Posts Tagged ‘google’


Why Microsoft will beat Google in the enterprise cloud war

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Google beat Microsoft to market with its cloud-based suite of business apps, but the tables have turned and many organizations, particularly large enterprises, are now looking to Microsoft for their cloud needs.

As Google and Microsoft battle for enterprise cloud customers, each company’s natural strengths (and weaknesses) become more apparent. Microsoft, for example, is winning over large enterprises that already have massive workforces on Office 365. Google for Work, meanwhile, continues to be popular among small-to-midsize businesses (SMBs), particularly organizations that don’t have dedicated IT staffs and aren’t burdened by legacy technologies that require ongoing support.

The pendulum started to slowly swing back in Microsoft’s favor after it released Office 365 in 2013 and finally embraced the cloud, according to TJ Keitt, a senior analyst with Forrester Research. It is difficult to accurately compare the two companies’ user numbers because neither Microsoft nor Google provide details on user bases, or the sizes of the companies they serve, but Keitt suggests Microsoft is on the winning end of the recent shift.

“There is momentum associated with Microsoft Office 365,” he says. “And that was probably always going to be the case, because there are some fundamental differences between Google Apps for Work and Office 365.”

Microsoft Office 365 gives IT more options and controls
It’s easier to get started with Google’s tools, for example, but Microsoft provides greater flexibility and support for critical IT deployment needs, according to Keitt. Office 365 customers have more options when it comes to licensing for apps and data that will be hosted by Microsoft partners; access to the platform in a shared environment; and using dedicated Office 365 environments. “Google doesn’t provide that deployment flexibility,” Keitt says, and adds that Google for Work only supports multi-tenancy deployments.

Vanessa Thompson, research vice president at IDC ( and IDC are both owned by IDG Communications), says both platforms are gaining momentum. “As the level of comfort for cloud-based solutions in general increases, there will be uplift across both solutions.”

Office 365 offers many more IT-specific plans than the two options available in Google for Work, Thompson says. “It is all up to customer choice. Some companies might be happier to mix and match functionality and licenses, and would go with Microsoft, but others are looking for a more straightforward transaction and would go with Google for Work.”

Microsoft provides a pathway for businesses with SharePoint deployments, for example, to continue using those services while moving other elements of their Microsoft portfolios to the cloud, Keitt says. Conversely, Google presents some “stumbling blocks for companies that aren’t interested in ripping or replacing what they were using previously,” he says.

These “different on-ramps” for large companies that already use Microsoft products represent opportunities for the software giant, according to Keitt.

Microsoft’s strengths are particularly appealing to Forbes Global 2000 companies, according to Keitt. “That’s usually where you start to see a break in interests between Google and Microsoft,” he says. “Those very big companies are interested in Microsoft more than Google because of deployment flexibility, as well as hybridization capabilities.”

Thompson says Keitt’s conclusions align with her research and suggests Microsoft’s approach is twofold, because it caters to companies that want to transition to Office 365 for email, as well as organizations looking to mobilize existing desktop apps that they want to continue use.

Google, however, targets companies looking to move completely to the cloud, according to Thompson. Google provides offline access to some of its products, but it can’t match the functionality and IT control enabled by Microsoft.

Despite Google’s earlier entry in the enterprise cloud market, it simply can’t compete with Microsoft in a number of areas, according to Keitt. Google’s technology was developed for use by consumers and then repackaged for business with a set of administrative consoles and IT controls, he says. Google also offers no enterprise equivalent to SharePoint, Yammer or machine learning. So “[i]t’s not an apples-to-apples comparison across the board.”

Last month Google said more than 2 million businesses pay to use Google for Work, and that suggests Google is still has more total customers, according to Keitt. But Microsoft owns the majority share of big business. “There is a fierce competition in smaller companies between Microsoft and Google,” Keitt says. “I would say that Microsoft probably has a pretty good lead in larger companies around Office 365.”
Google won’t go out without a fight

Google is running promotions to steal away enterprise customers from its competitors. The company kicked off an initiative last month that lets businesses under other providers’ contracts use Google for Work apps at no cost for the remainder of those license agreements. The move is part of a smart competitive strategy that could pay off in the SMBs market, according to both Keitt and Thompson. However, for most businesses, the choice between Google and Microsoft comes down to specific employee needs, as well as how frequently their employees use Microsoft Office.

“If your organizational policy is flexible enough to allow users to pick up standalone apps alongside suites then this might appease users and let them have more choice in the applications they use to get their work done,” Thompson says.


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Google removes ‘porn clicker’ malware from its Play Store

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The fake apps visit porn sites in order to click on ads

Google has removed dozens of apps from its Play Store that purport to be games but secretly click on advertisements on pornographic websites.

Security company Eset found 51 new apps that contained the “porn clicker” component, which it first discovered in April in a fake app mimicking a video app called Dubsmash.

Over the last three months, some 60 fake apps have been downloaded 210,000 times, showing how common it is for users to stumble across and download them.

“Following ESET’s notification, Google has pulled the malware from the Play Store and also reports some of them as potentially harmful applications using its built-in security service,” wrote Lukas Stefanko, an Eset malware researcher.

The bogus apps do not try to steal authentication credentials. If downloaded, the application presents itself as game or system application. It runs in the background and accesses porn websites and clicks on ads. The app could eat up data allowances on a person’s mobile phone account.

Google scans apps uploaded to its Play Store using technology called Bouncer. The automated scan checks an app for five minutes, performing a dynamic analysis of its code, according to Trend Micro. But apps that do not misbehave in that time period may not be caught.

Although Google can catch malicious apps, malware authors have become more clever in finding ways to avoid Bouncer, which has apparently happened with the porn clicker applications.

This time around, bogus versions of Dubsmash were uploaded again along with fake versions of other legitimate apps including Pou 2, Clash of Clans 2, Subway Surfers 2, Subway Surfers 3, Minecraft 3, Flappy Birds and Hay Day 2. The harmful apps were available for almost a week.

Since it’s hard for users to see if an app is malicious, Eset recommended that people pay close attention to the reviews of apps, which may provide a clue if a particular app is suspicious.

“Hopefully, Google is doing its best to fix this issue and find a way to prevent the developers of these porn clickers from publishing them to the Play Store,” Eset wrote.

