"management" entries

Signals from the O’Reilly Software Architecture Conference 2015

From careers to culture to code, here are key insights from the O'Reilly Software Architecture Conference 2015.

Experts from across the software architecture world came together in Boston for the O’Reilly Software Architecture Conference 2015. Below we’ve assembled notable keynotes, interviews, and insights from the event.

Software architects: post-“post-useful”

The old notion of a software architect being a non-coding, post-useful deep thinker is giving way to something far more interesting, says Neal Ford, software architect and meme wrangler at ThoughtWorks. “Architecture has become much more interesting now because it’s become more encompassing … it’s trying to solve real problems rather than play with abstractions.”

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Four short links: 18 March 2015

Moonshots, Decacorns, Leadership, and Deep Learning

1. How to Make Moonshots (Astro Teller) — Expecting a person to be a reliable backup for the [self-driving car] system was a fallacy. Once people trust the system, they trust it. Our success was itself a failure. We came quickly to the conclusion that we needed to make it clear to ourselves that the human was not a reliable backup — the car had to always be able to handle the situation. And the best way to make that clear was to design a car with no steering wheel — a car that could drive itself all of the time, from point A to point B, at the push of a button.
2. Billion-Dollar Math (Bloomberg) — There’s a new buzzword, “decacorn,” for those over $10 billion, which includes Airbnb, Dropbox, Pinterest, Snapchat, and Uber. It’s a made-up word based on a creature that doesn’t exist. “If you wake up in a room full of unicorns, you are dreaming,” Todd Dagres, a founding partner at Spark Capital, recently told Bloomberg News. Not just cute seeing our industry explained to the unwashed, but it’s the first time I’d seen decacorn. (The weather’s just dandy in my cave, thanks for asking). 3. What Impactful Engineering Leadership Looks Like — aside from the ugliness of “impactful,” notable for good advice. “When engineering management is done right, you’re focusing on three big things,” she says. “You’re directly supporting the people on your team; you’re managing execution and coordination across teams; and you’re stepping back to observe and evolve the broader organization and its processes as it grows.” 4. cxxnet“a fast, concise, distributed deep learning framework” that scales beyond a single GPU. Comment Four short links: 6 February 2015 Active Learning, Tongue Sensors, Cybernetic Management, and HTML5 Game Publishing 1. Real World Active Learningthe point at which algorithms fail is precisely where there’s an opportunity to insert human judgment to actively improve the algorithm’s performance. An O’Reilly report with CrowdFlower. 2. Hearing With Your Tongue (BoingBoing) — The tongue contains thousands of nerves, and the region of the brain that interprets touch sensations from the tongue is capable of decoding complicated information. “What we are trying to do is another form of sensory substitution,” Williams said. 3. The Art of Management — cybernetics and management. 4. kiwi.jsa mobile & desktop browser based HTML5 game framework. It uses CocoonJS for publishing to the AppStore. Comment: 1 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? Comments: 2 Four short links: 4 December 2014 Click to Captcha, Managing Hackers, Easy Ordering, and Inside Ad Auctions 1. One Click Captcha (Wired) — Google’s new Captcha tech is just a checkbox: “I am not a robot”. Instead of depending upon the traditional distorted word test, Google’s “reCaptcha” examines cues every user unwittingly provides: IP addresses and cookies provide evidence that the user is the same friendly human Google remembers from elsewhere on the Web. And Shet says even the tiny movements a user’s mouse makes as it hovers and approaches a checkbox can help reveal an automated bot. 2. The Responsive Enterprise: Embracing the Hacker Way (ACM) — Letting developers wander around without clear goals in the vastness of the software universe of all computable functions is one of the major reasons why projects fail, not because of lack of process or planning. I like all of this, although at times it can be a little like what I imagine it would be like if Cory Doctorow wrote a management textbook. (via Greg Linden) 3. Pizza Hut Tests Ordering via Eye-TrackingThe digital menu shows diners a canvas of 20 toppings and builds their pizza, from one of 4,896 combinations, based on which toppings they looked at longest. 4. How Browsers Get to Know You in Milliseconds (Andy Oram) — breaks down info exchange, data exchange, timing, even business relationships for ad auctions. Augment understanding of the user from third-party data (10 milliseconds). These third parties are the companies that accumulate information about our purchasing habits. The time allowed for them to return data is so short that they often can’t spare time for network transmission, and instead co-locate at the AppNexus server site. In fact, according to Magnusson, the founders of AppNexus created a cloud server before opening their exchange. Comment Four short links: 1 September 2014 Sibyl, Bitrot, Estimation, and ssh 1. Sibyl: Google’s System for Large Scale Machine Learning (YouTube) — keynote at DSN2014 acting as an intro to Sibyl. (via KD Nuggets) 2. Bitrot from 1997That’s 205 failures, an actual link rot figure of 91%, not 57%. That leaves only 21 URLs as 200 OK and containing effectively the same content. 