- Army Cloud Computing Strategy (PDF) — aka: “what we hope to do without having done, to use what we’re doing to them.”
- Guide to Technical Development (Google) — This guide is a suggested path for university students to develop their technical skills academically and non-academically through self-paced, hands-on learning.
- Immutable Infrastructure is the Future (Michael DeHaan) — The future of configuration management systems is in deploying cloud infrastructure that will later run immutable systems via an API level.
- machinery — an asynchronous task queue/job queue based on distributed message passing.
"devops" entries
Four short links: 15 May 2015
Army Cloud, Google Curriculum, Immutable Infrastructure, and Task Queues
Four short links: 14 May 2015
Human-Machine Cooperation, Concurrent Systems Books, AI Future, and Gesture UI
- Ghosts in the Machines (Courtney Nash) — People are neither masters of machines, nor subservient to their machine-learning outcomes — we cannot, and should not, separate the two. We are actors, together, in a very complex system. David Woods calls this “joint cognitive systems.”
- TLA+ (Leslie Lamport) — two tutorials: “Principles of Concurrent Computing” and “Specification of Concurrent Systems.” Ironically, I see people grizzling that the book on distributed systems hasn’t been linearised. I wonder if you can partition it into the two tutorials and still have full availability…
- Deep Learning vs Probabilistic vs Logic — As of 2015, I pity the fool who prefers Modus Ponens over Gradient Descent.
- Touché (Disney Research) — measur[es] capacitive response of object and human at multiple frequencies, a technique that we called Swept Frequency Capacitive Sensing. The signal travels through different paths depending on its frequency, capturing the posture of human hand and body as well as other properties of the context. The resulted data is classified using machine learning algorithms to identify gestures that are then used to trigger desired responses of the user interface.
Four short links: 7 May 2015
Predicting Hits, Pricing Strategies, Quis Calculiet Shifty Custodes, Docker Security
- Predicting a Billboard Music Hit (YouTube) — Shazam VP of Music and Platforms at Strata London. With relative accuracy, we can predict 33 days out what song will go to No. 1 on the Billboard charts in the U.S.
- Psychological Pricing Strategies — a handy wrap-up of evil^wuseful pricing strategies to know.
- What Two Programmers Have Revealed So Far About Seattle Police Officers Who Are Still in Uniform — through their shrewd use of Washington’s Public Records Act, the two Seattle residents are now the closest thing the city has to a civilian police-oversight board. In the last year and a half, they have acquired hundreds of reports, videos, and 911 calls related to the Seattle Police Department’s internal investigations of officer misconduct between 2010 and 2013. And though they have only combed through a small portion of the data, they say they have found several instances of officers appearing to lie, use racist language, and use excessive force—with no consequences. In fact, they believe that the Office of Professional Accountability (OPA) has systematically “run interference” for cops. In the aforementioned cases of alleged officer misconduct, all of the involved officers were exonerated and still remain on the force.
- Understanding Docker Security and Best Practices — explanation of container security and a benchmark for security practices, though email addresses will need to be surrendered in exchange for the good info.
Four short links: 6 May 2015
Self-Driving Cars, Cloud BigTable, Define "Uptime," and Continuous Delivery Architectures
- Andrew Ng (Wired) — I think self-driving cars are a little further out than most people think. There’s a debate about which one of two universes we’re in. In the first universe it’s an incremental path to self-driving cars, meaning you have cruise control, adaptive cruise control, then self-driving cars only on the highways, and you keep adding stuff until 20 years from now you have a self-driving car. In universe two you have one organization, maybe Carnegie Mellon or Google, that invents a self-driving car and bam! You have self-driving cars. It wasn’t available Tuesday but it’s on sale on Wednesday. I’m in universe one. I think there’s a lot of confusion about how easy it is to do self-driving cars. There’s a big difference between being able to drive a thousand miles, versus being able to drive anywhere. And it turns out that machine-learning technology is good at pushing performance from 90 to 99 percent accuracy. But it’s challenging to get to four nines (99.99 percent). I’ll give you this: we’re firmly on our way to being safer than a drunk driver.
