you identify such a technology you have a possible winner on your side.”

Parnafes acknowledges that we may never get to this boundary-less world, but he suggests that regulations as opposed to technology or business models will be what stands in the way. To bolster this idea, he points to the CIOs of large banks which have seen the cost efficiencies of running an Amazon-style compute cloud and are trying to emulate Amazon’s costs structure and elasticity as opposed to buying into some vendor-defined private cloud model.

“It’s kind of an ironic twist,” Parnafes said. “In the past the public clouds wanted to emulate the private data centers to make people feel comfortable and now the private ones want to emulate the public clouds which have very efficient model for people to run their [compute] jobs.” So as these worlds not only collide, but are coming together in some sort of software-defined and virtualized lovechild, startups that can help ease that transition should give Parnafes a call.

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That’s a lot of money for a storage startup, especially one that’s pursuing the appliance model in an era of build-it-yourself- commodity hardware, but investors are so confident the round was “massively oversubscribed,” and the valuation led the U.S. Securities and Exchange Commission to hold up the financing while it investigated the round, confirmed Nutanix President and CEO Dheeraj Pandey.

So what has investors so excited? Nutanix’s appliance allows companies to do two things that are important to companies on the leading edge of the scale out and virtualization shift: it allows companies to eliminate separate storage networks by virtualizing them and allows companies to move their storage closer to their compute power, which speeds up a company’s applications or response times. As my colleague Derrick Harris wrote in April of 2011 when Nutanix launched:

The key to Nutanix is virtualization, which provides the abstraction and the additional storage connections necessary to give Nutanix the performance edge it claims. The company is big on solid-state drives for performance and consolidation, but Pandey says legacy storage systems are limited to the amount of SSDs they can handle. With a virtualized computing layer, however, each virtual server and each physical node provide the requisite housing and connection to an additional SSD. The Nutanix appliance combines both SSDs and hard disk drives to achieve maximum levels of performance and affordability, Pandey said.

Nutanix has proved that customers want its appliances, noting that it has shipped 150 systems, including 600 servers attached with more than 3.3 PBs of spindle and Fusion-io storage. The additional money gives it the wherewithal to continue selling its product to more and more companies, likely with the aim for going public in the not-too-distant future.

“This round takes us to $50 million-plus in the bank, and that means we can build a company of lasting value,” said Pandey. “That’s why Goldman is involved.” Of course, when I asked Pandey about the timing of the IPO he declined to speculate.

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SolarBridge raises $25 million, series D: SolarBridge makes solar microinverters, which are miniature versions of conventional central solar inverters that are necessary for converting the direct current generated by solar panels to alternating current for feeding the grid or to be used onsite. Instead of matching a central inverter to a dozen panels at a time, each microinverter serves one panel. This design allows the microinverters to calculate and adjust the optimal energy output of each solar panel and prevents poor-performing panels from affecting the power output of the best-performing ones.

SolarBridge raised $25 million in a series D round led by Shea Ventures and including Battery Ventures, Rho Ventures and Osage University Partners. The company has raised more than $71 million to date, including a $19 million series C round last year. SolarBridge says the funding will be used to launch “new hardware and software products, increase sales and marketing efforts and expand the company’s operations globally.”

Solar microinverters are the future of solar inverters, but are still at an early market phase. Enphase Energy is another leader in the microinverter space and Enphase went public earlier this year.

Redwood Systems raises $11.75 million, series C: Redwood Systems makes a control and sensor system for LEDs that runs over an optimized version of Ethernet cables. The company just closed $11.75 million in a series C round from investors including Battery Ventures, U.S. Venture Partners, Index Ventures and Mitsui & Co, Ltd. Japanese conglomerate Mitsui started backing the company a year ago.

Redwood Systems is four years old and some of its customers include SAP, Volkswagen, Johnson Controls and most recently, Facebook. Commercial building owners and data center operators can use Redwood’s LED system to cut the amount of lighting used throughout the building — in some cases, up to 70 percent over standard non-networked fluorescent lighting systems. LEDs are more efficient than fluorescents, but Redwood’s management system also monitors the building environment, including temperature and room occupancy, and can dim and manage the lights to help maximize efficiency.