3. What We Do And Don’t Know About Software Effort Estimation — nice rundown of research in the field. 4. fabric — simple yet powerful ssh library for Python. Comment: 1 Four short links: 26 June 2014 IoT Future, Latency Numbers, Mobile Performance, and Minimum Viable Bureaucracy 1. Charlie Stross on 2034every object in the real world is going to be providing a constant stream of metadata about its environment — and I mean every object. The frameworks used for channeling this firehose of environment data are going to be insecure and ramshackle, with foundations built on decades-old design errors. (via BoingBoing) 2. Latency Numbers Every Programmer Should Know — awesome animation so you can see how important “constants” which drive design decisions have changed over time. 3. Extreme Web Performance for Mobile Devices (Slideshare) — notes from Maximiliano Firtman’s Velocity tutorial. 4. Minimum Viable Bureaucracy (Laura Thomson) — notes from her Velocity talk. A portion of engineer’s time must be spent on what engineer thinks is important. It may be 100%. It may be 60%, 40%, 20%. But it should never be zero. Comment Everything is distributed How do we manage systems that are too large to understand, too complex to control, and that fail in unpredictable ways? “What is surprising is not that there are so many accidents. It is that there are so few. The thing that amazes you is not that your system goes down sometimes, it’s that it is up at all.”—Richard Cook In September 2007, Jean Bookout, 76, was driving her Toyota Camry down an unfamiliar road in Oklahoma, with her friend Barbara Schwarz seated next to her on the passenger side. Suddenly, the Camry began to accelerate on its own. Bookout tried hitting the brakes, applying the emergency brake, but the car continued to accelerate. The car eventually collided with an embankment, injuring Bookout and killing Schwarz. In a subsequent legal case, lawyers for Toyota pointed to the most common of culprits in these types of accidents: human error. “Sometimes people make mistakes while driving their cars,” one of the lawyers claimed. Bookout was older, the road was unfamiliar, these tragic things happen. Read more… Comments: 5 Four short links: 20 March 2014 Smart Objects, Crypto Course, Culture Design, and Security v Usability 1. Smart Interaction Lab — some interesting prototyping work designing for smart objects. 2. Crypto 101 — self-directory crypto instruction. (via BoingBoing) 3. Chipotle Culture — interesting piece on Chipotle’s approach to building positive feedback loops around training. Reminded me of Ben Horowitz’s “Why You Should Train Your People”. 4. Keybase.io Writeup (Tim Bray) — Tim’s right, that removing the centralised attack point creates a usability problem. Systems that are hardest to attack are also the ones that are hardest for Normal People to use. (Can I coin this as the Torkington Conjecture, with the corollary that sufficiently stupid users are indistinguishable from intelligent attackers?) Comment Four short links: 18 March 2014 On Managers, Human Data, Driverless Cars, and Bad Business 1. On Managers (Mike Migurski) — Managers might be difficult, hostile, or useless, but because they are parts of an explicit power structure they can be evaluated explicitly. 2. Big Data: Humans Required (Sherri Hammons) — the heart of the problem with data: interpretation. Data by itself is of little value. It is only when it is interpreted and understood that it begins to become information. GovTech recently wrote an article outlining why search engines will not likely replace actual people in the near future. If it were merely a question of pointing technology at the problem, we could all go home and wait for the Answer to Everything. But, data doesn’t happen that way. Data is very much like a computer: it will do just as it’s told. No more, no less. A human is required to really understand what data makes sense and what doesn’t. (via Anne Zelenka) 3. Morgan Stanley on the Economic Benefits of Driverless CarsThe total savings of over$5.6 trillion annually are not envisioned until a couple of decades as Morgan Stanley see four phases of adoption of self-driving vehicles. Phase 1 is already underway, Phase 2 will be semi-autonomous, Phase 3 will be within 5 to 10 years, by which time we will see fully self-driving vehicles on the roads – but not widespread usage. The authors say Phase 4, which will have the biggest impact, is when 100% of all vehicles on the roads will be fully autonomous, they say this may take a couple of decades.
4. Worse (Marco Arment) — I’ve been sitting on this but can’t fault it. In the last few years, Google, Apple, Amazon, Facebook, and Twitter have all made huge attempts to move into major parts of each others’ businesses, usually at the detriment of their customers or users.
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