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Google opens up on its SDN

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For first time, hyperwebscale company details its data center network, offers it to developers

At this week’s Open Network Summit, Google spoke for the first time publicly about its custom data center network. For nearly a decade, we’ve been hearing, reading and writing about how Google was building its own switches and writing its own software to handle the tremendous traffic load on its search engine and applications because vendor offerings were either not up to the task, too expensive, or both.

This week we found out how they did it. In a keynote presentation at ONS, Amin Vahdat, Google Fellow and Technical Lead for Networking, described the company’s data center network architecture, capabilities and capacity for a rapt audience thirsting for information on software-defined networking implementations and experiences.

Vahdat summarized his talk here and offered use of the architecture to external developers through the Google Cloud Platform.

To summarize Vahdat’s summary:
The network is arranged around a Clos topology where a collection of small, cheap switches are grouped into a much larger logical switch.
Google uses an internally written centralized software control stack to manage thousands of switches within the data center and treat them as one large fabric.
The company’s current generation Jupiter fabrics are designed to deliver more than 1 Petabit-per-second of total bisection bandwidth, enough for 100,000 servers to exchange information at 10Gbps each, or enough to read the entire scanned contents of the Library of Congress in less than 1/10th of a second.

Over the past decade, Google has increased the capacity of a single data center network more than 100x.
And in building its own software and hardware, Google relies less on standard Internet protocols and more on custom protocols tailored to its data centers, and perhaps others.

Our network control stack has more in common with Google’s distributed computing architectures than traditional router-centric Internet protocols.

Perhaps vendors snubbed by Google these past 10 years can learn something about data center network product development from the hyperwebscale company. The key impetus might be how attractive the architecture is to external developers.

But then, is it the Google data center network architecture that attracts them? Or is it Google itself…

In any event, Google’s been using and benefitting from (its own) SDN for the past 10 years, Vahdat states. Just like Microsoft has been using and benefitting from (its own) SDN for five years.

The degree to which the industry can benefit from their experience may hinge on how much Google and Microsoft share with the industry not only their experiences, but actual code, through open source and other means. Cloud operators and enterprise users are being pressed at ONS this week to not only use open source for their SDNs, but contribute to the open source SDN community as well.

But as Microsoft Azure CTO Mark Russinovich said at ONS this week, that decision is not an easy one – it comes down to determining what the cost and benefit is to the contributor, the benefit to the community, and what constitutes “secret sauce” intellectual property vs. shareable development.

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Google for Work vs. Microsoft Office 365: A comparison of cloud tools

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While Google for Work and Microsoft Office 365 offer many similar services, choosing between the two can be a significant challenge for CIOs. This comparison eases that burden.

CIOs and IT managers have many choices when it comes to cloud-based productivity tools for email, documents, calendar and file-sharing. The first two options that come to mind for most, however, are Google Apps for Work and Office 365.

The former packs all the familiarities of the Google Apps suite, including Gmail, Hangouts, Drive and Calendar, while the latter comes with the longer legacy of tried-and-true Microsoft Office apps, such as Word, Excel, Outlook and PowerPoint. The two options have unique strengths and weaknesses, and each is best-suited for specific types of businesses and users.
Google for Work vs. Microsoft Office 365: Price, simplicity and storage

Both services start at $5 per month. Microsoft requires a full-year commitment, which costs at least $60 per year, while Google’s suite is available on a month-to-month basis. Google also offers a yearly discounted plan for $50 a year, plus tax.

Every Office 365 user gets at least 1TB of cloud storage, while Google’s entry-level plan provides considerably less space: 300MB of online storage per user. However, Google provides unlimited storage for accounts with at least five users on its $10 per month or $120 per year (plus tax) plans.

Google also gets high marks for simplicity, because it offers two relatively straightforward plans.
Microsoft makes things a bit more confusing with six total packages — three for small and medium-size businesses and three for large enterprises — that range in price from $5 to $20 per month, with a yearly commitment.

Pricing is an important determining factor, but equally important for CIOs are the feature sets, security safeguards and user experiences of both platforms. The ideal cloud-based platform is secure, stable and simple for employees to learn and use. Cost is just one of the many concerns IT managers must consider when investing in cloud-based productivity platforms.

Eric Schlissel, CEO of IT consultancy GeekTek IT Services, says his company uses Google for Work, but more often than not he recommends Office 365 to clients because they are already heavily dependent and invested in Microsoft Outlook. Many business owners are reluctant to change the way their offices work, according to Schlissel.

“We tend to recommend Google for Work to clients with a younger and more tech-savvy workforce,” Schlissel says. “CIOs should look at how their employees use technology and work outwards from there.”

Where Google for Work falls short
At Creative Solutions in Healthcare, a company that owns and operates assisted-living facilities, the IT department uses Google for Work while the rest of the company relies on Office 365, according to CIO Shawn Wiora.

“In many ways, Google for Work is a low-cost equivalent of Office 365, and it’s a great fit for startups and small businesses that need to limit costs while achieving ‘good enough’ status,” Wiora says. “However, the cost savings come with a number of nuances that limit its fit for enterprise customers.”

Wiora says there are at least four problems with Google for Work that can add up to a major burden for businesses. He cites “shared calendar issues, an inability to transfer Excel formulas directly into Google Spreadsheets, compatibility issues and vertical-specific decisions like Google’s past refusal to sign a HIPAA BAA [Health Insurance Portability and Accountability Act Business Associate] agreement for the healthcare industry.”

In Wiora’s his experience, Google’s suite keeps up with Office 365 about 90 percent of the time. It’s that other 10 percent that “makes Google for Work a poor substitute for medium and large enterprises that expect to simply pick up in Google where they leave off with Microsoft.”

BetterCloud, a company that provides security and management services for Google Apps and Office 365, also uses both Google and Microsoft’s offers, according to Tim Burke, BetterCloud’s IT director.

The company primarily uses Google for Work as the sole platform for its corporate calendar and conference room reservation system, but it also provides Office 365 accounts to users who work on its Microsoft-related products.

“We’ve looked into many solutions for coexistence between the two platforms (especially for calendar and contacts), but there’s nothing mature yet that allows Google Apps and Office 365 to ‘play together’ well on a single domain,” Burke says.

Both platforms are enterprise class, with almost identical offerings, according to Burke, who says Google’s suite is becoming more “enterprise” every day.

“Many people don’t realize [Google has] been in this market for over six years at this point, and Google Apps is used by some of the largest organizations in the world,” Burke says. Google’s strengths also include a deeply integrated infrastructure and a simple licensing structure, he says.