Lighting Science Group raises $140 million: LED maker Lighting Science Group has closed on $140 million in private funding, led by private equity firm Riverwood Capital, and including Pegasus Capital Advisors. Lighting Science Group is already publicly traded on the OTC bulletin board, and over a year ago indicated that it wanted to go public on the Nasdaq and raise $150 million.

Lighting Science designs and makes LED lamps and other light fixtures for the residential, commercial and industrial market. The company has been selling LED lighting for nearly a decade and owns factories in Satellite Beach, Florida and Monterrey, Mexico.

GreenBytes raises $12 million, series B: GreenBytes makes data de-duplication storage gear, which are tools that reduce redundant data as well as store data on energy efficient storage solid state drives. The company raised a $12 million series B round from Battery Ventures and Al Gore’s Generation Investment Management.

“Primary storage”, or top tier storage, is comprised of hardware designed for quick data access and are usually reserved for active or just-created data.  Beneath this are “secondary tiers” devoted to backup storage, archives and storage of lower priority business data. GreenBytes’ appliances are deployed close to the top tiers of storage so that fewer data trickles down to other tiers and the greater the potential cost and energy savings overall. Despite the promise of data deduplification, IT managers are still wary about it, according a GigaOM Pro report “De-Duplicating the Storage Industry” (subscription required).

Solar Mosaic raises $2.5 million: According to a filing, the kickstarter of solar, SolarMosaic has raised $2.5 million. The company is just about to launch the truly disruptive part of its business: as early as this Summer SolarMosaic plans to start offering people a way to buy into rooftop solar panel projects, and make back a return on their investment over time.

Soladigm raises close to $5 million in debt, option: Soladigm, which makes electrochromic “smart” windows that tint when electricity is applied to them, has raised $5 million in debt and options according to a filing. The startup was founded in 2007 and is based in Milpitas, Calif.

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New investor Crosslink Capital led this E Series round, joining previous backers Battery Ventures, BlueRun Ventures, El Dorado Ventures and Mohr Davidow Ventures. The cash influx brings total venture funding to $41. 5 million to date for the six-year old company.

Coupa, based in San Mateo, Calif. competes with companies like Ariba which started out in on-premises software but is adding more cloud services.

Business customers use these e-procurement services to track contracts, purchases and suppliers. In a statement, Coupa CEO Rob Bernshteyn said the company has closed 13 consecutive quarters of growth and has 200 customers in 40 countries.

In e-procurement — as in other vertical application areas — traditional software vendors like IBM, SAP and Oracle are building (or buying) cloud-based services to compete with pure play cloud players like Couda. Other e-procurement competitors include JDA, BravoSolution, and Emptoris, which IBM bought in December.

Photo courtesy of Flickr user Images_of_Mone

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The challenges in IaaS are pretty clear: it’s expensive to buy and operate the necessary gear, it’s difficult to build a differentiated platform and, perhaps most importantly, there’s the little challenge of standing out against IaaS heavyweights. AWS, Rackspace, Terremark,  and VMware. These are not small companies, and AWS, in particular, maintains a commanding lead in market share and mindshare.

But according to Dave Tabors, a partner at Battery and now member of the SingleHop board, IaaS “is as much an execution game as it is a technology,” and SingleHop has been executing. (Not that SingleHop’s technology is bad. It actually resembles SoftLayer — another up-and-coming IaaS provider that’s making a name for itself with some big-name customers — because of its single, automated platform that delivers both dedicated and cloud servers.) Tabors told me Battery spent the better part of four years researching the IaaS space before deciding that SingleHop presented the best investment opportunity around.

SingleHop now manages 10,000 servers across two Chicago data centers, with a third to come in Phoenix. Inc. Magazine named SingleHop the No. 25 fastest-growing U.S. company in 2011. And, most importantly, it’s making customers happy thanks to features such as its Customer Bill of Rights. With Battery’s backing, Tabors thinks SingleHop can scale its business to the next level.

