- Using Monitoring Dashboards to Change Behaviour — [After years of neglect] One day we wrote some brittle Ruby scripts that polled various services. They collated the metrics into a simple database and we automated some email reports and built a dashboard showing key service metrics. We pinpointed issues that we wanted to show people. Things like the login times, how long it would take to search for certain keywords in the app, and how many users were actually using the service, along with costs and other interesting facts. We sent out the link to the dashboard at 9am on Monday morning, before the weekly management call. Within 2 weeks most problems were addressed. It is very difficult to combat data, especially when it is laid out in an easy to understand way.
- Quiet Mitsubishi Cars — noise-cancelling on phone calls by using machine learning to build the filters.
- NSF Requiring Public Access — NSF will require that articles in peer-reviewed scholarly journals and papers in juried conference proceedings or transactions be deposited in a public access compliant repository and be available for download, reading, and analysis within one year of publication.
- Filtered for Capital (Matt Webb) — It’s important to get a credit line [for hardware startups] because growing organically isn’t possible — even if half your sell-in price is margin, you can only afford to grow your batch size at 50% per cycle… and whether it’s credit or re-investing the margin, all that growth incurs risk, because the items aren’t pre-sold. There are double binds all over the place here.
"devops" entries
Four short links: 19 March 2015
Changing Behaviour, Building Filters, Public Access, and Working Capital
Worship maintainers
The future is maintenance: build for the inevitable.
Technology has had a cult of newness for centuries. We hail innovators, cheer change, and fend off critics who might think new and change are coming too fast. Unfortunately, while that drives the cycle of creation, it also creates biases that damage what we create, reducing the benefits and increasing the costs.
Formerly new things rapidly become ordinary “plumbing,” while maintenance becomes a cost center, something to complain about. “Green fields” and startups look ever more attractive because they offer opportunities to start fresh, with minimal connections to past technology decisions.
The problem, though, is that most of these new things — the ones that succeed enough to stay around — have a long maintenance cycle ahead of them. As Axel Rauschmayer put it:
“People who maintain stuff are the unsung heroes of software development.”
In a different context, Steve Hendricks of Historic Doors pointed out that:
“Low maintenance is the holy grail of our culture. We’ve gone so far that we’re willing to throw things away rather than fix them.”
That gets especially expensive. Heaping praise on the creators of new things while trying to minimize the costs of the maintainers is a recipe for disaster over the long term.
Read more…
Four short links: 17 March 2015
Open Source Personal Assistant, Flintstoning Robots, Year of Personal Assistants, and Infrastructure Curiosity
- Sirius — UMich open source “intelligent Personal Assistant” (aka Siri, Cortana, Google Now, etc.). Text recognition, image recognition, query processing components. They hope it’ll be a focal point for research in the area, the way that open source operating systems have focused university research.
- MIT DragonBot Evolving to Teach Kids (IEEE Spectrum) — they’re moving from “Wizard of Oz” (humans-behind-the-scenes) control to autonomous operation. Lovely example of Flintstoning in a robotics context.
- Personal Assistants Coming (Robohub) — 2015 is the year physical products will be coming to market and available for experimentation and testing. Pepper ships in the summer in Japan, JIBO ships preorders in Q3, as does Cubic in the fall and EmoSpark in the summer. […]The key to the outcome of this race is whether a general purpose AI will be able to steer people through their digital world, or whether users would rather navigate to applications that are specialists (such as American Airlines or Dominos Pizza).
- Incuriosity Killed the Infrastructure — being actively curious about “fishy” things will lead to a more stable and happy infrastructure.
Four short links: 27 February 2015
No Estimates, Brand Advertising, Artificial Intelligence, and GPG BeGone
- #NoEstimates — Allspaw also points out that the yearning to break the bonds of estimation is nothing new — he’s fond of quoting a passage from The Unwritten Laws of Engineering, a 1944 manual which says that engineers “habitually try to dodge the irksome responsibility for making commitments.” All of Allspaw’s segment is genius.
