The company announced a $20 million Series B venture funding on Wednesday, bringing the total raised to more than $26 million. Sequoia Capital led the new round, which also contains a contribution from Greylock Partners.

Along with highlighting problematic use across multiple cloud services, the Skyhigh software also lets IT administrators take steps to minimize impact of the rogue behavior by controlling access to certain clouds and encrypting data, which could make activity more secure. Cisco and Equinix use the Skyhigh product. Skyhigh wants to add more customers and also invest in marketing and engineering with the new funding.

The news falls in line with an increase in investments in security recently. In addition to the Skyhigh investment, Blue Coat Systems has announced plans to acquire Solera Networks, and McAfee said it would buy Stonesoft.

But shadow IT is just one challenge facing CIOs these days, along with the push to try cloud services and implement big data projects. My colleague Barb Darrow will discuss challenges like these with the CIOs of the Clorox Co. and the Pabst Brewing Co. at GigaOM’s Structure conference in San Francisco on June 19.

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An article out Wednesday from Data Center Knowledge envisions the next few steps for automating operations inside the data centers. Robots can move literally higher up the stack than humans and still be safe, which means data center builders can build vertically instead of horizontally. That could bring better use of data center floor space.

If robots do all the work on the floor, lights might become unnecessary, and poof: just like that, a line item can be nixed from the budget. Deploying robots could also lead to less downtime, as they could act with more certainty than people when it comes to replacing a server or another hardware component.

Using robots to grab equipment is “becoming quite feasible,” and Google does it to get backup storage tapes, according to the article. Most gear isn’t really made for machines to handle, though, so this area might be in need of tinkering before it can get widely adopted.

The article also makes mention of unmanned data centers, including one operated by AOL. Apple revealed plans last year to build one of these facilities in Prineville, Ore., before saying it would expand the site to add data centers where some people would work. As more companies move in that direction, prices will drop, leading to further market penetration.

Despite this, the article suggests that data centers will still need administrators, so not everyone working inside data centers will lose their jobs as this wave of automation carries through — for now.

Meanwhile, data center admins can also optimize their facilities by changing out hardware and software to match use cases. Pat Gelsinger, CEO of VMware, will talk about his vision for the software-defined data center, and Andrew Feldman, general manager and corporate vice president of AMD, will talk about how companies can do these things at GigaOM’s Structure Conference in San Francisco on June 19.

With these sorts of upgrades, while the initial capital expenditures might be high, they could bring operating expenses down for public, private and hybrid cloud providers, resulting in price drops for customers in time.

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Terms of the deal were not disclosed.

Among Solera products is a BlackBox Recorder that, true to its name, records all network activity, which analysts can play back after attacks to see what happened. Solera Deepsee software conducts deep-packet inspection to reveal the nature of applications and associated files in play inside a network. It also brings up timelines of suspicious activity, runs analytics and enables integration with other network tools, such as Palo Alto Networks. Dashboards and other visual features are available. Solera also makes appliances that monitor traffic, storage boxes and a virtual appliance available as a VMware virtual machine.

The deal follows news earlier this month of Blue Coat’s acquisition of the SSL product line from Netronome. The thinking behind that deal was to offer enterprises more visibility into both inbound and outbound traffic and apply policy across all traffic, according to a Blue Coat statement.

Also this month, McAfee agreed to pay around $389 million for network-security provider Stonesoft.

In the midst of the attention on cybersecurity among other enterprise IT hot spots, it’s not surprising to see vendors rushing to bolt on products and services and then pinging potential customers to promise the solution to their problems (and then announcing sales gains). The real indicator people should be on the lookout for, though, is a drop in cyberattacks, and judging by some recent headlines, that might still be a ways off.

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The company is pitching the platform for both legacy vSphere applications already running in company data centers  and for brand new applications designed from the ground up.  VMware execs up to and including CEO Pat Gelsinger promised “seamless” interoperability between on-premises implementation and vCloud Hybrid Services.

