Wednesday, April 1, 2015

The geek shall inherit the earth: The age of developer-defined infrastructure

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If “software is eating the world,” then the meal will be prepared by developers.

Over the past several years, there have been articles about the primacy of software engineers. This reality is supported by the fact that technical majors are making more money coming out of college than their classmates and the average salary for a developer has risen dramatically over the past few years. In fact, developers will soon become some of the highest paid employees in a company — and I mean every company, not just in Silicon Valley.

We are entering the age of developer-defined infrastructure (DDI). Historically, developers had limited say in many application technologies. During the 1990s, we effectively lived in a bilateral world of Microsoft .NET vs Java, and we pretty much defaulted to using Oracle as a database. In the past several years, we have seen a renaissance in developer technologies and application infrastructure from a proliferation of languages and frameworks (Go, Scala, Python, Swift) as well as data infrastructure (Hadoop, Mongo, Kafka, etc.). With the power of open source, developers can now choose the language, runtime, and database that make sense. However, developers are not only making application infrastructure decisions. They are also making underlying cloud infrastructure decisions. They are determining not only where will their applications run (private or public clouds) but how storage, networking, compute, and security should be managed. This is the age of DDI, and the IT landscape will never look the same again.

The roles of developer and system administrators were separate and defined: developers made decisions about developer tools like source code management and issue tracking (Git, Jira), and system administrators (server admins, storage admins, network admins) managed production and infrastructure standards. However, with the move to clouds like Amazon Web Services (AWS) have given developers choice in what infrastructure services they can use.

How did we get here? Let’s take a quick look at the evolution of the data center.

The three ages of the data center

Physical-defined infrastructure (~1985 to 1999)
During the rise of the client/server era, corporations were moving from mainframes to mini-computers to a powerful server computers coupled with personal computers. This was the age when hardware design and hardware vendors drove IT strategy. Engineers debated CPU architectures (RISC vs CISC), Power vs X86 vs SPARC and the strategic vendors of this generation were companies like Sun Microsystems, IBM, and HP.

Software-defined infrastructure (~2000 to 2014)
In physical defined infrastructure, software was usually paired with hardware. In the early 2000s, we saw the Intel X86 architecture win out in the CPU layer, allowing servers and systems to standardize. Once you have hardware standards, the software ecosystem grew up around these servers started to decouple the logical from the physical. Operating systems like Windows and Linux became the layer to which software interacted with hardware. Eventually, VMware pioneered the idea of software virtualization, which enabled IT administrators to render virtual computers, disks, and networks all in software. Riding the power of Moore’s Law, VMware turned physical defined infrastructure into software-defined infrastructure. You can trace the evolution from physical to virtual just by looking at how profit margins flowed from system vendors like Sun to the winers of the software-defined infrastructure age like VMware, Microsoft, Red Hat, and Intel as the de facto CPU standard. VMware moved from virtualized compute to storage (vSAN) and then networking (NSX).

If VMware pioneered the idea of software-defined infrastructure, the web-scale giants like Google and Facebook perfected it. Living by the adage “software will eventually work, hardware will eventually fail,” they saw the value of using commodity hardware and software to make unreliable hardware reliable.

The impact of this software-defined data center can be seen by the fate of some of the leaders of the physical defined infrastructure age: Dell went private, IBM sold its x86 server line to Lenovo, and HP is undergoing an identity crisis right now.

Developer-defined infrastructure (2015 to ????)
Welcome to the age of DDI, where developers are making decisions on how, what, and where their applications should run. DDI is the natural evolution of software defined infrastructure. The power of turning hardware into software is partly the separation of logical from physical into software, but mainly the fact that once you have hardware represented in software, you can treat hardware like any other piece of code. You can move it, you can program it, you can write programs for it. For example, on AWS, everything has an application programming interface (API) and can be programmed: storage, compute, networking, security, etc. Today, developers need to think like IT and operations, and IT administrators must enable developers to make these infrastructure choices and not constrain them. With this rise of devops and cloud, developers are looking for technologies to build, run, and manage their applications that support DDI: If VMware was the platform for the last 15 years, then companies, like Docker, could be the platform for the next 15. In particular, Docker supports:

  • Programmability and portability: Infrastructure should be treated like any other bit of software. No longer tied to a physical location, Docker containers can easily be moved anywhere, from a laptop in a coffee shop to a cloud. Even more importantly, DDI like Docker can be programmed through its own API.
  • Consolidation: This is the attribute of Docker that wins over most of the IT and system admins. Just like virtualization replaced physical infrastructure by turning 10 physical servers into 10 virtualized servers on a single machine, Docker can further increase the consolidation ratio of server workloads while improving speed and performance.
  • Move to microservices: Companies, like Twitter, Google, and Facebook have adopted microservices to build their next generation of applications. Microservices are easier to scale, update, and develop by a larger engineering team.