Office 365 provides a continuity with legacy solutions that makes it easier to keep everyone happy with the applications they’ve been using for many years, or perhaps decades, but it’s also evolving. “Office 365 is based on Microsoft’s legacy products and is becoming more ‘cloud-enabled’ and easy to manage,” Burke says.

Google for Work vs. Microsoft Office 365: One size does NOT fit all
Many others familiar with Office 365 and Google for Work take a much less neutral stance than Wiora and Burke; both companies have dedicated users and evangelists.

Martin Milanov, a digital marketing specialist at Fair Point, a corporate travel management firm based in Germany, writes that he “will scream to the ends of hell if they take away my Excel and make me use the, let’s face it, subpar Excel wannabe that is Google Sheets.”

Kristin Bassett, corporate marketing manager at AppNeta, an application performance management provider, says her company recently switched from Microsoft to Google to get all employees on the same email system. The firm chose to migrate its entire staff to Google for Work because it preferred Gmail to Outlook and considered email its highest-priority tool.

Many of the engineers working for AppNeta had requested corporate access to Gmail, according to Bassett, and the switch improved the company’s ability to hire and retain engineers, who are core to its business.

Regardless of platform, it’s about preparation

Both Burke and Wiora encourage CIOs to gain a deep understanding of their users’ needs and company goals before deciding on Google for Work or Office 365.

“We’ve worked with thousands of customers across both platforms, and the most successful deployments involved a highly democratic approach where they set up small pilot groups, talked to managers in different departments, discussed pros and cons for both platforms, and generally took the time to make sure they were making the best decision for their users and not for their IT department or existing infrastructure,” says Burke.

For some CIOs, a hybrid approach will work best, according to Wiora. However, using both platforms can also lead to more work and potential problems for IT. “Each new service increases complexity for end users exponentially rather than linearly, so reducing confusion from having information in so many places will be critical for anyone using a hybrid approach,” says Wiora.

Above all, CIOs shouldn’t delay the necessary research and piloting, and they should try to make a decision as quickly as possible, according to Burke. “Whether your organization chooses Google Apps or Office 365, you’re getting a cloud office platform that’s going to fundamentally change the way your business operates if it’s correctly implemented and thoroughly adopted,” he says.

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Lenovo N20p Chromebook review: An affordable dual-mode device

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Lenovo’s latest Chromebook functions as both a regular laptop and a stand-supported tablet. But what is it like to use in the real world?

When you think of a Chromebook, you typically think of a keyboard-centric laptop — but Lenovo’s hoping to shake up that mindset with some versatile new devices.

The company has come out with a couple of convertible Chromebooks that can act as both traditional laptops and touchscreen tablets. The first, the Lenovo N20p Chromebook, costs $330 and offers a 300-degree tilting display. The second, the ThinkPad Yoga 11e Chromebook, costs $479 and features a higher-quality screen that bends back a full 360 degrees.

I’ve been living with the N20p model to start with, and one thing’s for sure: It offers a Chrome OS experience like no other.
Body, design and that tilting display

At first glance, Lenovo’s N20p Chromebook looks like any run-of-the-mill laptop: The computer has a matte-plastic gray casing with Lenovo’s logo and the Google Chrome logo at its top. Open the lid and you’re greeted by an 11.6-in. screen and a chiclet-style Chrome OS keyboard.

In that mode, the N20p Chromebook is pleasant enough to use: It’s one of the higher-quality devices in its class, with sturdy construction, a commendable keyboard and a smooth-feeling and responsive trackpad. If you press on the center of the lid, you do feel a little give — almost a slight springiness — but by and large, the N20p seems well-built and less flimsy than some of the cheaper options in its price range.

The N20p is comfortable to hold on your lap, too: The laptop is 11.6 x 8.3 x 0.7 in. and 2.9 lbs. — slightly heavier than some of the less sturdy devices of its size but still quite light and easy to carry.

As with other touch-enabled Chromebooks, you have the ability to tap, scroll or zoom the N20p’s screen with your fingers, which I find to be a surprisingly useful feature. It’s even more interesting, though, when you push the N20p’s display back beyond the standard stopping point — past the flattened-out 180-degree mark and all the way around to its fully tilted stand mode.

In that mode, you actually end up with the keyboard upside-down — in other words, with keys facing downward — serving as a base. The keyboard is automatically disabled in that state, so you don’t have to worry about accidental key presses. Instead, what you get is a tablet-like experience, complete with a virtual on-screen keyboard that appears when you need it.

Coupled with the N20p’s touch input, this setup works incredibly well. It opens up a whole new range of uses for the device while still leaving its traditional operations in place.

I’ve been using the N20p Chromebook in its laptop mode for work, for instance, then flipping the screen around and shifting into stand mode when I want to do something less input-oriented and more browsing-based — catching up on articles I’ve opened throughout the day, scrolling through my social media streams or watching videos with the device resting comfortably on my lap.

It’s reached the point where shifting between the system’s two modes feels effortless and natural to me, and I’ve really grown to appreciate having that option. Chrome OS itself isn’t entirely optimized for touch, so certain things are still a little awkward — like trying to tap the small “x” to close a tab with your finger, for example — but all in all, the touch-centric stand experience is quite pleasant. You just have to think of it as a complement to the traditional laptop environment rather than a replacement for it.

When the N20p is in its stand mode, the user interface does change a bit: All windows appear maximized, while a button shows up in the bottom-right area of the screen that allows you to switch between opened windows using a graphical interface. (Those already familiar with Chromebooks will note that it’s the same task-switching command also present on the top row of the regular Chrome OS keyboard.)

The on-screen keyboard works well enough, too, though if you’re typing anything more than a few words, you’ll almost certainly want to flip the system back around into its laptop mode for easier text input. Given the choice on any device, I think a full-size physical keyboard is always going to be preferable for heavy-duty typing.

Because the screen can be adjusted to any position while the N20p is in its stand mode, you can flip the laptop into a tent-like arrangement if you want — or even onto its side for a vertically oriented portrait view. I haven’t found a need to use either of those orientations, but the possibilities are there if you want them.

As for the display itself, it’s the same 1366 x 768 TN panel found in most lower-end Chromebooks these days — but even within those parameters, it’s one of the better screens I’ve seen. It’s glossy, bright and less grainy than the displays on many similarly priced systems. Viewing angles aren’t great and it’s no match for a higher-quality IPS display, but I’ve been able to use it for full days without being annoyed or feeling any significant eyestrain.

