Daily Archives: October 17, 2008

Power usage effectiveness

Two interesting blog posts:
Chirag Mehta: Greening the Data Centers
Microsoft: Charging Customers for Power Usage in Microsoft Data Centers

Also, Google has publicly released its data center efficiency measurements, as part of their docs on their commitment to sustainable computing. What they don’t say is the degree to which their green efforts impacts the availability of their facilities. Google can afford to have lower individual facility reliability, because their smart distributed infrastructure can seamlessly adapt to failure. Most enterprises don’t have that luxury.

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Blog vs. research note

I’ve been grappling with finding the right balance between blogging and writing actual research notes. I am an all-at-once writer — I’m usually at my best when I sit down and write an entire research note at one go, so it comes out as one coherent whole. A research note is something that has usually percolated about in my head for a while and is now ready to be expressed in what I hope is a bit of crystallized clarity. Problematically, though, I spend nearly my entire day on the phone with clients — I often only have 15 minutes between calls, just long enough to attend to the needs of biology and deal with my email. Eight such fragments in no way equate to an actual uninterrupted two hours, or even one hour, which makes it very hard to write substantive documents.

On the other hand, I can write a blog entry in 15 minutes, or in a bunch of 15-minute fragments, because it’s far more stream-of-consciousness. It’s unpolished thought; it can be more disjointed. It can raise questions without trying to provide answers, speculate, and be wooly maunderings rather than actionable advice. It can be trivial in the broader scheme of things, but is given power by immediacy and connectedness. It’s enormously tempting to scribble things down and just let them float out into the world. I became an analyst in part because I like to write, and it’s easy to get sucked into scribbling something whenever I get a chance.

I was googling around for the thoughts of others on this subject, and I came across Andrew Sullivan’s newly-published piece in the Atlantic, “Why I Blog“. His musings in that piece have the elegance of long contemplation, and, I think, he does an excellent job of capturing the nature of blogging, writing:

A blog is not so much daily writing as hourly writing. And with that level of timeliness, the provisionality of every word is even more pressing — and the risk of error or the thrill of prescience that much greater.

Andrew Sullivan’s piece has, perhaps, one of the best indirect answers to the whole Bloggers vs. Analysts question, as well:

A traditional writer is valued by readers precisely because they trust him to have thought long and hard about a subject, given it time to evolve in his head, and composed a piece of writing that is worth their time to read at length and to ponder. Blogs don’t do this and cannot do this — and that limits them far more than it does traditional long-form writing. A blogger will air a variety of thoughts or facts on any subject in no particular order other than that dictated by the passing of time. A writer will instead use time, synthesizing these thoughts, ordering them, weighing which points count more than others, seeing how his views evolved in the writing process itself, and responding to an editor’s perusal of a draft or two. The result is almost always more measured, more satisfying, and more enduring than a blizzard of posts.

I think the need to engage with the wider community and to be more timely will inexorably push analysts towards adding blogging to their output activities (even if not employer-recognized), but it certainly won’t replace traditional research notes. Moreover, social media is here to stay in the lives of analysts; it’s useful and it’s relevant.

Forrester’s Jeremiah Owyang described 7 tenets of the connected analyst in his blog today; it’s a well-encapsulated set of thoughts on how analysts should engage with the community. To me, that emphasis on connection is a shift in the nature of analysts. Although we write research notes, our research clients probably derive the greatest value from the relationship, the one-on-one interactions that consider an individual client’s situation and provide tailored advice. Blogging, on the other hand, is a one-to-many, perhaps many-to-many, activity.

I’ll have something on the order of 800 one-on-one client interactions this year. Many of these clients will have read a research note before talking to me. But they want to talk about it — to privately ask detailed questions, to get help with their specific situation, to understand the data supporting the conclusions, and in short, to get the equivalent of boutique personalization.

Despite my belief in the value of the relatoinship, though, analyst firms, including mine, still make a lot of money off research subscriptions. And that gives me a professional responsibility to think hard about what to put in a freely-accessible blog versus what to put in a research note that people pay a lot of money for. So in the end, I think that what I’ll be blogging are the things that don’t yet make for good research notes — quick news takes, musings, interesting little tidbits, things that aren’t of ongoing interest to clients, and interaction with the broader blogosphere.

I’m curious to hear the thoughts of others on this subject, whether they’re other Gartner analysts, analysts at competing firms, our clients, or our detractors.