It’s worth watching to see whether other VCs also still have an appetite for IaaS, and where they’ll decide to invest if they do. Thought leaders Joyent and Virtustream have raised piles of money in the past couple years (to the tune of $107 million and $50.4 $75 million, respectively), but IaaS investment has otherwise been rather slow. Promising startups are difficult to come by, and some more-established privately held providers might not be seeking venture financing.

Maybe the topic will come up during the VC panel at our Structure conference in June, during which leading investors will talk about what has them excited in the cloud. The cloud keeps evolving, but its IaaS foundation will always be important. The question is how much opportunity investors see to get a piece of IaaS providers that can actually deliver a big return.

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Bergman says he first realized that he had a business model when he was CTO at Wikia, which provides wikis. The site was seeing its load times slow, and it wanted to improve them, so it shopped around to major CDNs to see if anyone could help. The challenge was that Wikia needed pages to load almost instantly, as opposed to every few minutes or a few times an hour. When the season finale of True Blood  is occurring, users want their Wiki edits to update now.

But Bergman couldn’t find a provider that was as dynamic as he needed. So, he decided to build it himself. He had previously boosted Wikia’s page times in the U.K. by bringing in two servers and popping them into a rack at a data center in London. That made pages load a little more than five times faster. So, he decided to do the same thing in five other data centers and create his own business.

The company raised less than $2 million (he wouldn’t disclose specifics) in funding earlier this year from Battery Ventures and O’Reilly AlphaTech Ventures, and Bergman launched the service in July. It now carries more than a billion HTTP requests a day for customers that include Instructables and Y Combinator startup Imgix, which bills itself as a CDN for images. But the big disruption here is economic. Bergman can create his CDN using dozens of machines that cost about $10,000. Compared to Akamai, which has tens of thousands of servers in thousands of locations, Fastly is both smaller in scale and in terms of the cost it takes to build out the service.

But Bergman believes his way is as fast as, if not faster than, traditional CDNs for hosting dynamic web content as well as being more transparent to the site owner. Bergman was careful to make a distinction between delivering short video clips such as YouTube content and HD-quality iTunes or Netflix streams, but he’s confident his CDN could deliver performance improvements for the former market and just hasn’t modeled out the latter. CDNs are almost a dime a dozen nowadays, with several services from established players and newer services such as Amazon’s CloudFront and offerings from ISPs to contend with. Fastly’s all-SSD effort is certainly unique though.

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The current mantra in Web operations is to track, record and monitor everything. Data is valuable and storage is cheap, so this makes sense. Metrics that measure the right thing are incredibly important in the context of getting the best performance from your application. To that end there were some amazing talks on monitoring, metrics, lies, damn lies, and statistics, at the year’s Velocity Conference. Two of my favorite talks were from John Rauser at Amazon and Kellan Elliot-McCrea from Etsy.

However, I want to propose a new metric: Mean Time to Pretty Chart (MTPC). For full buzzword compliance, let’s say that WebOps + BigData + Information/Graphic Design = MTPC. If you’re not familiar with acronyms like “MTTR” and “MTBF,” metrics abbreviated with MT, meaning “Mean Time,” are common throughout operations-centric businesses of all kinds. MTTR (Mean Time To Recover) and MTBF (Mean Time Between Failure) are two of the most frequently used.

MTPC attempts to quantify the amount of time required to determine the root cause of an operational issue and depict it in an eye-catching way. The MTPC metric is challenging because it encompasses a number of challenges spanning large volumes of data acquisition, storage, correlation and design/representation.

The metric also has a corollary as a business metric for companies selling performance monitoring products. From the time your product is downloaded, your MTPC should be as short as possible. We have seen many companies over the years that could do incredible analysis but were too intrusive to install to get broadly deployed. In cases like this, the MTPC was too high and the business suffered as a result. Today’s trend is for downloadable free trials, and easy to install products focused on keeping MTPC as short as possible.

What is often overlooked by people who don’t operate large scale websites for a living is just how many layers of the stack underlie a modern website that someone needs to monitor. Let’s look at a very complex example. The chart below, courtesy of Adrian Cockcroft at Netflix, depicts the layers of the stack the streaming site monitors and the numerous data sources it ingests.