On the left edge of its frame, Lenovo’s N20p Chromebook has a proprietary charging port along with a USB 3.0 port, a dedicated HDMI-out port and a 3.5mm headphone jack. The laptop’s right edge, meanwhile, holds a USB 2.0 port and a physical power button — something slightly different from most Chromebooks, where the power button exists on the keyboard.

The N20p Chromebook has two speakers on either side of its bottom surface. The speakers are pretty decent, with loud, clear and full-sounding audio. They’re not the best you’ll ever hear, but for this class of device, they’re actually quite impressive.


So far so good, right? Unfortunately, there is one asterisk with Lenovo’s N20p Chromebook — and it’s on the subject of performance.

The N20p Chromebook uses one of Intel’s new Bay Trail processors — the Intel Celeron N2830 — along with 2GB of RAM. In real-world use, it feels like a meaningful step backward from the level of performance I’ve grown accustomed to seeing with the recent crop of Chrome OS devices, most of which are powered by Intel’s speedier Haswell-based chips.

To see the difference between two Chrome OS devices that use Intel processors, I compared the N20p to an Asus Chromebox, with a Haswell-based Cerelon 2955U processor and 2GB of RAM. The N20p Chromebook was consistently slower at loading pages — by as much as two to six seconds, depending on the site — and just seemed significantly less zippy overall.

Cons: Low-resolution display with low-quality TN panel; performance not as good as that of other Chromebooks in its class

In fact, even without a side-by-side comparison, the N20p just doesn’t feel terribly snappy. I noticed its limitations the most in situations where I had several browser tabs running; there, the device really seemed to struggle and reach levels of sluggishness I haven’t experienced on Chrome OS in quite some time.

All things considered, I’d say this: If you’re like most people and tend to keep only one or two tabs open at a time, the N20p should be fine for your needs. It’s still a noticeable step down from the level of performance you’d get from other similarly priced or even less expensive systems — which is disappointing, to say the least — but for basic levels of use, it’s acceptable enough and may be a worthwhile tradeoff for all of the device’s positives. If you do any resource-intensive multitasking, however, you’re going to find yourself frustrated by the relatively low performance ceiling.

Lenovo does offer a model of the N20p Chromebook with a slightly higher-end Bay Trail processor, the Intel Celeron N2930; that model is sold only via Lenovo’s website and costs $20 more than the regular base model. While I haven’t had an opportunity to test it firsthand, the promise of enhanced performance seems to make the extra $20 a worthwhile investment.

The N20p does do reasonably well in terms of battery life: The laptop is listed for eight hours of use per charge, which is pretty much in line with what I’ve gotten. As for storage, the device comes with 16GB of onboard space along with the option to expand with your own SD card.
Bottom line

Lenovo’s N20p Chromebook offers a compelling experience that goes beyond what the typical Chromebook provides. The tilting display really is a nice touch that expands the device’s potential and opens it up to new and interesting types of uses.

The system is held back, however, by lower than average performance — something we’ll probably be seeing more of as Intel’s Bay Trail chips make their way into more Chrome OS devices. That’s a factor you’ll have to closely consider in determining whether the N20p Chromebook is right for you.

The N20p Chromebook is a standout device with lots of attractive qualities. For folks in the power-user camp, it’s just a shame it’s not available with the more robust internals that other similarly priced products provide.

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Ultimate cloud speed tests: Amazon vs. Google vs. Windows Azure

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A diverse set of real-world Java benchmarks shows that Google is fastest, Azure is slowest, and Amazon is priciest

If the cartoonists are right, heaven is located in a cloud where everyone wears white robes, every machine is lightning quick, everything you do works perfectly, and every action is accompanied by angels playing lyres. The current sales pitch for the enterprise cloud isn’t much different, except for the robes and the music. The cloud providers have an infinite number of machines, and they’re just waiting to run your code perfectly.

The sales pitch is seductive because the cloud offers many advantages. There are no utility bills to pay, no server room staff who want the night off, and no crazy tax issues for amortizing the cost of the machines over N years. You give them your credit card, and you get root on a machine, often within minutes.

[ From Amazon to Windows Azure, see how the elite 8 public clouds compare in InfoWorld Test Center’s review. | Benchmarking Amazon: The wacky world of cloud performance | Stay on top of the cloud with InfoWorld’s “Cloud Computing Deep Dive” special report and Cloud Computing Report newsletter. ]

To test out the options available to anyone looking for a server, I rented some machines on Amazon EC2, Google Compute Engine, and Microsoft Windows Azure and took them out for a spin. The good news is that many of the promises have been fulfilled. If you click the right buttons and fill out the right Web forms, you can have root on a machine in a few minutes, sometimes even faster. All of them make it dead simple to get the basic goods: a Linux distro running what you need.

At first glance, the options seem close to identical. You can choose from many of the same distributions, and from a wide range of machine configuration options. But if you start poking around, you’ll find differences — including differences in performance and cost. The machines may seem like commodities, but they’re not. This became more and more evident once the machines started churning through my benchmarks.

Fast cloud, slow cloudI tested small, medium, and large machine instances on Amazon EC2, Google Compute Engine, and Microsoft Windows Azure using the open source DaCapo benchmarks, a collection of 14 common Java programs bundled into one easy-to-start JAR. It’s a diverse set of real-world applications that will exercise a machine in a variety different ways. Some of the tests will stress CPU, others will stress RAM, and still others will stress both. Some of the tests will take advantage of multiple threads. No machine configuration will be ideal for all of them.

Some of the benchmarks in the collection will be very familiar to server users. The Tomcat test, for instance, starts up the popular Web server and asks it to assemble some Web pages. The Luindex and Lusearch tests will put Lucene, the common indexing and search tool, through its paces. Another test, Avrora, will simulate some microcontrollers. Although this task may be useful only for chip designers, it still tests the raw CPU capacity of the machine.

I ran the 14 DaCapo tests on three different Linux machine configurations on each cloud, using the default JVM. The instances aren’t perfect “apples to apples” matches, but they are roughly comparable in terms of size and price. The configurations and cost per hour are broken out in the table below.

I gathered two sets of numbers for each machine. The first set shows the amount of timethe instance took to run the benchmark from a dead stop. It fired up the JVM, loaded the code, and started to work. This isn’t a bad simulation because many servers start up Java code from command lines in scripts.