- Old Fashioned Snapchat — get a few drinks in any brand advertiser and they’ll admit that the number one reason they know that brand advertising works is that, if they stop, sales inevitably drop.
- Q&A With Bruce Sterling on Artificial Intelligence — in which Sterling sounds intelligent, and the questioner sounds Artificial.
- GPG and Me (Moxie Marlinspike) — Even though GPG has been around for almost 20 years, there are only ~50,000 keys in the “strong set,” and less than 4 million keys have ever been published to the SKS keyserver pool ever. By today’s standards, that’s a shockingly small user base for a month of activity, much less 20 years. This was a great talk at Webstock this year.
Four short links: 26 February 2015
Autocompletion, Colliding Trends, Microservices, and Writing Useful Code
- awesomplete — MIT-licensed ultra lightweight, usable, beautiful autocomplete with zero dependencies in Javascript.
- How to Seize the Opportunities when Megatrends Collide — excuse the cheesy title, the chart from PwC showing pairwise combination of trends, is interesting.
- Adopting Microservices at Netflix: Lessons for Architectural Design — you want to think of servers like cattle, not pets. If you have a machine in production that performs a specialized function, and you know it by name, and everyone gets sad when it goes down, it’s a pet. Instead you should think of your servers like a herd of cows. What you care about is how many gallons of milk you get. If one day you notice you’re getting less milk than usual, you find out which cows aren’t producing well and replace them. People for Ethical Treatment of Iron, your time has come!
- Your Job is Not to Write Code (Laura Klein) — I know what you’re thinking. This will all take so long! I’ll be so much less effective! This isn’t true. You’ll be far more effective because you will actually be doing your job. Amen to it all.
Four short links: 20 February 2015
Robotic Garden, Kids Toys, MSFT ML, and Twitter Scale
- The Distributed Robotic Garden (MIT) — We consider plants, pots, and robots to be systems with different levels of mobility, sensing, actuation, and autonomy. (via Robohub)
- CogniToys Leverages Watson’s Brain to Befriend, Teach Your Kids (IEEE) — Through the dino, Watson’s algorithms can get to know each child that it interacts with, tailoring those interactions to the child’s age and interests.
- How Machine Learning Ate Microsoft (Infoworld) — Azure ML didn’t merely take the machine learning algorithms MSR had already handed over to product teams and stick them into a drag-and-drop visual designer. Microsoft has made the functionality available to developers who know the R statistical programming language and Python, which together are widely used in academic machine learning. Microsoft plans to integrate Azure ML closely with Revolution Analytics, the R startup it recently acquired.
- Handling Five Billion Sessions a Day in Real Time (Twitter) — infrastructure porn.
Elvis has left the ivory tower
Pragmatism now rules in team structure, technology, engineering practices, and operational innovation.
Ancient history in computer science (2004) provides a gem about the personas that Microsoft envisioned as users of the development environment Visual Studio. They developed three:
- Mort, the opportunistic developer, likes to create quick-working solutions for immediate problems. He focuses on productivity and learns as needed.
- Elvis, the pragmatic programmer, likes to create long-lasting solutions addressing the problem domain, and learning while working on the solution.
- Einstein, the paranoid programmer, likes to create the most efficient solution to a given problem and typically learns in advance before working on the solution.
These designations received a lot of negative press, particularly around the Mort persona, but I want to focus on Einstein and Elvis.
Formerly, software architects exemplified the Einstein persona: isolated from day-to-day development details, focused on building abstractions and frameworks. The isolation is so common that it spawned its own “Ivory Tower Architect” derogatory phrase. But the realities of building systems that scale as fast as the business does invalidates that approach. Now, Elvis, the pragmatic developer, has ascended to architect while simultaneously descending from the Ivory Tower. Modern architects don’t have the luxury of isolation from the gritty realities of software development today. Pragmatism now rules in team structure, technology, engineering practices, and operational innovation because:
What is DevOps (yet again)?
Empathy, communication, and collaboration across organizational boundaries.
