A group of social networking mischief-makers are bringing a panto to Twitter for the whole world to see.

If you’ve never been to a British pantomime, here’s what to expect:
 

• A central cast of actors take common themes and familiar stories, and twist them in new ways
• Men play women and vice-versa
• Old jokes are updated with topical humor
• Everything has a second, and decidedly naughty, meaning.
• The audience is expected–nay, commanded–to participate.
• Famous people show up unexpectedly.

 
It’s a perfect prototype for Twitter, with 140-character repartee and fast-flying innuendos.

And on Tuesday, December 23, a cast and audience are coming together on the microblogging network to put on the first Twitter panto. In true social network style, there’s only loose direction and gentle nudging from the directors. The brainchild of social media consultant John Bounds it’s an interesting holiday experiment.

There’s an interesting response from Chris Hoff over at Rational Security to my GigaOm piece about cloud computing and security. Chris makes some great points (and flagged a good study on computer fraud that refutes some of what I said.)

Worth a read. What do you think? Are clouds less secure than in-house computing? The usual answer seems to be “it depends” — but what does it depend on? Can we come up with some rules for what’s safe to do in a cloud and when?

Maybe I can convince Chris to come to Vegas and get into a pointed argument about cloud computing risks.

Twitter-like micromessaging is a relatively new communications model, with unique characteristics that affect how we use it and what’s appropriate. It’s an RSS feed for people, a way to directing the attention of audiences, and a means of reaching the famous without burdening them with an obligation to respond.

In short, Twitter is a human API. It’s being defined in real time in front of our eyes, through an amazing example of Internet Darwinism.

I’ve been spending a bunch of time on Twitter lately, partly because it’s fun, and partly because of the community management and social networking portions of a book I’m writing with @seanpower. Here are some observations so far.
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I wrote a piece for GigaOm on the gradually forming Google strategy for applications. Here’s the short version: Google Apps + App Engine + Chrome + Marketplace = Appexchange for small businesses.

The piece got referred to in a post by Enrique Dans, who blogs in Spanish. Naturally, I wanted to see what he’d said in the post, so I figured I’d put it into Babelfish and get a translation.

Sometimes the Internet says it better than you can: “Google has had 95% good news and is prepared to put all the meat in the spit.” I might stop and reflect on just how much technology was involved in that — writers in two countries, RSS feeds and linkbacks, translation.

Nah, putting all the meat in the spit is just awesome.

I use an email client on my iMac. When it can’t get to the server, it still works. But sometimes, on a slow day with an unreliable network like the one I’m on right now, I don’t realize that I have mail waiting for me. The disconnect between by client-side logic and the server-side data camouflages the fact that the network isn’t working.

By contrast, when I use GMail’s web interface to read my mail, I know when I have new messages. Because Google controls the processing (on its servers) and data (right next to them) the two are connected. No camouflage there: If the network sucks, I know it.
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If you’re wondering about the reach of Twitter (clocking in at over 3 million users now) consider the tragedy that’s happening right now in Mumbai. Apparently the police (and perhaps the attackers) are not only aware of Twitter — it’s also part of the problem.  The Indian government is asking that the #mumbai hashtag be shut down.

What’s more, with Twitter being an excellent medium for short messages but lacking the space for details, Internet users are now repurposing Wikipedia to maintain a frequently edited page.

Abstract: Network effects are powerful and scary.

The clouds just keep rolling in. Microsoft has thrown their hat in the ring with Azure which deserves notice because Ray Ozzie is behind it. Amazon just released a CDN service. With recent coverage in The Economist and every major newspaper, even my local news tonight, cloud computing appears to be here to stay, judging by the marketing feeding frenzy. There have been some recent well publicized outages that have generated some concerned opinion.  Something struck a related chord when I read an excellent interview by Stephen Strogatz about network effects in Seed magazine:

I have this general concern about entering this networked era, which we’re clearly already in. For example, the power grid used to not be a grid. It was just a lot of isolated power stations. When there was trouble people would just close down the power plants and repair whatever the problem was. But now that there’s a grid, when something bad happens at one point in the grid, and you use the defense strategy of just shutting down that plant, it can have propagating effects. It can put too much load on other plants, which may cause them to shut down. And this is exactly what we saw here in the northeast when we had the 2003 blackout. Or think about what is happening right now in the market, where there are all kinds of propagating, cascading failures in our market and financial systems. So, I’m just thinking that you may be opening a Pandora’s Box

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Mark Dowds and I just finished the Beyond Technology event in Vancouver, BC. Lots of folks wanted the slides, so here they are.

My content focused on the outside community — how to find and join conversations that your market, customers, and partners are having. Mark’s presentation looked at the cultural changes within organizations, and how social networking can help capture learning and promote sharing of knowledge within companies.

It was a very interesting discussion, with lots of follow-up both online and off.

From the Register, by way of Broadsight, it seems that Google has patched an issue with Android that interpreted text you type as commands. So you can type “reboot” and reboot the phone.

Really? Really?

I mean, I’ve heard Android is supposed to be an open platform. But if the tale is true — and there isn’t some kind of double-backflip configuration knob you have to fiddle with to make this work — it’s a big deal.

Consumer electronics don’t like to be open. Openness breeds complexity. The iPhone is criticized for being closed, but it’s usable (despite this post to the contrary) in part because it’s locked down. The button-bar iPhone resembles nothing so much as the old Compuserve menu. It took us years to move from consumer adoption of buttons to comfort with the open web.

If you let humans play with the guts of things, they tend to break in new and creative ways. Social engineering is the new hacking; now that many operating systems are patched and scanned, hackers exploit human weaknesses to send drive-by malware links to Facebook users. (Good thing the bad guys are after Warcraft passwords, then.)

But back to Android. Apple locks it down; Google opens it up. One approach delivers a seamless experience, the other so much flexibility you can hurt yourself. Apple assumes people will use its devices on a busy New York subway, jostling for handholds and bouncing in purses. Google assumes people will hack together scripts and plug-ins, finding new ways to use tag clouds and APIs. Apple partners with monopoly-scale carriers; Google lobbies for free spectrum.

The two philosophies couldn’t be more different. It’ll be fascinating to see whether integration trumps flexibility, or vice-versa.

Today, I’m going to write about an equation. I’ll try to make it easy to follow, but it’s still stats and graphs. Stay tuned and I’m convinced it will be worth your while, because in my opinion, it’s the most important equation in cloud computing. It’s what drives your market, your customers, and your burn rate.

If you build a traditional data center platform for your application, you worry about three variables: The amount of traffic to your site, your capacity to handle that traffic, and the user experience they get, such as latency. The equation looks like this:

User experience = Traffic / Capacity

As traffic increases, user experience gets worse and delay goes up. This is because each visit to your site consumes resources on your infrastructure, and some users wind up waiting for the app to respond. Networks get full; databases encounter record locking; message queues back up; and so on. Ultimately, some of your visitors have a lousy experience.

On-demand computing platforms fundamentally change how you deal with this, because as far as you’re concerned, they have infinite capacity.

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