Andy Oram

Andy Oram is an editor at O'Reilly Media. An employee of the company since 1992, Andy currently specializes in open source technologies and software engineering. His work for O'Reilly includes the first books ever released by a U.S. publisher on Linux, the 2001 title Peer-to-Peer, and the 2007 best-seller Beautiful Code.

How did we end up with a centralized Internet for the NSA to mine?

The Internet is naturally decentralized, but it's distorted by business considerations.

I’m sure it was a Wired editor, and not the author Steven Levy, who assigned the title “How the NSA Almost Killed the Internet” to yesterday’s fine article about the pressures on large social networking sites. Whoever chose the title, it’s justifiably grandiose because to many people, yes, companies such as Facebook and Google constitute what they know as the Internet. (The article also discusses threats to divide the Internet infrastructure into national segments, which I’ll touch on later.)

So my question today is: How did we get such industry concentration? Why is a network famously based on distributed processing, routing, and peer connections characterized now by a few choke points that the NSA can skim at its leisure?
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Security firms must retool as clients move to the cloud

The risk of disintermediation meets a promise of collaboration.

This should be flush times for firms selling security solutions, such as Symantec, McAfee, Trend Micro, and RSA. Front-page news about cyber attacks provides free advertising, and security capabilities swell with new techniques such as security analysis (permit me a plug here for our book Network Security Through Data Analysis). But according to Jane Wright, senior analyst covering security at Technology Business Research, security vendors are faced with an existential threat as clients run their applications in the cloud and rely on their cloud service providers for their security controls.
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Who will upgrade the telecom foundation of the Internet?

A conference report on the IP transition.

Although readers of this blog know quite well the role that the Internet can play in our lives, we may forget that its most promising contributions — telemedicine, the smart electrical grid, distance education, etc. — depend on a rock-solid and speedy telecommunications network, and therefore that relatively few people can actually take advantage of the shining future the Internet offers.

Worries over sputtering advances in bandwidth in the US, as well as an actual drop in reliability, spurred the FCC to create the Technology Transitions Policy Task Force, and to drive discussion of what they like to call the “IP transition”.

Last week, I attended a conference on the IP transition in Boston, one of a series being held around the country. While we tussled with the problems of reliability and competition, one urgent question loomed over the conference: who will actually make advances happen?
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23andMe flap at FDA indicates fundamental dilemma in health reform

We must go beyond hype for incentives to provide data to researchers

The FDA order stopping 23andM3 from offering its genetic test kit strikes right into the heart of the major issue in health care reform: the tension between individual care and collective benefit. Health is not an individual matter. As I will show, we need each other. And beyond narrow regulatory questions, the 23andMe issue opens up the whole goal of information sharing and the funding of health care reform.

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The new stage of system monitoring is better integrated

Current tools make collection and visualization easier but don't reduce work

New tools are raining down on system administrators these days, attacking the “monitoring sucks” theme that was pervasive just a year ago. The new tools–both open source and commercial–may be more flexible and lightweight than earlier ones, as well as more suited for the kaleidoscopic churn of servers in the cloud, making it easier to log events and visualize them. But I look for more: a new level of data integration. What if the monitoring tools for different components could send messages to each other and take over from the administrator the job of tracing causes for events?

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Geographic data is the glue for public health and treatment

Esri conference highlights uses of GIS data

We’ve all seen cool maps of health data, such as these representations of diabetes prevalence by US county. But few people think about how thoroughly geospacial data is transforming public health and changing the allocation of resources at individual hospitals. I got a peek into this world at the Esri Health GIS Conference this week in Cambridge, Mass.

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OpenStack release offers more flexibility and aids to performance

The Havana release features metering and orchestration

I talked this week to Jonathan Bryce and Mark Collier of OpenStack to look at the motivations behind the enhancements in the Havana release announced today. We focused on the main event–official support for the Ceilometer metering/monitoring project and the Heat orchestration project–but covered a few small bullet items as well.

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Where are the chances for change in health care – top-down or bottom-up?

Impressions from Strata Rx bolster different philosophies

Everyone seems to agree that health care is the next big industry waiting to be disrupted. But who will force that change on a massive system full of conservative players? Three possibilities present themselves:

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Ticking all the boxes for a health care upgrade at Strata Rx

What is needed for successful reform of the health care system?

Here’s what we all know: that a data-rich health care future is coming our way. And what it will look like, in large outlines. Health care reformers have learned that no single practice will improve the system. All of the following, which were discussed at O’Reilly’s recent Strata Rx conference, must fall in place.

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Building the Brain of Dr. Algorithm

Archimedes advances evidence-based medicine to foster model-based medicine

This posting is by guest author Tuan Dinh, who will speak about this topic at the Strata Rx conference.

Legendary Silicon Valley investor Vinod Khosla caused quite a stir last year when he predicted at Strata Rx that “Dr. Algorithm”–artificial intelligence driven by large data sets and computational power–would replace doctors in the not-too-distant future. At that point, he said, technology will be cheaper, more accurate and objective, and will ultimately do a better job than the average human doctor at delivering routine diagnoses with standard treatments.

I not only support Khosla’s provocative prophecy, I’ll add one of my own: that Dr. Algorithm (aka Dr. A) will “come to life” in three to five years, by the time today’s first-year med school students are pulling 30-hour shifts as new interns. But what will it take to build the brain of Dr. A? And how can we teach Dr. A to account for increasingly complex medical inputs, such as laboratory tests results, genomic/genetic information, family and personal history, co-morbidities and patient preferences, so he can make optimal clinical decisions for living, breathing patients?

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