They promised it will let customers move data from on-premise infrastructure to public clouds on Layer 2 or Layer 3 networks and create the same virtual-networking infrastructure like load balancers and firewalls. Management will happen all inside current VMware software tools. Managing and moving virtual machines will be possible inside vSphere through a free-plugin. The idea is to help customers move existing applications around and develop new applications on the public cloud. Some customers will want to run specified applications on the public cloud and keep key data on premises, said Gelsinger, who will be a featured speaker at GigaOM Structure next month.

Bill Fathers, VMware’s senior vice president and general manager of hybrid cloud services, described vCloud Hybrid Service as the easiest public cloud to adopt. It will be available through current partners, so licensing won’t be different. And customers can get support for the vCloud Hybrid Service from VMware, just as they can for other services.

Partners that endorsed the platform included  Tibco, Microsoft, SAP, Puppet Labs (see disclosure) and Pivotal, VMware’s step-brother that is co-owned by VMware and parent company EMC. VMware  holds a significant stake in Puppet. “VMware will be the first and only cloud provider to provide SAP software, including HANA, as a subscription service on premise and in the cloud,” Fathers said.

The vCloud Hybrid Service actually has two flavors: a Dedicated Cloud mode has “physically isolated and reserved compute resources” for predictable workloads and a Virtual Private Cloud for seasonal workloads that require greater elasticity but are multitenant in nature. The former service will start at 13 cents an hour for a 1 GB virtual machine with a single processor on an annual basis, while the latter will start at 4.5 cents an hour on a monthly basis. But those prices will come as year-long licenses. Fathers said he expects customers to use both in parallel.

To provide the infrastructure for the vCloud Hybrid Service in the United States, VMware will pull from infrastructure in Santa Clara, Calif.; Las Vegas; Dallas; and Sterling, Va. Fathers said the plan is for “an asset-light model” in which the facilities in those cities are “third-party data centers.”

Beta customer, Julio Sobral, senior vice president of post production for Fox Broadcasting, said the movement of certain applications to VMware’s public cloud, particularly collaboration tools for dispersed employees, had, in fact, been “seamless.”

Other beta customers include the state of Michigan, the city of Melrose, Mass.; and Planview. The question is how many of VMware’s roughly 500,000 customers will move onto the service too, rather than keep using IaaS providers such as Amazon (a amzn) Web Services for certain applications, as some customers have.

There could also be friction with existing VMware cloud partners. They have been underwhelmed by the offering and the service provider partners not selected to host the offering now feel they are competing with their supplier, as my colleague Barb Darrow has noted.

Disclosure: Puppet Labs is backed by True Ventures, a venture capital firm that is an investor in the parent company of this blog, Giga Omni Media. Om Malik, founder of Giga Omni Media, is also a venture partner at True.

This story was updated Wednesday with corrected pricing charts from VMware. The company originally posted to its website different pricing models for storage and bandwidth. Additionally, a sentence about the lack of information about storage and network prices was removed.

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Keeping data isolated inside any one database prevents companies from making discoveries across multiple data sets. Plus, he said, at least one database tends to have trouble at any given time.

Earlier this year, Falco started Orchestrate.io to respond to these issues. The company provides a single API through which customers can send data from multiple databases. This way, customers can join, say, geolocation data, time-series data and tweets, drawing graph relationships and doing full-text searches on top of it all.

To build out the infrastructure to do this with multiple cloud providers and bring on customers, Portland, Ore.-based Orchestrate.io is taking on $3 million in seed funding. True Ventures is leading the round (see disclosure) alongside contributions from Frontline Ventures and Resonant Venture Partners.

Some companies were already testing out the Orchestrate.io service, although Falco declined to identify them. He said the price of using the service is tied to the number of queries per second customer make.

When it comes to competition, Falco said, “Certainly there’s Amazon.” On Amazon Web Services, customers can get a slew of tools, from RDS for relational databases to DynamoDB for nonrelational work to Elastic MapReduce for Hadoop. And, of course, if companies don’t buy into the Orchestrate.io logic, existing databases constitute challengers. But Falco has an answer for that. “Databases can do most of these queries,” he said. “The problem is, they can’t do them efficiently and at scale at the same time.”