- Google Cloud BigTable — Google’s BigTable, with Apache HBase API, single-digit millisecond latency, and “fully managed”. G are hell-bent on catching up with Amazon and Microsoft at this cloud serving thing.
- Call Me Maybe: Aerospike — We’re setting a timeout of 500ms here, and operations still time out every time a partition between nodes occurs. In these tests we aren’t interfering with client-server traffic at all. Aerospike may claim “100% uptime”, but this is only meaningful with respect to particular latency bounds. Given Aerospike claims millisecond-scale latencies, you may want to reconsider whether you consider this “uptime”.
- 31 Continuous Delivery Architectures (Slideshare) — from a vendor, so one name crops up repeatedly (other than “Jenkins”), but it’s still good devops voyeurism/envy.
The two-sided coin of Web performance
Hacking performance across your organization.
I’ve given Web performance talks where I get to show one of my favorite slides with the impact of third-party dependencies on load time. It’s the perfect use case for “those marketing people,” who overload pages with the tracking pixels and tags that make page load time go south. This, of course, would fuel the late-night pub discussrion with fellow engineers about how much faster the Web would be if those marketing people would attend a basic Web performance 101 course.
I’ve also found myself discussing exactly this topic in a meeting. This time, however, I was the guy arguing to keep the tracking code, although I was well aware of the performance impact. So what happened?
Read more…
Chaos Monkey for systems of people: The ultimate performance hack
The O'Reilly Radar Podcast: Alois Reitbauer on performance hacking, DevOps applications, and fostering a culture of respect.
Subscribe to the O’Reilly Radar Podcast to track the technologies and people that will shape our world in the years to come.
In this week’s episode of the Radar Podcast, O’Reilly’s Courtney Nash chats with Alois Reitbauer, chief evangelist at Ruxit, about how DevOps is deeply woven into the Ruxit culture. Reitbauer also talks about how the term “performance hacking” came about at Ruxit, why Chaos Monkey should be applied to systems of people, and why trust across — and between — all departments in an organization is essential.
DevOps beyond DevOps
Performance hacking is a term that emerged at Ruxit about a year ago as the company prepared for the beta launch, Reitbauer said, when they realized as the company scaled up, they needed to bring everyone from all their teams together. “The idea of performance hacking, then,” he noted, “was really, how can we scale up this collaboration between the DevOps teams, the product development teams, and our go-to-market growth hacking teams while we grow as an organization.” The ultimate aim was to figure out how to continue to act like a three-person, one-room startup as the company scaled to a couple hundred people.
One of the approaches embraced at Ruxit is to apply some of the DevOps best practices to their growth hacking and product development strategies. As an example, Reitbauer offered up the idea of Chaos Monkey, as applied not to AWS instances, but to the organization as a whole. The way it works, he explained, is to send a member of a team — any team — away on short notice (or no notice) and see what breaks. Reitbauer said that they’d actually done this and outlined what they learned from the exercise:
We have done it, and it also came up as part of our regular organizational practices. Like, when we had our first very strong conference season — we sent people to different shows all over the place; we picked people from the team who had to go somewhere. And even if people knew they were going to be out of the office in a couple of weeks, they still started to behave as if they would be around all the time, that they wouldn’t be leaving the office. Then, suddenly they were on a plane. They had no time to do their everyday work, and suddenly they realized where they really needed help. So, you don’t even have to make it a total surprise. You just have to plan how to get people out of their regular working behavior to do something else. Then we were able to figure out, ‘We really need somebody else to be able to jump in here or to help somebody out over there.’ It might be a regular holiday or just not daily routine.
The Puppet design philosophy
Explore the declarative, idempotent, and stateless Puppet DSL.
It can be very easy to get started with Puppet, but scaling it effectively can be a challenge. In this early release excerpt from Puppet Best Practices, author Chris Barbour discusses the philosophy behind using Puppet effectively.
Read more…
Before we begin to explore practical best practices with Puppet, it’s valuable to understand the reasoning behind these recommendations.
Puppet can be somewhat alien to technologists who have a background in automation scripting. Where most of our scripts are procedural, Puppet is declarative. While a declarative language has many major advantages for configuration management, it does impose some interesting restrictions on the approaches we use to solve common problems.
