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Google is the dominant player in search, and has more data center capacity and servers than any one company providing information services.
With Google Search so much part our lives it is probably a good thing for you to understand how Google Search works.
There is all kinds of news on Facebook's IPO. Some have learned to be cautious of an IPO.
What some people don't get is the elite, the smart ones have figured out that being a private company is better than being public.
The Economist has an article on this topic. Here is an excerpt that will get you thinking.
Companies are like jets; the elite go private
Mr Zuckerberg will be joining a troubled club. The burden of regulation has grown heavier for public companies since the collapse of Enron in 2001. Corporate chiefs complain that the combination of fussy regulators and demanding money managers makes it impossible to focus on long-term growth. Shareholders are also angry. Their interests seldom seem to be properly aligned at public companies with those of the managers, who often waste squillions on empire-building and sumptuous perks. Shareholders are typically too dispersed to monitor the men on the spot. Attempts to solve the problem by giving managers shares have largely failed.
At the same time, alternative corporate forms are flourishing. Once “going public” was every CEO’s dream; now it is perfectly respectable to “go private”, like Burger King, Boots and countless other famous names. State-run enterprises have recovered from the wreck of communism and now include the world’s biggest mobile-phone company (China Mobile), its most successful port operator (Dubai World), its fastest-growing big airline (Emirates) and its 13 biggest oil companies.
To be a green data center you need a sustainable solution that reduces your environmental impact. This is complicated in itself figuring out the power grid, local weather conditions, and designing an efficient solution. What few talk about is the #1 thing that will cause the top guys to go from one state to another though are the taxes.
Mike Manos's posts on his observation on the pay to play game to get data centers to be in a state can backfire.
The Pay to Play that I am referring to is an emerging set of regulations and litigation techniques that require companies to pay tax bills upfront (without any kind of recourse or mediation) which then forces companies to litigate to try and recover those taxes if unfair. Increasingly I am seeing this in states where the budgets are challenged and governments are looking for additional funds and are targeting Internet based products and services.
If the state your data center is in not financially healthy then you could be in for a few surprises.
It does beg the question as to whether or not you have checked into the financial health of the States you may be hosting your data and services in. Have you looked at the risk that this may pose to your business? It may be something to take a look at!
WSJ has a post by Dan Ariely who has a new book.
The Honest Truth About Dishonesty: How We Lie to Everyone---Especially Ourselves [Hardcover]
Dan Ariely (Author)
I've pre-ordered the book. Why? I have read and watched Dan Ariely's works and he is on to some good issues that need to be addressed. The human factor of lying is something few think about, but it is human nature to lie.
Check out the WSJ article.
What we have found, in a nutshell: Everybody has the capacity to be dishonest, and almost everybody cheats—just by a little. Except for a few outliers at the top and bottom, the behavior of almost everyone is driven by two opposing motivations. On the one hand, we want to benefit from cheating and get as much money and glory as possible; on the other hand, we want to view ourselves as honest, honorable people. Sadly, it is this kind of small-scale mass cheating, not the high-profile cases, that is most corrosive to society.
Morales can help people take the path to honesty vs. dishonesty.
...my colleagues and I ran an experiment at the University of California, Los Angeles. We took a group of 450 participants, split them into two groups and set them loose on our usual matrix task. We asked half of them to recall the Ten Commandments and the other half to recall 10 books that they had read in high school. Among the group who recalled the 10 books, we saw the typical widespread but moderate cheating. But in the group that was asked to recall the Ten Commandments, we observed no cheating whatsoever. We reran the experiment, reminding students of their schools' honor codes instead of the Ten Commandments, and we got the same result. We even reran the experiment on a group of self-declared atheists, asking them to swear on a Bible, and got the same no-cheating results yet again.
I went to GigaOm Structure for the first time last year as a blogger. I am attending again this year as a GigaOm Pro Analyst.
Here are a few of the companies that look interesting from a data center perspective.
- Atlantis Computing goes beyond the VDI market and makes it possible to leverage commodity servers for storage-intensive virtualized applications in cloud environments.
- Cluttr focuses on helping companies manage their data centers more efficiently and responsibly, with a smaller environmental footprint.
- ComputeNext is a transparent marketplace for consumers and providers of cloud services that empowers choice and enables the search, purchase, and utilization of compute resources.
- Garantia Data is a fully automated cloud service for reliable memcached and infinitely-scalable redis, requiring zero management and guaranteeing absolutely no data loss.
- Keen provides analytics infrastructure as a service for mobile applications.
- MLstate is the provider of Opa, a new open source cloud development language designed to accelerate time-to-market for high-performance, massively scalable, exceptionally secure services and applications on any connected device.
- OneOps enables organizations to design cloud-based applications that align software requirements with business goals, automating the transition to agile operations.
- Tempo is the data layer for the measured world, purpose-built to store and analyze massive streams of time-series data generated by sensors and connected devices.