After the company comes out of private beta, Falco thinks Orchestrate.io has the potential to be a go-to provider for lots of different kinds of data-analysis services, Falco said, just as companies look to Twilio for voice services and SendGrid for email. “(There’s a) shift of operational burden from a corporation or the end user to a service provider,” he said. “I think we’re just part of the trend. You’re going to continue to see that over the next several years.”

Disclosure: Orchestrate.io is backed by True Ventures, a venture capital firm that is an investor in the parent company of GigaOM. Om Malik, founder of GigaOM, is also a venture partner at True.

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Intel Labs is engaged in a research partnership with wethedata.org, a “hub of conversation, news, and events celebrating innovative communities who are each focused on democratizing data in their own way.” Intel also has contributed to a hackathon for building tools consumers can use to understand publicly available data, and it’s sponsoring the National Day of Civic Hacking for getting people across the country to come up with ways to analyze open data sets.

It’s somewhat surprising for Intel to be pushing for data democratization. Intel chips are at the heart of servers THAT companies and government organizations use to crunch heavy loads of consumer data. And Intel also has come out with its own Hadoop distribution for handling big data.

The sort of rhetoric floating around the Wethedata.org site — “we are the customer, but our data are the product. … How do we regain more control over what happens to our data and what is targeted at us as a result?” — seems more likely to come from a nonprofit or even a government agency than from a collaboration that includes a corporation such as Intel. But that might help explain why the efforts are noteworthy.

Intel isn’t the only one active on this front. Andreas Weigend, a former chief scientist at Amazon.com, often raises the topic with executives in his consulting work with big companies around the world, partly because some data is simply wrong, and consumers ought not be penalized for it. And as the MIT Technology Review article notes, legislators have taken stabs at the issue, albeit with little success so far.

Now that Intel is on board, perhaps more tech companies will join in and the prompt the tide to change. And if that happens, interesting questions would arise, such as how exactly companies would roll out more data on its customers, whether companies should give consumers access to algorithms that factor into decision-making and how much visualization software and other tools should be made available.

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GCE customers are now able to do things like establish virtual private Layer 3 networks and assign static public IP addresses to instances, James said. Connecting networks will also become possible. And a load-balancing service is on the way “as part of the native fabric for Google Compute Engine,” James said.

Developers interested in trying out GCE load balancing can fill out a form to do so. Developers can also sign up for early access to all emerging Google Cloud Platform features.

The load balancing and routing services are the sorts of things that could help more businesses make the decision to try real projects on the newly publicly available Infrastructure as a Service (IaaS) piece of the Google Cloud Platform.

And the new capabilities move Google a few steps closer campaign to becoming a top, widely used IaaS provider — if not one day bigger than Amazon Web Services then at least No. 2. That position is already feasible for Google as it is.

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Without a doubt, the panel, at Google I/O, was an apt forum for that question. If any company is innovating in a big way, it’s Google, with recent advancements in voice recognition, wearable technology, quantum computing and other realms. So it wouldn’t be surprising to see some of the Google luminaries’ ideas actually come into being. Here’s what they had to say:

“Speech recognition and vision are showing dramatic improvements over the last few years. We just need to scale them up and make them work better. … They’re (mobile devices) going to vanish into much smaller devices that you carry around and aren’t full-size laptops.” — Jeff Dean

“We’re getting more contextualized. The computer is not what you go to to use. It’s something that’s around you all the time and sort of more integrated into your life, rather than a separate thing.” — Peter Norvig

“I would argue that we’re currently living the singularity, where the tool stops and the mind begins will start becoming blurry.” — Thad Starner

So there you have it, folks — the computer as a smaller and more natural extension of the human brain. Now, let’s set the kitchen timer for 10 years and see what actually happens.

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At a talk at the Google I/O conference on Thursday, Googlers Colt McAnlis (pictured), a developer advocate working on Chrome games and performance, and Grace Kloba, the technical lead on Chrome for Android, gave developers some tips for making better use of the GPU. Doing some of these things can help websites display their graphics as soon as possible and become optimized for “touch events” such as scrolling without sacrificing performance.