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Google’s G1 Android phone

The first real reviews of Google’s first Android phone, the T-Mobile G1 (otherwise known as the HTC Dream), have begun to emerge, a week in advance of its release in stores.

Walt Mossberg of the Wall Street Journal has a detailed first look. Andrew Garcia of eWeek has a lengthy review. John Brandon of Computerworld has a first look and review round-up. But the reviews thus far have been focused on the core phone functionality, and it’s not clear to what extent the available third-party apps explore the capabilities of Android.

I am personally looking forward to checking out the new phone. I was an early user of the T-Mobile Sidekick (aka the Danger Hiptop), and I loved its rendering of webpages (and its smart proxy that reduced image sizes, did reformatting, and so on), its useful keyboard, its generally easy-to-use functionality, and the fact that it stored all of its data on the network, removing the need to ever back up the device. I was disappointed when the company did not follow through on its promise of broad third-party apps; despite release of an SDK and an app store, you couldn’t use third-party apps without voiding your warranty.

These days I carry a corporate-issued Cingular 8525 (aka HTC Hermes), but despite it being a very powerful Windows Mobile smartphone, I actually use fewer apps than I did on my Sidekick. I use my phone to tether my laptop, for SSH access to my home network, and for basic functionality (calls, SMS, browser), but despite one of the best keyboards of any current smartphone it’s still not good enough to for real note-taking (with serious annoyances like the lack of a double-quote key), the browser falls well short of the Sidekick’s, the lack of network storage means I’m reluctant to trust myself to put a lot of data on it, and the UI is uninspired. So I’m quite eager to see what Android, which represents the next generation of thinking of the key figures of the Sidekick team, is going to be able to do for me. But I don’t want to return to T-Mobile (and I need AT&T for our corporate plan anyway), which means I’m going to be stuck waiting.

On another note, I’m wondering how many Android developers will choose to put the back-ends of their applications on Google App Engine. Browsing around, it seems like developers are worried about exceeding GAE quotas — everyone likes to think their app will be popular, and quota-exceeded messages are deadly, since they are functionally equivalent to downtime. GAE also requires development in Python, whereas Android requires development in Java, but I suspect that’s probably not too significant.

I haven’t really seen anything on hosting for iPhone applications, thus far, except for Morph using it as a marketing ploy. (Morph seems to be a cloud infrastructure overlay provider leveraging Amazon EC2 et.al.)

Hosting the back-end for mobile apps is really no different than hosting any other kind of application, of course, but I’m curious what service providers are turning out to be popular for them. Such hosting providers could also potentially offer value-adds like mobile application acceleration, especially for enterprise-targeted mobile apps.

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Software and thick vs. thin-slice computing

I’ve been thinking about the way that the economics of cloud computing infrastructure will impact the way people write applications.

Most of the cloud infrastructure providers out there offer virtual servers as a slice of some larger, physical server; Amazon EC2, GoGrid, Joyent, Terremark Enterprise Cloud, etc. all follow this model. This is in contrast to the abstracted cloud platform provided by Google App Engine or Mosso, which provide arbitrary, unsliced amounts of compute.

The virtual server providers typically provide thin slices — often single cores with 1 to 2 GB of RAM. EC2’s largest available slices are 4 virtual cores plus 15 GB, or 8 virtual cores plus 7 GB, for about $720/month. Joyent’s largest slice is 8 cores with 32 GB, for about $3300/month (including some data transfer). But on the scale of today’s servers, these aren’t very thick slices of compute, and the prices don’t scale linearly — thin slices are much cheaper than thick slices for the same total aggregate amount of compute.

The abstracted platforms are oriented around thin-slice compute, as well, at least from the perspective of desired application behavior. You can see this in the limitations imposed by Google App Engine; they don’t want you to work with large blobs of data nor do they want you consuming significant chunks of compute.

Now, in that context, contemplate this Intel article: “Kx – Software Which Uses Every Available Core“. In brief, Kx is a real-time database company; they process extremely large datasets, in-memory, parallelized across multiple cores. Their primary customers are financial services companies, who use it to do quantitative analysis on market data. It’s the kind of software whose efficiency increases with the thickness of the available slice of compute.

In the article, Intel laments the lack of software that truly takes advantage of multi-core architectures. But cloud economics are going to push people away from thick-sliced compute — away from apps that are most efficient when given more cores and more RAM. Cloud economics push people towards thin slices, and therefore applications whose performance does not suffer notably as the app gets shuffled from core to core (which hurts cache performance), or when limited to a low number of cores. So chances are that Intel is not going to get its wish.

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