Amazon

Time for Net Giants to Pay Fairly for the Open Source on Which They Depend

Glyn Moody — Mon, 05 Nov 2018 13:00:00 +0000

Net giants depend on open source: so where's the gratitude?

Licensing lies at the heart of open source. Arguably, free software began with the publication of the GNU GPL in 1989. And since then, open-source projects are defined as such by virtue of the licenses they adopt and whether the latter meet the Open Source Definition. The continuing importance of licensing is shown by the periodic flame wars that erupt in this area. Recently, there have been two such flarings of strong feelings, both of which raise important issues.

First, we had the incident with Lerna, "a tool for managing JavaScript projects with multiple packages". It came about as a result of the way the US Immigration and Customs Enforcement (ICE) has been separating families and holding children in cage-like cells. The Lerna core team was appalled by this behavior and wished to do something concrete in response. As a result, it added an extra clause to the MIT license, which forbade a list of companies, including Microsoft, Palantir, Amazon, Motorola and Dell, from being permitted to use the code:

For the companies that are known supporters of ICE: Lerna will no longer be licensed as MIT for you. You will receive no licensing rights and any use of Lerna will be considered theft. You will not be able to pay for a license, the only way that it is going to change is by you publicly tearing up your contracts with ICE.

Many sympathized with the feelings about the actions of the ICE and the intent of the license change. However, many also pointed out that such a move went against the core principles of both free software and open source. Freedom 0 of the Free Software Definition is "The freedom to run the program as you wish, for any purpose." Similarly, the Open Source Definition requires "No Discrimination Against Persons or Groups" and "No Discrimination Against Fields of Endeavor". The situation is clear cut, and it didn't take long for the Lerna team to realize their error, and they soon reverted the change:

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CloudWatch Is of the Devil, but I Must Use It

Corey Quinn — Wed, 31 Oct 2018 11:30:00 +0000

by Corey Quinn

Let's talk about Amazon CloudWatch.

For those fortunate enough to not be stuck in the weeds of Amazon Web Services (AWS), CloudWatch is, and I quote from the official AWS description, "a monitoring and management service built for developers, system operators, site reliability engineers (SRE), and IT managers." This is all well and good, except for the part where there isn't a single named constituency who enjoys working with the product. Allow me to dispense some monitoring heresy.

Better, let me describe this in the context of the 14 Amazon Leadership Principles that reportedly guide every decision Amazon makes. When you take a hard look at CloudWatch's complete failure across all 14 Leadership Principles, you wonder how this product ever made it out the door in its current state.

"Frugality"

I'll start with billing. Normally left for the tail end of articles like this, the CloudWatch billing paradigm is so terrible, I'm leading with it instead. You get billed per metric, per month. You get billed per thousand metrics you request to view via the API. You get billed per dashboard per month. You get billed per alarm per month. You get charged for logs based upon data volume ingested, data volume stored and "vended logs" that get published natively by AWS services on behalf of the customer. And, you get billed per custom event. All of this can be summed up best as "nobody on the planet understands how your CloudWatch metrics and logs get billed", and it leads to scenarios where monitoring vendors can inadvertently cost you thousands of dollars by polling CloudWatch too frequently. When the AWS charges are larger than what you're paying your monitoring vendor, it's not a wonderful feeling.

"Invent and Simplify"

CloudWatch Logs, CloudWatch Events, Custom Metrics, Vended Logs and Custom Dashboards all mean different things internally to CloudWatch from what you'd expect, compared to metrics solutions that actually make some fathomable level of sense. There are, thus, multiple services that do very different things, all operating under the "CloudWatch" moniker. For example, it's not particularly intuitive to most people that scheduling a Lambda function to invoke once an hour requires a custom CloudWatch Event. It feels overly complicated, incredibly confusing, and very quickly, you find yourself in a situation where you're having to build complex relationships to monitor things that are themselves far simpler.

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Shall We Study Amazon's Pricing Together?

Doc Searls — Tue, 02 Oct 2018 11:30:00 +0000

by Doc Searls

Is it possible to figure out how we're being profiled online?

This past July, I spent a quality week getting rained out in a series of brainstorms by alpha data geeks at the Pacific Northwest BI & Analytics Summit in Rogue River, Oregon. Among the many things I failed to understand fully there was how much, or how well, we could know about how the commercial sites and services of the online world deal with us, based on what they gather about us, on the fly or over time, as we interact with them.

The short answer was "not much". But none of the experts I talked to said "Don't bother trying." On the contrary, the consensus was that the sums of data gathered by most companies are (in the words of one expert) "spaghetti balls" that are hard, if not possible, to unravel completely. More to my mission in life and work, they said it wouldn't hurt to have humans take some interest in the subject.

