January 2015 Archives

DevOps keeps it cool with ICE

How inclusivity, complexity, and empathy are shaping DevOps.

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Over the next five years, three ideas will be central to DevOps: the need for the DevOps community to become more Inclusive; the realization that increasing Complexity of systems is the underlying reason for DevOps; and the critical role of Empathy in the growth and adoption of DevOps. Channeling John Willis, I’ll coin my own DevOps acronym, ICE, which is shorthand for Inclusivity, Complexity, Empathy.

Inclusivity

There is a major expansion of the DevOps community underway, and it’s taking DevOps far beyond its roots in agile systems administration at “unicorn” companies (e.g., Etsy or Netflix). For instance, a significant majority (80-90%) of participants at the Ghent conference were first-time attendees, and this was also the case for many of the devopsdays in 2014 (NYC, Chicago, Minneapolis, Pittsburgh, and others). Moreover, although areas outside development and operations were still underrepresented, there was a more even split between developers and operations folks than at previous events. It’s also not an accident that the DevOps Enterprise conference took place the week prior to the fifth anniversary devopsdays and included talks about the DevOps journeys at large “traditional” organizations like Blackboard, Disney, GE, Macy’s, Nordstrom, Raytheon, Target, UK.gov, US DHS, and many others.

The DevOps community has always been open and inclusive, and that’s one of the reasons why in the five years since the word “DevOps” was coined, no single, widely accepted definition or practice has emerged. The lack of definition is more of a blessing than a curse, as DevOps continues to be an open conversation about ways of making our organizations better. Within the DevOps community, old-time practitioners and “newbies” have much to learn from each other.

Read more…

Announcing BioCoder issue 6

BioCoder 6: iGEM's first Giant Jamboree, an update from the #ScienceHack Hack-a-thon, the Open qPCR project, and more.

Today, we’ve released the 6th issue of BioCoder. There’s a lot of great content, including a report from iGEM’s first Giant Jamboree, and an update from the #ScienceHack Hack-a-thon. We’ve also got a report on the Open qPCR project, which reduces the cost of real-time PCR by a factor of 10, and an article about bringing microfluidics into the DIY lab. There’s nothing more disruptive than taking exotic and expensive techniques and putting them in the hands of experimenters.

Once again, we’re interested in your ideas and in new content, so if you have an article or a proposal for an article, send it in to BioCoder@oreilly.com. We’re very interested in what you’re doing. There are many, many fascinating projects that aren’t getting media attention. We’d like to shine some light on those. If you’re running one of them — or if you know of one, and would like to hear more about it — let us know. We’d also like to hear more about exciting start-ups. Who do you know that’s doing something amazing? And if it’s you, don’t be shy: tell us.

Above all, don’t hesitate to spread the word. BioCoder was meant to be shared. Our goal with BioCoder is to be the nervous system for a large and diverse but poorly connected community. We’re making progress, but we need you to help make the connections.

A brief look at data science’s past and future

In this O'Reilly Data Show Podcast: DJ Patil weighs in on a wide range of topics in data science and big data.

Back in 2008, when we were working on what became one of the first papers on big data technologies, one of our first visits was to LinkedIn’s new “data” team. Many of the members of that team went on to build interesting tools and products, and team manager DJ Patil emerged as one of the best-known data scientists. I recently sat down with Patil to talk about his new ebook (written with Hilary Mason) and other topics in data science and big data.

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Here are a few of the topics we touched on:

Proliferation of programs for training and certifying data scientists

Patil and I are both ex-academics who learned learned “data science” in industry. In fact, up until a few years ago one acquired data science skills via “on-the-job training.” But a new job title that catches on usually leads to an explosion of programs (I was around when master’s programs in financial engineering took off). Are these programs the right way to acquire the necessary skills? Read more…

Four short links: 15 January 2015

Four short links: 15 January 2015

Secure Docker Deployment, Devops Identity, Graph Processing, and Hadoop Alternative

  1. Docker Secure Deployment Guidelinesdeployment checklist for securely deploying Docker.
  2. The Devops Identity Crisis (Baron Schwartz) — I saw one framework-retailing bozo saying that devops was the art of ensuring there were no flaws in software. I didn’t know whether to cry or keep firing until the gun clicked.
  3. Apache Giraphan iterative graph processing system built for high scalability. For example, it is currently used at Facebook to analyze the social graph formed by users and their connections.
  4. Apache Flinka data processing system and an alternative to Hadoop’s MapReduce component. It comes with its own runtime, rather than building on top of MapReduce. As such, it can work completely independently of the Hadoop ecosystem. However, Flink can also access Hadoop’s distributed file system (HDFS) to read and write data, and Hadoop’s next-generation resource manager (YARN) to provision cluster resources. Since most Flink users are using Hadoop HDFS to store their data, we ship already the required libraries to access HDFS.