To add another dimension, the second set reports the times using the “converge” option. This runs the benchmark repeatedly until consistent results appear. This sometimes happens after just a few runs, but in a few cases, the results failed to converge after 20 iterations. This option often resulted in dramatically faster times, but sometimes it only produced marginally faster times.

The results (see charts and tables below) will look like a mind-numbing sea of numbers to anyone, but a few patterns stood out:

Google was the fastest overall. The three Google instances completed the benchmarks in a total of 575 seconds, compared with 719 seconds for Amazon and 834 seconds for Windows Azure. A Google machine had the fastest time in 13 of the 14 tests. A Windows Azure machine had the fastest time in only one of the benchmarks. Amazon was never the fastest.
Google was also the cheapest overall, though Windows Azure was close behind. Executing the DaCapo suite on the trio of machines cost 3.78 cents on Google, 3.8 cents on Windows Azure, and 5 cents on Amazon. A Google machine was the cheapest option in eight of the 14 tests. A Windows Azure instance was cheapest in five tests. An Amazon machine was the cheapest in only one of the tests.

The best option for misers was Windows Azure’s Small VM (one CPU, 6 cents per hour), which completed the benchmarks at a cost of 0.67 cents. However, this was also one of the slowest options, taking 404 seconds to complete the suite. The next cheapest option, Google’s n1-highcpu-2 instance (two CPUs, 13.1 cents per hour), completed the benchmarks in half the time (193 seconds) at a cost of 0.70 cents.

If you cared more about speed than money, Google’s n1-standard-8 machine (eight CPUs, 82.9 cents per hour) was the best option. It turned in the fastest time in 11 of the 14 benchmarks, completing the entire DaCapo suite in 101 seconds at a cost of 2.32 cents. The closest rival, Amazon’s m3.2xlarge instance (eight CPUs, $0.90 per hour), completed the suite in 118 seconds at a cost of 2.96 cents.

Amazon was rarely a bargain. Amazon’s m1.medium (one CPU, 10.4 cents per hour) was both the slowest and the most expensive of the one CPU instances. Amazon’s m3.2xlarge (eight CPUs, 90 cents per hour) was the second fastest instance overall, but also the most expensive. However, Amazon’s c3.large (two CPUs, 15 cents per hour) was truly competitive — nearly as fast overall as Google’s two-CPU instance, and faster and cheaper than Windows Azure’s two CPU machine.

These general observations, which I drew from the “standing start” tests, are also borne out by the results of the “converged” runs. But a close look at the individual numbers will leave you wondering about consistency.

Some of this may be due to the randomness hidden in the cloud. While the companies make it seem like you’re renting a real machine that sits in a box in some secret, undisclosed bunker, the reality is that you’re probably getting assigned a thin slice of a box. You’re sharing the machine, and that means the other users may or may not affect you. Or maybe it’s the hypervisor that’s behaving differently. It’s hard to know. Your speed can change from minute to minute and from machine to machine, something that usually doesn’t happen with the server boxes rolling off the assembly line.

So while there seem to be clear performance differences among the cloud machines, your results could vary. These patterns also emerged:

Bigger, more expensive machines can be slower. You can pay more and get worse performance. The three Windows Azure machines started with one, two, and eight CPUs and cost 6, 12, and 48 cents per hour, but the more expensive they were, the slower they ran the Avrora test. The same pattern appeared with Google’s one CPU and two CPU machines.
Sometimes bigger pays off. The same Windows Azure machines that ran the Avrora jobs slower sped through the Eclipse benchmark. On the first runs, the eight-CPU machine was more than twice as fast as the one-CPU machine.

Comparisons can be troublesome. The results table has some holes produced when a particular test failed, some of which are easy to explain. The Windows Azure machines didn’t have the right codec for the Batik tests. It didn’t come installed with the default version of Java. I probably could have fixed it with a bit of work, but the machines from Amazon and Google didn’t need it. (Note: Because Azure balked at the Batik test, the comparative times and costs cited above omit the Batik results for Amazon and Google.)
Other failures seemed odd. The Tradesoap routine would generate an exception occasionally. This was probably caused by some network failure deep in the OS layer. Or maybe it was something else. The same test would run successfully in different circumstances.

Adding more CPUs often isn’t worth the cost. While Windows Azure’s eight-CPU machine was often dramatically faster than its one-CPU machine, it was rarely ever eight times faster — disappointing given that it costs eight times as much. This was even true on the tests that are able to recognize the multiple CPUs and set up multiple threads. In most of the tests the eight CPU machine was just two to four times faster. The one test that stood out was the Sunflow raytracing test, which was able to use all of the compute power given to it.
The CPU numbers don’t always tell the story. While the companies usually double the price when you get a machine with two CPUs and multiply by eight when you get eight CPUs, you can often save money if you don’t increase the RAM too. But if you do, don’t expect performance to still double. The Google two-CPU machine in these tests was a so-called “highcpu” machine with less RAM than the standard machine. It was often slower than the one-CPU machine. When it was faster, it was often only about 30 percent faster.
Thread count can also be misleading. While the performance of the Windows Azure machines on the Sunflow benchmark track the number of threads, the same can’t be said for the Amazon and Google machines. Amazon’s two-CPU instance often went more than twice as fast as the one-CPU machine. On one test, it was almost three times faster. Google’s two-CPU machine, on the other hand, went only 20 to 25 percent faster on Sunflow.

The pricing table can be a good indicator of performance. Google’s n1-highcpu-2 machine is about 30 percent more expensive than the n1-standard-1 machine even though it offers twice as much theoretical CPU power. Google probably used performance benchmarks to come up with the prices.

Burst effects can distort behavior. Some of the cloud machines will speed up for short “bursts.” This is sort of a free gift of the extra cycles lying around. If the cloud providers can offer you a temporary speed up, they often do. But beware that the gift will appear and disappear in odd ways. Thus, some of these results may be faster because the machine was bursting.
The bursting behavior varies. On the Amazon and Google machines, the Eclipse benchmark would speed up by a factor of more than three when using the “converge” option of the benchmark. Windows Azure’s eight-CPU machine, on the other hand, wouldn’t even double.

If all of these factors leave you confused, you’re not alone. I tested only a small fraction of the configurations available from each cloud and found that performance was only partially related to the amount of compute power I was renting. The big differences in performance on the different benchmarks means that the different platforms could run your code at radically different speeds. In the past, my tests have shown that cloud performance can vary at different times or days of the week.