In fact, that was pretty much why I was invited there, as a Special Guest. My topic was "When customers are in full command of what companies do with their data—and data about them". As it says at that link, "The end of this story...is a new beginning for business, in a world where customers are fully in charge of their lives in the marketplace—both online and off: a world that was implicit in both the peer-to-peer design of the Internet and the nature of public markets in the pre-industrial world."

Obviously, this hasn't happened yet.

This became even more obvious during a break when I drove to our AirBnB nearby. By chance, my rental car radio was tuned to a program called From Scurvy to Surgery: The History Of Randomized Trials. It was an Innovation Hub interview with Andrew Leigh, Ph.D. (@ALeighMP), economist and member of the Australian Parliament, discussing his new book, Randomistas: How Radical Researchers Are Changing Our World (Yale University Press, 2018). At one point, Leigh reported that "One expert says, 'Every pixel on Amazon's home page has had to justify its existence through a randomized trial.'"

I thought, Wow. How much of my own experience of Amazon has been as a randomized test subject? And can I possibly be in anything even remotely close to full charge of my own life inside Amazon's vast silo?

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What Does "Ethical" AI Mean for Open Source?

Glyn Moody — Mon, 20 Aug 2018 11:30:00 +0000

by Glyn Moody

Artificial intelligence is a threat—and an opportunity—for open source.

It would be an understatement to say that artificial intelligence (AI) is much in the news these days. It's widely viewed as likely to usher in the next big step-change in computing, but a recent interesting development in the field has particular implications for open source. It concerns the rise of "ethical" AI.

In October 2016, the White House Office of Science and Technology Policy, the European Parliament's Committee on Legal Affairs and, in the UK, the House of Commons' Science and Technology Committee, all released reports on how to prepare for the future of AI, with ethical issues being an important component of those reports. At the beginning of last year, the Asilomar AI Principles were published, followed by the Montreal Declaration for a Responsible Development of Artificial Intelligence, announced in November 2017.

Abstract discussions of what ethical AI might or should mean became very real in March 2018. It was revealed then that Google had won a share of the contract for the Pentagon's Project Maven, which uses artificial intelligence to interpret huge quantities of video images collected by aerial drones in order to improve the targeting of subsequent drone strikes. When this became known, it caused a firestorm at Google. Thousands of people there signed an internal petition addressed to the company's CEO, Sundar Pichai, asking him to cancel the project. Hundreds of researchers and academics sent an open letter supporting them, and some Google employees resigned in protest.

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Leaving the Land of the Giants

Doc Searls — Tue, 05 Feb 2013 18:44:57 +0000

by Doc Searls

The next revolution will be personal. Just like the last three were.

The cover of the December 1st–7th 2012 issue of The Economist shows four giant squid battling each other (http://www.economist.com/printedition/2012-12-01). The headline reads, "Survival of the biggest: The internet's warring giants". The squid are Amazon, Apple, Facebook and Google. Inside, the story is filed under "Briefing: Technology giants at war". The headline below the title graphic reads, "Another game of thrones" (http://www.economist.com/news/21567361-google-apple-facebook-and-amazon-are-each-others-throats-all-sorts-ways-another-game). The opening slug line reads "Google, Apple, Facebook and Amazon are at each other's throats in all sorts of ways." (Raising the metaphor count to three.)

Now here's the question: Is that all that's going on? Is it not possible that, in five, ten or twenty years we'll realize that the action that mattered in the early twenty-teens was happening in the rest of the ocean, and not just among the mollusks with the biggest tentacles?

War stories are always interesting, and very easy to tell because the format is formulaic. Remember Linux vs. Microsoft, personalized as Linus vs. Bill? Never mind that Linux as a server OS worked from the start with countless millions (or even billions) of Windows clients. Or that both Linus and Bill had other fish to fry from the start. But personalization is cheap and easy, and there was enough antipathy on both sides to stoke the story-telling fires, so that's what we got. Thus, today we might regard Linux as a winner and Microsoft as a loser (or at least trending in that direction). The facts behind (or ignored by) the stories mostly say that both entities have succeeded or failed largely on their own merits.

Here's a story that illustrates how stories can both lead and mislead.

The time frame was the late 1980s and early 1990s, and the "war" was between CISC (Complex Instruction Set Computing, http://en.wikipedia.org/wiki/Complex_instruction_set_computing) and RISC (Reduced Instruction Set Computing, http://en.wikipedia.org/wiki/Reduced_instruction_set_computing). The popular CPUs at the time were CISC, and the big two CISC competitors were Intel's x86 and Motorola's 68000. Intel was winning that one, so Motorola and other chip makers pushed RISC as the Next Big Thing. Motorola had an early RISC lead with the 88000 (before later pivoting to the PowerPC).

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