The geek shall inherit the earth

What are the implications for vendors, developers, and IT professionals in the DDI era? Software vendors that don’t understand or embrace developers will fail to be relevant. Incumbents that sell to IT administrators like virtualization, storage, network, or security admins will need to understand how to sell to developers. IT professionals need to think about how to enable developer choice and not restrict it. Finally, developers need to expand what the definition of an application is. Code isn’t just a program, or an app on a smart phone, code becomes everything from metal to management, to the final pixel.

Jerry Chen is a partner at Greylock Partners. He sits on the board of Docker. Previously he was vice president of cloud and application services at VMware.

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Big data analytics can prevent health care fraud. Here’s how

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Catching and preventing health care fraud is more important than ever.

The industry has undergone massive transformations with breakthroughs like the adoption of online health records, remote patient care and data-driven care. While these changes have created a more efficient health care system, improved patient outcomes, and boosted bottom lines, they have also given rise to a host of challenges that, if poorly addressed, could mean skyrocketing costs, breached privacy, and even patients’ lives.

According to the Association of Certified Fraud Examiners, 2015 is the year that technology will give fraudsters an edge. Yet, while technology is contributing to the sophistication of fraud schemes, it is also providing organizations and government investigators with powerful weapons to catch and prevent perpetrators. As data analytics rises to the top as the weapon of choice against health care fraud, the association states that gleaning insights from unstructured data will be the most notable use of analytic tools.

As sophisticated data-analytics tools become more accessible, we can expect to see the use of them make progress in two areas: securing patient privacy and mitigating prescription fraud.

Data analytics prevent health care data breaches

The past year was dim for cybersecurity with major data breaches like those at Sony, Target and eBay reinforcing the importance of protecting sensitive information. Unfortunately, health care organizations are not immune to these data attacks. In fact, a 2014 analysis of Standard & Poor’s 500-stock index companies by BitSight Technologies found that health care and pharmaceutical companies fare worse than retailers in terms of security performance with poor practices and slow response times.

For health care organizations tasked with the responsibility to protect patient details and medical information, data is their best friend. It can be used to not only address security, fraud prevention and compliance problems, but also to anticipate and proactively address these issues.

With the health care security landscapes and compliance requirements constantly evolving, organizations must be able to act quickly. And doing so requires unlocking trends, patterns, and outliers buried in log, sensor, and machine data –– both structured and unstructured types of data.

Collecting, preparing, and analyzing this fragmented data is no small feat, but with the help of sophisticated data analytics, it’s possible. Big data analytics is the most powerful weapon in this fight because it allows organizations to combine, integrate, and analyze all of their data at once — regardless of source, type, size, or format — and identify patterns needed to address fraud and compliance-related challenges. For example, organizations can analyze public websites, tracking pages, and application programming interfaces to catch attacks early on or analyze log files to spot abnormal server access patterns and perform security forensics.

Data defers prescription drug abuse

Not only can data analytics help protect patient data, it can also help protect patient lives. According to the Centers for Disease Control and Prevention (CDC), more than half of the 43,982 overdose deaths in 2012 were related to pharmaceuticals, and this prescription drug abuse costs the nation more than $55 billion annually. If doctors and pharmacies have quick access to controlled substance history information at the point of care, it will help them make better prescribing decisions and identify potential prescription drug abuse.

With the ability to combine multiple data sources, analyze data and quickly deliver insights, pharmacies, doctor offices, and hospitals can track abnormal activity to mitigate prescription drug abuse. Currently, California has a Prescription Drug Monitoring Program (PDMP) system, which allows health care workers eligible to prescribe and dispense controlled substances to access timely patient history information. More and more states are calling for secure databases like this that use big data analytics to detect patterns of fraud or misuse. Using data analytics tools that simplify the process and deliver digestible data visualizations empower everyone, not just data scientists, to use data for the benefit of all. Rather than just delivering raw data to health care professionals, sophisticated databases like California’s will give health care professionals a larger picture that allows them to address why, where, when, and how these issues are arising.

In the fight against health care fraud, it’s clear that data analytics will play a crucial role. As more organizations adopt analytics tools that make big data simple for everyone, we’ll start to see its benefits spread across all aspects of health care.

Stefan Groschupf is chief executive of Datameer.

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Tuesday, March 31, 2015

DroneDeploy tech creates aerial maps in real time, often before a drone even lands

A 3D model of a construction site generated by software from DroneDeploy.

SONOMA, Calif. — As I clicked the little red button on the screen, the drone in front of me leaped into the air, soared to about 250 feet above the ground, and then began methodically flying back and forth in a lawnmower pattern a hundred yards or so away, all the while taking photos.