The Netflix stack is based on Java and runs on AWS, so applications developed in other languages, such as Ruby, PHP, Python, will use different tools for the application layers. The chart above is not meant to be an exhaustive list of the monitoring tools and techniques, nor a comment on the merits of open source tools vs. commercial products. WebOps pros often use a number of both types of products to do their jobs. A highly incomplete list of relevant commercial and open source tools would include Ganglia, Nagios, Cati, Graphite, Munin, Splunk, New Relic, Tracelytics (see disclosure), DataDog (see disclosure), and AppDynamics.

The visualization challenge associated with displaying such large amounts of information about so many physical and virtual entities is potentially more challenging than collecting and storing the data. Numerous options exist for visualizations: simple time series graphs, stack charts, heat maps, and more complex choices, like 3D, which leverage the graphics horsepower in modern GPUs. Let your Minority Report UI fantasies run wild.

However, the state of the art in WebOps visualizations appears to have reached a plateau with RRDTool graphs and Skitch.app annotations. We haven’t made much progress in the past few years. This important capability is basically relegated to a “Lolcat macro.” Don’t believe me? Check out WebObsViz on Flickr and see for yourself.

One of the most powerful graphic representations is to look at data from multiple layers in the stack co-mingled in a coherent fashion. A simple example could be CPU and memory utilization overlaid with the timing of pushing new code into production. Looking at data across layers can be very powerful because it allows one to see how changes at one layer in the stack ripple through the infrastructure. Some leading edge organizations are dumping machine data into packages like SAS, SPSS, and R to do correlations and other more advanced statistical analysis. Enter the Data Scientist. While correlation doesn’t imply causation, with large enough sample sizes the old adage “where there is smoke there is usually fire” often applies. When you can visualize that smoke in a pretty chart, it’s easier to pinpoint the fire.

Further design complexity also stems from having to provide different views into data for different constituencies within an organization. Developers may want to see a certain view into application errors or how multiple services in their distributed system interact with each other. Operations may want lower level machine data, network statistics, or performance metrics from a cloud provider.

Visualizing operations information is further complicated by the challenge of finding an Edward Tufte disciple who can do information design, user interface, and code a bit. The technically competent designer is also one of the hardest spots to fill in our portfolio companies these days. Many companies I speak to have given up searching for this unicorn and have broken out the design and front-end implementation into multiple roles.

The future may be brighter in this regard as the next generation of art and design graduates are digital natives. The work of RISD President John Maeda sits at the nexus of graphic design, computer science, and the fine arts. His disciples, including Ben Fry, Casey Reas, and RISD alum Nicholas Felton, are pioneering new ways to make sense of large sets of data. Not surprisingly Stanford is also on the cutting edge from the computer science perspective with Pat Hanrahan’s Visualization Group leading the way.

Alex Benik is a principal at Battery Ventures. Battery Ventures is an investor in DataDog and Tracelytics.

Image courtesy of Flickr user jspaw.

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FirstFuel Software is able to use its analytics and a set of data to remotely determine energy information about a commercial building, like consumption habits, and give recommendations for how to make it run more energy efficiently. The company says it uses no onsite hardware or onsite energy audits, to get this data, and yet says its information is as accurate as information received through an onsite energy audit, which is far more costly. The data sets needed to produce an accurate set of energy information includes, utility-based electric and gas data for a year, the location’s weather and climate data, as well as GIS mapped building data.

If you don’t believe in the accuracy of the remote assessment, the company had its analytics tested by the Fraunhofer Center for Sustainable Energy Systems via a Department of Energy grant. FirstFuel Software says the study found that its software “has the potential to be a valuable engine for the large scale benchmarking of buildings and to identify energy-saving opportunities without on-site audits.”

The major customer for this tool is utilities, which want a cheaper and quicker way to determine the energy information about commercial customers. Using the information, utilities can give both operational recommendations and retrofit recommendations that can lead to energy savings, and can continue monitoring consumption data remotely.

Other startups are turning to big data to solve problems with energy, like EcoFactor, Opower, Geostellar, SAP and Hara.

Images courtesy of FirstFuel Software.

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