This test matrix may be large, but it doesn’t even come close to exploring the different variations that the different platforms can offer. All of the companies are offering multiple combinations of CPUs and RAM and storage. These can have subtle and not-so-subtle effects on performance. At best, these tests can only expose some of the ways that performance varies.

This means that if you’re interested in getting the best performance for the lowest price, your only solution is to create your own benchmarks and test out the platforms. You’ll need to decide which options are delivering the computation you need at the best price.

Calculating cloud costsWorking with the matrix of prices for the cloud machines is surprisingly complex given that one of the selling points of the clouds is the ease of purchase. You’re not buying machines, real estate, air conditioners, and whatnot. You’re just renting a machine by the hour. But even when you look at the price lists, you can’t simply choose the cheapest machine and feel secure in your decision.

The tricky issue for the bean counters is that the performance observed in the benchmarks rarely increased with the price. If you’re intent upon getting the most computation cycles for your dollar, you’ll need to do the math yourself.

The simplest option is Windows Azure, which sells machines in sizes that range from extra small to extra large. The amount of CPU power and RAM generally increase in lockstep, roughly doubling at each step up the size chart. Microsoft also offers a few loaded machines with an extra large amount of RAM included. The smallest machines with 768MB of RAM start at 2 cents per hour, and the biggest machines with 56GB of RAM can top off at $1.60 per hour. The Windows Azure pricing calculator makes it straightforward.

One of the interesting details is that Microsoft charges more for a machine running Microsoft’s operating system. While Windows Azure sometimes sold Linux instances for the same price, at this writing, it’s charging exactly 50 percent more if the machine runs Windows. The marketing department probably went back and forth trying to decide whether to price Windows as if it’s an equal or a premium product before deciding that, duh, of course Windows is a premium. 

Google also follows the same basic mechanism of doubling the size of the machine and then doubling the price. The standard machines start at 10.4 cents per hour for one CPU and 3.75GB of RAM and then double in capacity and price until they reach $1.66 per hour for 16 CPUs and 60GB of RAM. Google also offers options with higher and lower amounts of RAM per CPU, and the prices move along a different scale.

The most interesting options come from Amazon, which has an even larger number of machines and a larger set of complex pricing options. Amazon charges roughly double for twice as much RAM and CPU capacity, but it also varies the price based upon the amount of disk storage. The newest machines include SSD options, but the older instances without flash storage are still available.

Amazon also offers the chance to create “reserved instances” by pre-purchasing some of the CPU capacity for one or three years. If you do this, the machines sport lower per-hour prices. You’re locking in some of the capacity but maintaining the freedom to turn the machines on and off as you need them. All of this means that you can ask yourself how much you intend to use Amazon’s cloud over the next few years because it will then help you save more money.

In an effort to simplify things, Google created the GCEU (Google Compute Engine Unit) to measure CPU power and “chose 2.75 GCEUs to represent the minimum power of one logical core (a hardware hyper-thread) on our Sandy Bridge platform.” Similarly, Amazon measures its machines with Elastic Compute Units, or ECUs. Its big fat eight-CPU machine, known as the m3.2xlarge, is rated at 26 ECUs while the basic one-core version, the m3.medium, is rated at three ECUs. That’s a difference of more than a factor of eight.

This is a laudable effort to bring some light to the subject, but the benchmark performance doesn’t track the GCEUs or ECUs too closely. RAM is often a big part of the equation that’s overlooked, and the algorithms can’t always use all of the CPU cores they’re given. Amazon’s m3.2xlarge machine, for instance, was often only two to four times faster than the m3.medium, although it did get close to being eight times faster on a few of the benchmarks.

Caveat cloudsterThe good news is that the cloud computing business is competitive and efficient. You put in your credit card number, and a server pops out. If you’re just looking for a machine and don’t have hard and fast performance numbers in mind, you can’t go wrong with any of these providers.

Is one cheaper or faster? The accompanying tables show the fastest and cheapest results in green and the slowest and priciest results in red. There’s plenty of green in Google’s table and plenty of red in Amazon’s. Depending on how much you emphasize cost, the winners shift. Microsoft’s Windows Azure machines start running green when you take the cost into account.

The freaky thing is that these results are far from consistent, even across the same architecture. Some of Microsoft’s machines have green numbers and red numbers for the same machine. Google’s one-CPU machine is full of green but runs red with the Tradesoap test. Is this a problem with the test or Google’s handling of it? Who knows? Google’s two-CPU machine is slowest on the Fop test — and Google’s one-CPU machine is fastest. Go figure.

All of these results mean that doing your own testing is crucial. If you’re intent on squeezing the most performance out of your nickel, you’ll have to do some comparison testing and be ready to churn some numbers. The performance varies, and the price is only roughly correlated with usable power. There are a number of tasks where it would just be a waste of money to buy a fancier machine with extra cores because your algorithm can’t use them. If you don’t test these things, you can be wasting your budget.

It’s also important to recognize that there can be quite a bit of markup hidden in these prices. For comparison, I also ran the benchmarks on a basic eight-core (AMD FX-8350) machine with 16GB of RAM on my desk. It was generally faster than Windows Azure’s eight-core machine, just a bit slower than Google’s eight-core machine, and about the same speed as Amazon’s eight-core box. Yet the price was markedly different. The desktop machine cost about $600, and you should be able to put together a server in the same ballpark. The Google machine costs 82 cents per hour or about $610 for a 31-day month. You could start saving money after the first month if you build the machine yourself.

The price of the machine, though, is just part of the equation. Hosting the computer costs money, or more to the point, hosting lots of computers costs lots of money. The cloud services will be most attractive to companies that need big blocks of compute power for short sessions. If they pay by the hour and run the machines for only a short block of time, they can cut the costs dramatically. If your workload appears in short bursts, the markup isn’t a problem because any machine you own will just sit there most of the day waiting, wasting cycles and driving up the air conditioning bills.

All of these facts make choosing a cloud service dramatically more complicated and difficult than it might appear. The marketing is glossy and the imagery makes it all look comfy, but hidden underneath is plenty of complexity. The only way you can tell if you’re getting what you’re paying for is to test and test some more. Only then can you make a decision about whether the light, airy simplicity of a cloud machine is for you.

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Windows 8 cobranding with Android may backfire for Microsoft

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All business in the front and party in the back, this category is the mullet of mobile devices.

At CES, dual-boot devices running Windows 8.1 and Android revealed a conflicted situation for Microsoft. In the struggle to make Windows 8 relevant in mobile, the OS has been cobranded with Android on these devices.