In the past, I would have had to wait hours after the drone landed and I’d downloaded the pictures for third-party software to stitch them together into a single image that I could use as a map of the vineyard stretching out on the horizon. But today, even as the drone was still above me, the photos were appearing on the mobile phone and already being stitched into a map.

I had come here to wine country to see a demo of drone-based mapping and 3D modeling technology from San Francisco startup DroneDeploy, which has been developing software that can autonomously control consumer- and enterprise-grade drones, as well as manage imagery taken by the flying devices.

Earlier today, the company announced a $9 million Series A round led by Emergence Capital, bringing its total funding to $11 million. Here, at an invite-only event held at the Ram’s Gate winery, surrounded by lush green grapevines, the company was showing off what its technology can now do for customers in the agriculture, construction, and mining industries.

The demonstration was of DroneDeploy’s brand-new app — for iOS and Android — and the San Francisco startup’s software automatic integration with DJI drones. As DroneDeploy cofounder and chief executive Mike Winn put it, the company has built what might be the world’s-first real-time mapping technology, something even Google and NASA can’t do.

Iain Butler, a developer of software for drones, told VentureBeat that until he’d seen a demo of DroneDeploy’s technology, he didn’t think it was possible to put together a properly stitched map based on images taken by a drone in less than seven hours or so. But he said Winn promised it was possible in 15 minutes. A skeptic until he saw the demo, Butler is now a convert. And here’s why: As Winn explained, “in some cases, 90 percent of the data is returned before the drone even returns to land.”

DJI partnership

China’s DJI has become the world’s best-selling drone manufacturer. Every day, the company sells about 2,000 of its devices. So partnering with the company is a big feather in DroneDeploy’s cap.

The app shows that the survey route is planned and the drone is ready to fly.

Above: The app shows that the survey route is planned and the drone is ready to fly.

Image Credit: DroneDeploy

Now integrated with DJI’s Phone 2 Vision+ drones, as well as those from 3D Robotics and AgEagle, DroneDeploy’s software is meant to allow autonomous control of the flying devices with just a few taps on a mobile app. “This takes [DJI’s Phantom] from being a hobbyist toy and makes them a real tool,” said CTO and cofounder Nick Pilkington.

For now, the DJI integration only works on Android devices, but DroneDeploy says iOS functionality should be added within about two months.

Upon launching the app, a user sees an aerial image of their current location. Then they tap the screen to define an area — which is customizable — they’d like to survey for mapping purposes. The app then does a few safety checks in the background, and once it’s ready, a button shows up to start flying. Tap that button and the drone takes off and begins the survey — with no manual control by the user at all.

That’s key, DroneDeploy believes, because the devices are not always easy to control in flight, especially in rough weather. But with this app connected to a drone, the software does all the work.

What really makes it worth its price of $99 a month is its ability to send the drones on those surveys and autonomously work on the map even as the device is still in the air. And it’s up to the user to determine whether they’re interested in a high-resolution, up-close look at something like a construction site, or a broader, lower-resolution look at, say, a corn field.

According to Pilkington, the app allows the drone to autonomously fly over almost any terrain because it correlates the GPS coordinates of the location with a geographical database. That means that while the drone is in flight, the software knows what the device might encounter, and how to avoid it.

Now, as DroneDeploy moves forward, it is getting ready to add more drone manufacturer partners. The startup will use its new funding to build out its engineering team. Winn said the company also hopes to enhance its software so that it can proactively detect problems for clients like railroad owners. The idea, he said, is that the software could survey tracks and look for, and identify, obstacles. If any are discovered, Winn added, the app could automatically inform the railway.

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Scientologists’ tweet campaign against ‘Going Clear’ movie was laughably clumsy

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It’s well known that the Church of Scientology takes a “fight fire with fire” approach to people who criticize it, and in the face of the church’s damning portrayal in Alex Gibney’s documentary “Going Clear,” it took to Twitter to mount its defense. With pretty poor results.

The paid tweets come from an account called @FreedomEthics, which the church set up just for the campaign (its regular account is @Scientology). The tweets began before the movie premiered March 29, and are still flowing.

The Church of Scientology is a rich organization, yet is exempt from some taxes because it qualifies as a religious organization. We don’t know if it received any tax breaks on its purchase of thousands of sponsored tweets from Twitter.

Some of the tweets fault the movie for not filling up venues:

Many of the tweets say something like “More people watched X show than watched ‘Going Clear.” And they just fill in the “X” with whatever shows they can think of. Over and over. It sounds like a playground taunt.

I later found out that these tweets were in response to an HBO claim that “Going Clear” had more viewers than a Beyonce documentary. The Scientologists disagreed with that.

Another tweet portrays Gibney as a Stalin-esque figure, with the heading “HBO’s Doctor of Propaganda.” If you click the link, you go to a page where the church has posted videos that attempt to discredit the sources Gibney used in the movie.