Although Puppet’s design philosophy may not be the most exciting topic to begin this book, it drives many of the practices in the coming chapters. Understanding that philosophy will help contextualize many of the recommendations covered.
Four short links: 2 April 2015
250 Whys, Amazon Dash, Streaming Data, and Lightning Networks
- What I Learned from 250 Whys — Let’s Plan for a Future Where We’re All As Stupid as We Are Today.
- Thoughts on Amazon Dash (Matt Webb) — In a way, we’re really seeing the future of marketing here. We’ve separated awareness (advertising) and distribution (stores) for so long, but it’s no longer the way. When you get a Buy Now button in a Tweet, you’re seeing ads and distribution merging, and the Button is the physical instantiation of this same trend. […] in the future every product will carry a buy button.
- A Collection of Links for Streaming Algorithms and Data Structures — is this not the most self-evident title ever?
- Lightning Networks (Rusty Russell) — I finally took a second swing at understanding the Lightning Network paper. The promise of this work is exceptional: instant, reliable transactions across the bitcoin network. But the implementation is complex, and the draft paper reads like a grab bag of ideas; but it truly rewards close reading! It doesn’t involve novel crypto, nor fancy bitcoin scripting tricks. There are several techniques that are used in the paper, so I plan to concentrate on one per post and wrap up at the end. Already posted part II.
Four short links: 31 March 2015
Boring Technology, Psychology Memes, Engineering Ladder, and Flatpack Refugee Shelters
- Choose Boring Technology (Dan McKinley) — Adding technology to your company comes with a cost. As an abstract statement this is obvious: if we’re already using Ruby, adding Python to the mix doesn’t feel sensible because the resulting complexity would outweigh Python’s marginal utility. But somehow when we’re talking about Python and Scala or MySQL and Redis, people lose their minds, discard all constraints, and start raving about using the best tool for the job.
- Dunning-Kruger and Other Memes — a reality check on the popsci conception of some psych research.
- Sharing our Engineering Ladder — In addition to the ladder causing problems inside of my team, we were having a hard time evaluating candidates during interviews and determining what level to hire them into. Particularly at the more senior levels, it wasn’t clear what the criteria for success really looked like. So, together with my tech leads and engineering managers, we rewrote the ladder to be more specific. It has been very helpful both for the process of reviews and promotion committees as well as for the process of hiring.
- Ikea’s flat-pack refugee shelter is entering production (The Verge) — The UNHCR has agreed to buy 10,000 of the shelters, and will begin providing them to refugee families this summer. […] Measuring about 188 square feet, each shelter accommodates five people and includes a rooftop solar panel that powers a built-in lamp and USB outlet. The structure ships just like any other piece of Ikea furniture, with insulated, lightweight polymer panels, pipes, and wires packed into a cardboard box. According to Ikea, it only takes about four hours to assemble.
How the DevOps revolution informs software architecture
The O'Reilly Radar Podcast: Neal Ford on the changing role of software architects and the rise of microservices.
In this episode of the Radar Podcast, O’Reilly’s Mac Slocum sits down with Neal Ford, a software architect and meme wrangler at ThoughtWorks, to talk about the changing role of software architects. They met up at our recent Software Architecture Conference in Boston — if you missed the event, you can sign up to be notified when the Complete Video Compilation of all sessions and talks is available.
Slocum started the conversation with the basics: what, exactly, does a software architect do. Ford noted that there’s not a straightforward answer, but that the role really is a “pastiche” of development, soft skills and negotiation, and solving business domain problems. He acknowledged that the role historically has been negatively perceived as a non-coding, post-useful, ivory tower deep thinker, but noted that has been changing over the past five to 10 years as the role has evolved into real-world problem solving, as opposed to operating in abstractions:
“One of the problems in software, I think, is that you build everything on towers of abstractions, and so it’s very easy to get to the point where all you’re doing is playing with abstractions, and you don’t reify that back to the real world, and I think that’s the danger of this kind of ivory-tower architect. When you start looking at things like continuous delivery and continuous deployment, you have to take those operational concerns into account, and I think that is making the role of architect a lot more relevant now, because they are becoming much more involved in the entire software development ecosystem, not just the front edge of it.”