Security comes from evolution, not revolution

The O'Reilly Radar Podcast: Mike Belshe on making bitcoin secure and easy enough for the mainstream.

locks_Steven_Tom_Flickr

Editor’s note: you can subscribe to the O’Reilly Radar Podcast through iTunes, SoundCloud, or directly through our podcast’s RSS feed.

In this week’s O’Reilly Radar Podcast episode, I caught up with Mike Belshe, CTO and co-founder of BitGo, a company that has developed a multi-signature wallet that works with bitcoin. Belshe talks about about the security issues addressed by multi-signature wallets, how the technology works, and the challenges in bringing cryptocurrencies mainstream. We also talk about his journey into the bitcoin world, and he chimes in on what money will look like in the future. Belshe will address the topics of security and multi-signature technology at our upcoming Bitcoin & the Blockchain Radar Summit on January 27, 2015, in San Francisco — for more on the program and registration information, visit our Bitcoin & the Blockchain website.

Multi-signature technology is exactly what it sounds like: instead of authorizing bitcoin transactions with a single signature and a single key (the traditional method), it requires multiple signatures and/or multiple machines — and any combination thereof. The concept initially was developed as a solution for malware. Belshe explains:

“I’m fully convinced that the folks who have been writing various types of malware that steal fairly trivial identity information — logins and passwords that they sell super cheap — they are retooling their viruses, their scanners, their key loggers for bitcoin. We’ve seen evidence of that over the last 12 months, for sure. Without multi-signature, if you do a bitcoin transaction on a machine that’s got any of this bad stuff on it, you’re pretty much toast. Multi-signature was my hope to fix that. What we do is make one signature happen on the server machine, one signature happen on the client machine, your home machine. That way the attacker has to actually compromise two totally different systems in order to steal your bitcoin. That’s what multi-signature is about.”

Read more…

Four short links: 14 January 2015

Four short links: 14 January 2015

IoT and Govt, Exactly Once, Random Database Subset, and UX Checking

  1. Internet of Things: Blackett Review — the British Government’s review of Internet of Things opportunities around government. Government and others can use expert commissioning to encourage participants in demonstrator programmes to develop standards that facilitate interoperable and secure systems. Government as a large purchaser of IoT systems is going to have a big impact if it buys wisely. (via Matt Webb)
  2. Exactly Once Semantics with Kafka — designing for failure means it’s easier to ensure that things get done than it is to ensure that things get done exactly once.
  3. rdbms-subsetter — open source tool to generate a random sample of rows from a relational database that preserves referential integrity – so long as constraints are defined, all parent rows will exist for child rows. (via 18F)
  4. UXcheck — a browser extension to help you do a quick UX check against Nielsen’s 10 principles.

Fixing what’s wrong with hardware startups

Five pointers to increase the odds of engineering a great hardware startup.

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Attend Shahin Farshchi’s free webcast “5 Tools for Building Value Into Your Hardware Startups,” being held May 19 at 10 a.m. PT.

It is an amazing time to be a hardware entrepreneur: Companies like Arduino and ElectricImp are abstracting away tedious device and back-end development; Shapeways (disclaimer: my firm Lux Capital is an investor) and Advanced Circuits are turning around beautiful prototypes in days; while AngelList and IndieGogo are democratizing access to sophisticated investors, which in turn facilitate access to money, partners, and amazing talent.

In their rush to introduce the next Jawbone, Beats, Nest, FuelBand, GoPro, and Dropcam, many fledgling hardware startups — and their investors — seem to be simply rolling the dice. Rather than truly understanding the dynamics of their prospective markets, they are producing marketing videos that could otherwise pass for Super Bowl ads. Rather than understanding their competitive landscape, they are producing designs and out-of-box experiences that would make Steve Jobs proud. Many aspire to achieve Oculus’ visibility, and the acquisition offer that ensued. This puts incumbent consumer electronics companies in an enviable position: free market research and product experiments with an option to acquire any breakaway company. Although there is always an element of luck in every startup, here are a few pointers to increase the odds of success. Read more…

Products are now platforms

With remote connectivity and remote updates, companies are able to iterate and add value to products customers already own.