The best parts are the titles above the videos. The say the person’s name, then tack on an insult. Like “Mike Rinder — The Wife Beater” and “Sarah Goldberg — The Homewrecker.” Good stuff.

And here’s another tweet about another of Gibney’s sources. This one uses a more direct approach.

And there are many others. If anything, these tweets probably increased interest in Gibney’s movie, as this tweeter suggests:

The fact is, the Church of Scientology is perceived by normal people as a cult-like religion for the weird, the rich, the famous, or all three. That’s why so many people want to hear the truth about Scientology, and why so few on Twitter have any sympathy for its cause.

In one tweet, the church even goes after the soundtrack of Gibney’s film:

Indeed, the @FreedomEthics tweets are inevitably followed by lots of replies criticizing or mocking them. Many of the replies criticized the Scientologists for hiding behind a “fake” Twitter handle to mount its smear campaign against the movie. The main account is @Scientology, and the tweets are much more friendly there.

Just 815 tweets have come from the @FreedomEthics account.

It doesn’t have the look of a popular cause. The account has just 672 followers.

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Why 5 minutes of ‘Goo-diligence’ will save your startup thousands


“Dear Entrepreneur,

I’m glad you’ve decided to solve the world’s problems. I sincerely hope to see you succeed. Before you start, please spend five minutes Googling your solution with the questions below in mind. If you are still excited, let’s talk.”

That’s the advice I wish I’d had five years ago.

Entrepreneurs (myself included) have this incredible ability to ignore reality when it isn’t in line with our goals. We feel threatened by the idea that the answers to the questions we should be asking may prevent us from moving forward, so we don’t ask them. Or worse, we ask the questions but don’t listen to the answers. It’s self-deception in the worst way, and it’s an entrepreneur’s Achilles’ heel. It feels better to move forward blindly than to search out whatever hurdles may be in the way.

But closing your eyes doesn’t make monsters go away. The answers exist, whether you want to face them or not. There are thousands of examples of this, but let me share one of mine:

A startup by any other name?

My cofounder and I started our loyalty marketing business, CityGro, five years ago. CityGro’s original name was BlueCache, which we thought was clever for a business started by “true blue” Aggies (Utah State University) from Cache Valley, Utah.

It wasn’t more than a few weeks after we launched that a client paid for their “BlueCache” service with an American Express “BlueCash” credit card. I remember my gut telling me that this was going to cause problems, but I had a number of ways to excuse the severity of it in my mind.

“We’re an unrelated business,” I thought. “We spell it differently, and we can prove its originality.” Ignoring my intuition, I went ahead.

Long story short, a year later we received a cease and desist letter from AMEX and had to spend thousands of dollars rebranding. Had I done a five-minute Google search beforehand, I would have quickly found that naming my business BlueCache was a terrible idea.

5 questions you should ask about any idea

I now live by the rule of “Goo-diligence.” Whenever have a new idea or am asked for feedback on someone else’s, I won’t move forward without a quick search on Google. I hate to say it, but many of my “great ideas” have stopped before they ever started because of things I’ve found in less than five minutes. On the other hand, this research period has also helped me refine my ideas so they become even greater.

So as you start Googling (or using whatever search engine you prefer), here are five questions you might ask yourself. And, please, try to be honest about the answers:

1. Is there really a need for my solution? This question requires brutal honesty. It’s the easiest question on the list to justify. Start by Googling related terms and see if people are talking about the subject. Find out if there is a market of people that would be willing to pay for your solution.

2. Does my solution already exist? Assuming there is a market, how are people currently solving the problem? I’ve learned to love analyzing competition, because it has sparked some of our greatest ideas.

3. Is my solution disruptive? If the market exists and there are other solutions out there (which is typically the case if you have a large market), you may still have a business if your idea is disruptive. There are great books written about disruption, but to summarize, you can be disruptive by introducing a similar product at a much lower cost OR by offering a much better solution that saves time, effort, etc. (Try reading The Innovator’s Solution by Clayton Christensen if you’re looking for more info on this.)

4. Is the name I’ve chosen available? As mentioned above, this one got me personally. Make sure you search several different versions of the spelling, check URLs, and consider any pre-designated connotations that may be associated with the name your choosing.

5. What other solutions would I use? This is a close relative to #2 but can’t be emphasized enough. Force yourself to see what else is out there and don’t jump into the ring without knowing who you are up against.

If you do your due diligence with these questions in mind, and can pass favorably on each one, chances are you have a great idea.

If not, before you lose a lot of money, you may want to stop or take a new twist on your idea.

Jon Parrish is the founder and CEO of CityGro, a loyalty marketing company that allows businesses of all sizes to connect with their customers. He lives in Salt Lake City with his family and enjoys snowmobiling, RockStar Energy drinks, and cheering for the Jazz. Connect on Twitter @CityGro.

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