Microsoft’s OEMs missed the point. Relevancy is measured in terms of digital life, the amount of time mobile users spend engaged with a mobile internet ecosystem. According to Chetan Sharma’s research, Microsoft ranks seventh in importance. In a similar unpublished interactive survey of 300 industry insiders at the Open Mobile Summit in San Francisco, Google led the digital life market, with Apple in second place, while Microsoft finished in the back of the pack.

With dual-boot tablets and notebooks, Microsoft is willfully sacrificing valuable digital life for Windows 8. As Richard Windsor of Radio Free Mobile reported from CES:

“The idea is that the user uses Windows 8.1 when he or she is working and Android when at leisure. This is a crazy proposition as the whole point of Windows 8 is to make an environment that is optimized for both use cases, and it’s telling that the OEMs feel the need to add something else.”

Splitting productivity time using a keyboard with Windows 8 and then rebooting for leisure time via gestures with Android just compounds the problem, because it stagnates users’ curiosity to search for new Windows 8 apps. This reduces some much-needed traffic to the Windows app store, which, compared to Android and iOS, is currently a ghost town.

Dual-boot teaches a user to boot Windows 8 for compatibility with Microsoft’s old ecosystem and to boot Android to use the new mobile ecosystem. This points to a glaring problem. If Microsoft is to fix this, Windows 8 users need a reason to spend their entire digital life in the Windows 8 ecosystem; when the user toggles from desktop to mobile they have to think –there’s an app for that – and download a Windows app.

Once upon a time, Windows users helped one another make Windows applications work. Given the dominance of earlier Windows versions, Microsoft had an army of users to help other users make Windows work. Mobile has completely changed user behavior. Mobile users download an app, give it a few seconds to satisfy the need that influenced them to download it, and if the app fails, they uninstall it and try the next app in the category. According to NetMarketshare, Microsoft retains 91% of the desktop market share, but Windows 8 only accounts for 10% of that. So a user’s chance of solving a Windows 8 problem through the help of another user who understands Windows 8 is only one in 10. According to Windsor:

“The Metro [the old name for the Windows 8 UI] user experience is perfectly capable of offering a good experience for Digital Life.”
If Microsoft is to become relevant in mobile, it needs to convince users of the value of this UI without the army of helpers it once had. Cobranding with Android doesn’t help, it hurts. Dual boot and virtualization isn’t a solution any longer in the consumer mobile market because app developers motivated by a good business model in target devices will port their apps. Dual boot emphasizes the limited number of apps available for Windows 8, and proves that Microsoft has not convinced users that it’s a good OS to begin with.

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Data scientists: IT’s new rock stars

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Data scientists: IT’s new rock stars
These days, just showing up to work as a data scientist will get you attention.

The evolution of the data scientist role is making even those who are successful in IT wish they could go back.

In an interview with Network World last month, Robert Stroud, a member of ISACA’s Strategic Advisory council and vice president of innovation and strategy at CA Technologies, called the data scientist a “hard sought-after role” and compelled those entering the technology job market target that field.

“If I were starting my career again, I’d be going into this space,” Stroud says.

The hype for data scientists was given some weight in American Journalism Review’s recent profile of Buzzfeed’s director of data science, Ky Harlin. Buzzfeed’s growth has been massive in the past few years, reaching an average of 55.2 million uniquely visitors, according to September 2013 numbers from Quantcast. That’s more than Craigslist and AOL, and within reach of Yahoo and Essentially, Buzzfeed has made a business out of viral content, and Harlin is responsible for sustaining that.

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According to the AJR profile, Harlin created his own algorithms that identify when and why specific pieces of web content will go viral.

“There are many variables we look at, both quantitative and descriptive,” Harlin told AJR. “Quantitative factors are things like the amount of times something’s been shared on Facebook, while descriptive factors are things like what’s contained in the text of the article. We employ machine learning algorithms that help us map out the relationship between those variables and shareability.”

What’s more interesting is where Harlin developed those skills – a medical imaging company. According to AJR, Buzzfeed’s founder and CEO Jonah Peretti sought out Harlin while he was working in the medical imaging field, and brought him in for an interview about what data science could do for his media company. In the interview, Peretti found just how versatile data science skills can be.

“There are actually a lot of similarities between medical imaging and content publishing on a purely mathematical level,” Peretti told AJR. “Both fields are looking for patterns in vast data sets. And during the interview, [Harlin] was clearly more interesting in understanding how content spreads than medical imaging, so I knew he would be good.”

The rest of the details on Harlin’s role and how he became the company’s “secret weapon,” as AJR described him, are available in that article, which is an interesting peak behind the curtains at the fastest-growing media company in the world.

However, the mere fact that a technology employee would be the center of a lengthy profile in the American Journalism Review should be an eye-opener. The kind of attention it’s been gathering has sent experts in the field out to start spread the word. In a June 2012 interview with Network World, Laura Kelley, Houston vice president for IT staffing and consulting firm Modis, advised those with MBAs to seek out certifications for statistical software programs, and those with computer science degrees to pursue an MBA. Facebook and Google have both been looking to bring on data scientists for years. In October 2012, the Harvard Business Review called data scientist “the sexiest job of the 21st century.” Data scientists like Harlin can go from work in the medical imaging field to a high-profile job at a media startup, and even though, like most tech workers, his day-to-day job rarely changes, they’ll get press coverage. It seems the Harvard Business Review was right.

It all makes sense. Data scientists represent the new age of IT, where employees will not only contribute to a company’s business goals, but help identify them in the first place.

“This is where you add real business value,” he says. “Where an IT person is not just running machines anymore, but fundamentally taking good information and helping the business make true business decisions so that they can adjust the business in real time based on this information. If used well, you’ll be able to spot trends and opportunities far faster than you could in the past.”

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Google, Intel cement ties on Chrome OS, could weaken Wintel

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New Chromebooks highlight a tight partnership between Google and Intel, and a shift away from only Wintel

New Chromebooks announced this week signal Intel’s willingness to broaden its horizons and work with companies like Google, at the expense of its long-standing Windows partnership with Microsoft.

Three new Chromebooks from Hewlett-Packard, Acer and newcomer Toshiba with Google’s Chrome OS were shown on stage during this week’s Intel Developer Forum. The sub-US$299 laptops will run on Intel’s Haswell chips, and executives from Google and the chip maker said they worked closely to tune the OS at the kernel and driver levels to work with Intel’s chips.

