- P Values are not Error Probabilities (PDF) — In particular, we illustrate how this mixing of statistical testing methodologies has resulted in widespread confusion over the interpretation of p values (evidential measures) and α levels (measures of error). We demonstrate that this confusion was a problem between the Fisherian and Neyman–Pearson camps, is not uncommon among statisticians, is prevalent in statistics textbooks, and is well nigh universal in the pages of leading (marketing) journals. This mass confusion, in turn, has rendered applications of classical statistical testing all but meaningless among applied researchers.
- Breaking the 1000ms Time to Glass Mobile Barrier (YouTube) —
See also slides. Stay under 250 ms to feel “fast.” Stay under 1000 ms to keep users’ attention.
- Modern Methods for Sentiment Analysis — Recently, Google developed a method called Word2Vec that captures the context of words, while at the same time reducing the size of the data. Gentle introduction, with code.
An introduction to multi-level caching.
Since a content delivery network (CDN) is essentially a cache, you might be tempted not to make use of the cache in the browser, to avoid complexity. However, each cache has its own advantages that the other does not provide. In this post I will explain what the advantages of each are, and how to combine the two for the most optimal performance of your website.
Why use both?
While CDNs do a good job of delivering assets very quickly, they can’t do much about users who are out in the boonies and barely have a single bar of reception on their phone. As a matter of fact, in the US, the 95th percentile for the round trip time (RTT) to all CDNs is well in excess of 200 milliseconds, according to Cedexis reports. That means at least 5% of your users, if not more, are likely to have a slow experience with your website or application. For reference, the 50th percentile, or median, RTT is around 45 milliseconds.
So why bother using a CDN at all? Why not just rely on the browser cache?
Leveraging the power of emergence to balance flexibility with coherency.
Download a free copy of Building an Optimized Business, a curated collection of chapters from the O’Reilly Web Operations and Performance library. This post is an excerpt by Jeff Sussna from Designing Delivery, one of the selections included in the curated collection.
In 1973, Daniel Bell published a book called “The Coming of Post-Industrial Society”. In it, he posited a seismic shift away from industrialism towards a new socioeconomic structure which he named ‘post-industrialism’. Bell identified four key transformations that he believed would characterize the emergence of post-industrial society:
- Service would replace products as the primary driver of economic activity
- Work would rely on knowledge and creativity rather than bureaucracy or manual labor
- Corporations, which had previously strived for stability and continuity, would discover change and innovation as their underlying purpose
- These three transformations would all depend on the pervasive infusion of computerization into business and daily life
If Bell’s description of the transition from industrialism to post-industrialism sounds eerily familiar, it should. We are just now living through its fruition. Every day we hear proclamations touting the arrival of the service economy. Service sector employment has outstripped product sector employment throughout the developed world. 1
Companies are recognizing the importance of the customer experience. Drinking coffee has become as much about the bar and the barista as about the coffee itself. Owning a car has become as much about having it serviced as about driving it. New disciplines such as service design are emerging that use design techniques to improve customer satisfaction throughout the service experience.
Using Docker Machine to create a Swarm cluster across cloud providers.
You understand how to create a Swarm cluster manually (see Recipe 7.3), but you would like to create one with nodes in multiple public Cloud Providers and keep the UX experience of the local Docker CLI.
Use Docker Machine to start Docker hosts in several Cloud providers and bootstrap them automatically to create a swarm cluster.
Why DevOps needs a manifesto after all, but may never get one.
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.