I might try to define DevOps as the movement that doesn’t want to be defined. Or as the movement that wants to evade the inevitable cargo-culting that goes with most technical movements. Or the non-movement that’s resisting becoming a movement. I’ve written enough about “what is DevOps” that I should probably be given an honorary doctorate in DevOps Studies.
Baron Schwartz (among others) thinks it’s high time to have a definition, and that only a definition will save DevOps from an identity crisis. Without a definition, it’s subject to the whims of individual interest groups, and ultimately might become a movement that’s defined by nothing more than the desire to “not be like them.” Dave Zwieback (among others) says that the lack of a definition is more of a blessing than a curse, because it “continues to be an open conversation about making our organizations better.” Both have good points. Is it possible to frame DevOps in a way that preserves the openness of the conversation, while giving it some definition? I think so.
DevOps started as an attempt to think long and hard about the realities of running a modern web site, a problem that has only gotten more difficult over the years. How do we build and maintain critical sites that are increasingly complex, have stringent requirements for performance and uptime, and support thousands or millions of users? How do we avoid the “throw it over the wall” mentality, in which an operations team gets the fallout of the development teams’ bugs? How do we involve developers in maintenance without compromising their ability to release new software?
Four short links: 27 January 2015
Autonomous Corporations, Abstract Thought, Down Rounds, and Distributed Messaging
- Decentralised Autonomous Corporations — Charlie Stross’s near-future fiction of Accelerando comes closer to reality: Malice – revenge for waking him up – sharpens Manfred’s voice. “The president of agalmic.holdings.root.184.97.AB5 is agalmic.holdings.root.184.97.201. The secretary is agalmic.holdings.root.184.D5, and the chair is agalmic.holdings.root.184.E8.FF. All the shares are owned by those companies in equal measure, and I can tell you that their regulations are written in Python. Have a nice day, now!” He thumps the bedside phone control and sits up, yawning, then pushes the do-not-disturb button before it can interrupt again. After a moment he stands up and stretches, then heads to the bathroom to brush his teeth, comb his hair, and figure out where the lawsuit originated and how a human being managed to get far enough through his web of robot companies to bug him.
- Coding is Not the New Literacy (Chris Grainger) — We build mental models of everything – from how to tie our shoes to the way macro-economic systems work. With these, we make decisions, predictions, and understand our experiences. If we want computers to be able to compute for us, then we have to accurately extract these models from our heads and record them. Writing Python isn’t the fundamental skill we need to teach people. Modeling systems is. Amen!
- Let’s Stop Laughing at Groupon (Fortune) — it is much easier to survive a valuation decline as a public company than as a private one.
- nsq — Bitly’s open sourced realtime distributed messaging platform.
Four short links: 22 January 2015
MSVR, The Facebook, Social Robots, and Testing Microservices
- Microsoft HoloLens Goggles (Wired) — a media release about the next thing from the person behind Kinect. I’m still trying to figure out (as are investors, I’m sure) where in the hype curve this Googles/AR/etc. amalgam lives. Is it only a tech proof-of-concept? Is it a games device like Kinect? Is it good and cheap enough for industrial apps? Or is this the long-awaited climb out of irrelevance for Virtual Reality?
- The Facebook (YouTube) — brilliant fake 1995 ad for The Facebook. Excuse me, I’m off to cleanse.
- Natural Language in Social Robotics (Robohub) — Natural language interfaces are turning into a de-facto interface convention. Just like the GUI overlapped and largely replaced the command line, NLP is now being used by robots, the Internet of things, wearables, and especially conversational systems like Apple’s Siri, Google’s Now, Microsoft’s Cortana, Nuance’s Nina, Amazon’s Echo and others. These interfaces are designed to simplify, speed up, and improve task completion. Natural language interaction with robots, if anything, is an interface. It’s a form of UX that requires design.
- Microservices and Testing (Martin Fowler) — testing across component boundaries, in the face of failing data stores and HTTP timeouts. The first discussion of testing in a web-scale world that I’ve seen from The Mainstream.