Editor’s note: this is an excerpt from our recent report, When Hardware Meets Software, by Mike Barlow. The report looks into the new hardware movement, telling its story through the people who are building it. For more stories on the evolving relationship between software and hardware, download the free report.

The Internet of Things doesn’t presage a return to the world of smoke-belching factories and floors covered with sawdust. But it does signify that change is afoot for any business or activity related to the information technology or communications industries.

“Not everyone will become a hardware designer,” says Joi Ito, director of the MIT Media Lab. But many students, software engineers, and entrepreneurs will see the advantages of learning how to work with hardware. “It’s never too late to learn this stuff,” says Ito, “if you decide that you want to do it.”

At minimum, software engineers should learn as much about design and manufacturing as possible. “Buy an Arduino and start building. Everything you need to learn is on the web,” urges Jordan Husney, an avid hardware hacker who serves as strategy director at Undercurrent, an organizational transformation firm and digital think tank in lower Manhattan.

In the same way that software people will have to reconfigure their modes of thinking, hardware people will need to learn new technical skills and new ways of looking at problems, says Husney. “They will have to become more comfortable with uncertainty occurring later and later in the process,” he says. “Hardware engineers will keep things in the realm of bits (as opposed to committing them to atoms) by sharing designs using digital collaboration and simulation tools virtually, while testing multiple physical prototypes. I think we’re going to see the supply chain start to shift around these concepts.” Read more…

The DevOps identity crisis

Why DevOps needs a manifesto after all, but may never get one.

Image: CC BY-SA 2.0 Libby Levi for opensource.com

DevOps is everywhere! The growth and mindshare of the movement is remarkable. But if you care deeply about DevOps, you might agree with me when I say that although its moment has “arrived,” DevOps is in serious trouble. The movement is fragmented and weakly defined, and is being usurped by those who care more about short-term opportunities than the long-term viability of DevOps.

They are the ninety-nine percent, and nobody cares

How bad could it be? Travel back in time. It is mid-November 2011, and Occupy Wall Street is occupying the headlines. One of the major reasons is that the protestors are targeting shipping ports on the West Coast, causing shutdowns and even violence. As things are getting out of hand, parts of the movement start condemning these actions as counter-productive, hurting the 99% instead of the intended 1%. Spokespeople for the movement are quoted in the media as saying the instigators “don’t represent the movement.”

Why did the Occupy movement become a footnote in history so fast? There were several reasons: there was no cohesive agreement on its identity, values, goals, and mission; in an effort to be unlike “them,” the OWS proponents avoided anything that looked like centralized leadership; and it seemed to be entirely negative, advocating nothing to replace what it wanted to remove.

I believe a similar thing is happening to DevOps right now, for many of the same reasons. Let’s talk about some of these problems.

Read more…

Four short links: 13 January 2015

Four short links: 13 January 2015

Slack Culture, Visualizations of Text Analysis, Wearables and Big Data, and Snooping on Keyboards

  1. Building the Workplace We Want (Slack) — culture is the manifestation of what your company values. What you reward, who you hire, how work is done, how decisions are made — all of these things are representations of the things you value and the culture you’ve wittingly or unwittingly created. Nice (in the sense of small, elegant) explanation of what they value at Slack.
  2. Interpretation and Trust: Designing Model-Driven Visualizations for Text Analysis (PDF) — Based on our experiences and a literature review, we distill a set of design recommendations and describe how they promote interpretable and trustworthy visual analysis tools.
  3. The Internet of Things Has Four Big Data Problems (Alistair Croll) — What the IoT needs is data. Big data and the IoT are two sides of the same coin. The IoT collects data from myriad sensors; that data is classified, organized, and used to make automated decisions; and the IoT, in turn, acts on it. It’s precisely this ever-accelerating feedback loop that makes the coin as a whole so compelling. Nowhere are the IoT’s data problems more obvious than with that darling of the connected tomorrow known as the wearable. Yet, few people seem to want to discuss these problems.
  4. Keysweepera stealthy Arduino-based device, camouflaged as a functioning USB wall charger, that wirelessly and passively sniffs, decrypts, logs, and reports back (over GSM) all keystrokes from any Microsoft wireless keyboard in the vicinity. Designs and demo videos included.