Chrome developers can split up many website components into GPU layers, each of which can be subdivided into a bunch of tiles for an entire page — think of a grid overlaid on top of the page. Instead of asking the CPU to upload the pixels to the whole screen area, the GPU caches those tiles inside its memory when a page is accessed and then serves up select tiles in response to user behavior, such as scrolling. This approach “allows the CPU to drink margaritas and essentially chill out while the GPU does all the heavy lifting,” McAnlis said.

But there’s a tradeoff to this layering approach. Making many layers can result in entirely too many tiles, and the GPU “has a static, non-growable memory resource in its texture cache,” McAnlis said. “If the cache is full, you have to push old tiles out of the cache before you put new tiles in.” And that can result in a decrease in performance.

In short, developers have to figure out the right number of layers for each page. For example, if a user ends up not using a tile that is loaded and cached on the GPU, it’s a waste of a GPU compute cycle. Developers can learn more about the use of GPU inside Chrome in the Chromium Project’s design documents and get insight into GPU use with the Trace Event Profiling Tool. Developers can also run experiments through Chrome, McAnlis said.

To demonstrate good use of layers, McAnlis pointed, perhaps unsurprisingly, to a Google site, the mobile version of the Google I/O conference site. “Look at the source code,” he said. “It’s a great example.” The header is its own layer, he said, and it expands and contracts and adjusts the times of conference sessions as the user scrolls up and down the page.

The winners on the web over the next few years will be the sites that can serve rich, compelling content as fast as possible. It looks like Google believes taking full advantage of the GPU might be the best way to accomplish that goal.

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Earlier this year Lockheed Martin shared details of its implementation of a D-Wave Systems quantum computer, which reportedly cost $10 million: The contractor is using the computer to develop new aircraft, radar and space systems.

Now Google is taking steps at incorporating more quantum computing into its operations with the Quantum Artificial Intelligence Lab, which will be located at the NASA Ames Research Center in Moffett Field, Calif. Researchers from the Universities Space Research Association will be able to use the machine 20 percent of the time, Forbes reports. That could lead to lots of interdisciplinary thinking and collaboration.

For Google, though, the goal of the initiative is to make strides in machine learning, according to a Thursday Google Research blog post. The best results could trickle down to end users, perhaps in search results and speech-recognition applications.

Quantum computing could mean smarter smartphones

Google has already assembled machine-learning algorithms that involve quantum elements, Hartmut Neven, a Google director of engineering, explained in the post:

One produces very compact, efficient recognizers — very useful when you’re short on power, as on a mobile device. Another can handle highly polluted training data, where a high percentage of the examples are mislabeled, as they often are in the real world.

It’s not hard to imagine how quantum computing could inform machine learning on a smartphone with just a drop of battery life left. It could be that a smarter smartphone one day will take a minuscule amount of input and determine with a high probability who a user wants to talk to or what information it needs right away, rather than forcing the user to cycle through a string of commands and risking the death of the battery altogether.

The applications might have arisen after Google’s earlier partnership with D-Wave, which came to light in a different blog post from Neven in 2009.

Google has already used machine learning to recognize faces and other things in photos and videos. New technology Google executives talked about at the Google I/O developer conference in San Francisco on Wednesday also appears to use machine learning to stitch together photos and clean them up.

What Google has learned so far is the best results come from blending regular binary computing using ones and zeros with quantum style computing. Quantum computing accommodates the space between a one and a zero with quantum bits of information, or qubits. It can express likelihood as well as take shortcuts by approximating when handling certain kinds of workloads. Given what Google has observed thus far, it could decide to build hardware combining quantum and classical computing capabilities.

For now, though, Google is diving deeper into quantum computing with the D-Wave machine. The move could kick off a sort of arms race for webscale companies to buy quantum computers and come up with new notions by way of probabilistic logic. In this way, Google could help push the development of quantum computing much like its invention of MapReduce changed the way firms do distributed data processing.

In any case, quantum computing has a long way to go before reaching commercial viability. That could take decades (so far it has). But because the organization at the helm of the quantum research is Google and not IBM or Bell Labs, regular people could start seeing much more of the advantages in just a few years’ time, which in turn could drive commercialization.

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