A tighter Chrome alliance with Google is just another example of how Intel, which has been largely left out of the tablet and smartphone markets, is spreading its wings to succeed in the PC, mobile and emerging markets like wearables. In an interview with IDG News Service, Intel president Renee James said the Microsoft-Intel alliance is alive, but the chip maker wants to offer choice beyond Windows.

“Microsoft [Windows] is not the only client operating system anymore. The same way for years and years Microsoft balanced between Intel and Advanced Micro Devices, we’re in the same situation now. Our customers want choice, and we offer choice,” James said.

Intel’s partnership with Google is centered around Android, but the Chrome OS partnership is mutually beneficial. Intel is looking to perk up PC sales following the slow adoption of Windows 8, while Google is trying to expand beyond smartphones and tablets into desktop-style computing with Chrome OS.

“Chrome OS represents a new form of computing,” said Sundar Pichai, senior vice president for Android, Chrome and applications at Google, in an appearance during a keynote speech by Doug Fisher, vice president of the software and services group at Intel, on Wednesday.

Intel sees Google as a partner for a range of devices, and the partnership has been getting stronger since they first started working together on Android two years ago, said Jack Gold, principal analyst at J. Gold Associates, during an interview on the show floor.

That doesn’t mean the Wintel alliance isn’t dead, but it is not close to what it was like four to five years ago, Gold said.

“Microsoft is going off dancing with other partners, Intel has got to do the same thing. Intel is going to go where the volumes are,” Gold said, referring to Microsoft’s decision to make Windows RT for processors designed by Intel’s rival ARM Holdings.

Intel had no choice but to support Chrome OS in the sub-$300 PC market, where Windows 8 does not fit, said Jim McGregor, principal analyst at Tirias Research.

“It’s like netbook 2.0,” McGregor said. “Intel is damned if they do, damned if they don’t.”

Intel’s relationship with Microsoft is deteriorating, which also may have prompted the chip maker to approach Google, McGregor said. Intel tried to develop operating systems like Meego, but failed.

“[Microsoft and Intel] get along in the face of the public, but there’s huge animosity,” McGregor said.

The analysts agreed that Chrome OS won’t sustain fast growth, but Intel had to continue supporting the OS to maintain a presence in the low-end of the PC market. Samsung offers a Chromebook based on a processor from ARM, which is trying to gain share in the low-cost PC market.

Intel will support any OS in markets ranging from PCs to wearables, but only if the customer asks for it, analysts said. For example, Intel has said smartphones based on its Atom chips could support Windows Phone OS, but only if customers requested it.

Intel this week introduced the very low power Quark family of chips for wearable and embedded devices. Intel didn’t say which OSes will run on Quark, but Google has a non-Android OS for Google Glass. Intel also could possibly use a real-time operating system from its own Wind River unit. But the chip maker needs to keep its options open, analysts said.

“It’s a logical business model for Intel,” Gold said.

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Google Android feeling brain drain?

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VP of Android mgmt. Hugo Barra headed from Google to Xiaomi – but why?

And just like that, Google I/O 2014 will be a different show – vice president of Android product management Hugo Barra abruptly announced that he’ll be leaving Google in “a few weeks” to join Chinese phone maker Xiaomi.

It’s not the first high-profile change at the Android unit in recent months. Andy Rubin, who’d been with Android since its pre-Google inception, left in March to tinker with robots over at Google X. Over at the Android Open-Source Project, maintainer Jean-Baptiste Quéru stepped down a couple weeks ago over an apparent clash with Qualcomm.

Uniting Android and Chrome under Sundar Pichai’s leadership made sense in the case of Rubin, and JBQ’s role as interlocutor between the AOSP community and Google’s corporate partners always carried the possibility of precisely the type of situation that led to his leaving. Yet Barra’s departure is less readily susceptible to explanation – he’s been one of the more prominent public faces of Android, and a key presenter at Google’s I/O developer conferences.

Valleywag is keen to paint Barra’s move as fallout from some sort of sordid romantic entanglement involving another Google employee and no less than Sergey Brin himself, based largely on reports from AllThingsD which were based in turn on anonymous sources.

It’s a bit disappointing to see from Valleywag, which frequently sends up the craziness of Silicon Valley’s elites with much more justification, but I suppose you can’t really complain too hard about what you get from a site that says up-front that it deals in gossip. AllThingsD’s anonymous “sources close to the situation” also say that Barra made his decision before “he was made aware of the new relationship,” for what it’s worth.

At any rate, broken heart or no, Barra is set to take over as vice president of Xiaomi Global, according to a Google Plus post making his pending departure official. It’s a pretty big coup for a company without much public profile outside of China, but, according to USA Today, much in keeping with its strategy of attracting experienced personnel from established U.S. companies like Google, Microsoft and Motorola.

* A recent study from the Department of Homeland Security and the FBI says that Android is a “primary target” for mobile malware attacks thanks to its open architecture and skyrocketing user base. The biggest threats to Android users, the report says, are SMS Trojans, rootkits and bogus Google Play domains.

The study, which was publicized by activist group Public Intelligence, also states that older versions of the platform – which are still in use on 44% of Android devices – are particularly vulnerable to malicious attacks. You know, just in case you were looking for other reasons OS fragmentation is bad.

* Android geeks briefly erupted in flames this week at the news that well-known Android developer Koushik Dutta’s AirCast app for the Chromecast video dongle had been prevented from working by an update. AirCast was designed to allow users to stream locally stored content from their devices to the TV, but an official update to Chromecast added a whitelist system, preventing users from using the device to stream content from non-approved sources.

Dutta’s sonorously unhappy Google Plus post here has most of the details.

However, Google subsequently told The Verge that the software is still early in its development stages, and that “we’re excited to bring more content to Chromecast and would like to support all types of apps, including those for local content.” So that’s probably that, then.

* Like most people, I’ve been spending plenty of time lately thinking to myself “you know, I could really do with some more PR stunts involving Google Glass.” Take heart, everyone! A surgeon at Ohio State University has performed an ACL repair operation while wearing the device, which streamed pictures to colleagues and students.

To be fair, that’s one of the more useful PR stunts I’ve heard of recently. But I’m just worried about what happens when a doctor is out and about and accidentally switches back to the consultation app. It’d have to be a little off-putting to keep seeing gastrointestinal surgery when you’re just trying to get directions to the nearest Starbucks.


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