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GigaOM | How Cloud & Utility Computing Are Different

We are witnessing a seismic shift in information technology — the kind that comes around every decade or so. It is so massive that it affects not only business models, but the underlying architecture of how we develop, deploy, run and deliver applications. This shift has given a new relevance to ideas such as cloud computing and utility computing. Not surprisingly, these two different ideas are often lumped together.

What is Utility Computing?

While utility computing often requires a cloud-like infrastructure, its focus is on the business model on which providing the computing services are based. Simply put, a utility computing service is one in which customers receive computing resources from a service provider (hardware and/or software) and “pay by the drink,” much as you do for your electric service at home – an analogy that Nicholas Carr discusses extensively in “The Big Switch.”

Amazon Web Services (AWS), despite a recent outage, is the current poster child for this model as it provides a variety of services, among them the Elastic Compute Cloud (EC2), in which customers pay for compute resources by the hour, and Simple Storage Service (S3), for which customers pay based on storage capacity. Other utility services include Sun’s Network.com, EMC’s recently launched storage cloud service, and those offered by startups such as Joyent and Mosso.

The main benefit of utility computing is better economics. Corporate data centers are notoriously underutilized, with resources such as servers often idle 85 percent of the time. This is due to overprovisioning — buying more hardware than is needed on average in order to handle peaks (such as the opening of the Wall Street trading day or the holiday shopping season), to handle expected future loads and to prepare for unanticipated surges in demand. Utility computing allows companies to only pay for the computing resources they need, when they need them.

What is Cloud Computing?

Cloud computing is a broader concept than utility computing and relates to the underlying architecture in which the services are designed. It may be applied equally to utility services and internal corporate data centers, as George Gilder reported in a story for Wired Magazine titled The Information Factories. Wall Street firms have been implementing internal clouds for years. They call it “grid computing,” but the concepts are the same.

Although it is difficult to come up with a precise and comprehensive definition of cloud computing, at the heart of it is the idea that applications run somewhere on the “cloud” (whether an internal corporate network or the public Internet) – we don’t know or care where. But as end users, that’s not big news: We’ve been using web applications for years without any concern as to where the applications actually run.

The big news is for application developers and IT operations. Done right, cloud computing allows them to develop, deploy and run applications that can easily grow capacity (scalability), work fast (performance), and never — or at least rarely — fail (reliability), all without any concern as to the nature and location of the underlying infrastructure.

Taken to the next step, this implies that cloud computing infrastructures, and specifically their middleware and application platforms, should ideally have these characteristics:

• Self-healing: In case of failure, there will be a hot backup instance of the application ready to take over without disruption (known as failover). It also means that when I set a policy that says everything should always have a backup, when such a fail occurs and my backup becomes the primary, the system launches a new backup, maintaining my reliability policies.
• SLA-driven: The system is dynamically managed by service-level agreements that define policies such as how quickly responses to requests need to be delivered. If the system is experiencing peaks in load, it will create additional instances of the application on more servers in order to comply with the committed service levels — even at the expense of a low-priority application.
• Multi-tenancy: The system is built in a way that allows several customers to share infrastructure, without the customers being aware of it and without compromising the privacy and security of each customer’s data.
• Service-oriented: The system allows composing applications out of discrete services that are loosely coupled (independent of each other). Changes to or failure of one service will not disrupt other services. It also means I can re-use services.
• Virtualized: Applications are decoupled from the underlying hardware. Multiple applications can run on one computer (virtualization a la VMWare) or multiple computers can be used to run one application (grid computing).
• Linearly Scalable: Perhaps the biggest challenge. The system will be predictable and efficient in growing the application. If one server can process 1,000 transactions per second, two servers should be able to process 2,000 transactions per second, and so forth.
• Data, Data, Data: The key to many of these aspects is management of the data: its distribution, partitioning, security and synchronization. New technologies, such as Amazon’s SimpleDB, are part of the answer, not large-scale relational databases. And don’t let the name fool you. As my colleague Nati Shalom rightfully proclaims, SimpleDB is not really a database. Another approach that is gaining momentum is in-memory data grids.

One thing is certain: The way the industry has traditionally built software applications just won’t cut it on the cloud. That’s why companies such as Google, Amazon and eBay have developed their own infrastructure software, opting not to rely on products from the large middleware vendors such as Oracle and BEA, who designed them with a very different approach in mind.

For this reason, we are seeing the emergence of a new generation of application platform vendors. These vendors, which include my own company, GigaSpaces, are building software platforms made for the cloud from the ground up: “cloudware,” if you will.

So although they are often lumped together, the differences between utility computing and cloud computing are crucial. Utility computing relates to the business model in which application infrastructure resources — hardware and/or software — are delivered. While cloud computing relates to the way we design, build, deploy and run applications that operate in an a virtualized environment, sharing resources and boasting the ability to dynamically grow, shrink and self-heal.

http://gigaom.com/2008/02/28/how-cloud-utility-computing-are-different/

VentureBeat | ParAccel, analytical database company, raises $22M more

ParAccel, a San Diego company that has developed an analytical database that it says provides faster access to business information data, has raised $22 million in a second round of financing, VentureBeat has learned.

Investors include Bay Partners, Mohr Davidow Ventures and PacVen Walden Ventures.

Here is some of the company’s literature on its offering:

Built for Speed: Why ParAccel’s Columnar, MPP DBMS is More Efficient

• Only relevant columns are retrieved (A row-wise DBMS would pull all columnns and typically discard 80-95% of them)
• All operations are done in parallel (A non-parallel DBMS must scan all of the data sequentially)
• Adaptive compression makes disks faster, reduces decompress effect
• A memory-centric design maximizes in-memory processing
• Patent-pending innovations drive performance to unprecedented levels

Tagged co:ParAccel, deal, inv:Bay Partners, inv:Mohr Davidow Ventures, inv:PacVen Walden Ventures

http://venturebeat.com/2008/02/25/paraccel-analytical-database-company-raises-22m-more/

The Economist | e-Government - from Web1.0 to Web2.0

GOVERNMENTS have more or less caught up with what in geek-speak is called “web 1.0”, with the online world largely mimicking the offline world. E-mails replace letters; websites make publishing speedier and more effective; data are stored on the user's computer. A collection of programs, paid-for or pirated, are the essential tools for getting going.

But all this has been overtaken by “web 2.0”, shorthand for the interactivity brought by wikis (pages that anyone can edit) and blogs (on which anyone can comment). Data are accessed through the internet; programs are opened in browser windows rather than loaded from the hard disc; instant messages, often attached to social-networking sites such as Facebook, replace e-mail. Web 2.0 also means free video-sharing on sites such as YouTube and free phone calls between computers. These developments allow information to be shared far more effectively, at almost no cost. That gives great hope to the proponents of e-democracy.

Citizens are not only the state's customers; they are also its owners. The term often used in the jargon of government technology is citoyen, reflecting the French idea of the politically engaged citizen. Technology can amplify and aggregate voices that used to be faint and muffled. Voters used to write letters to newspaper editors and hope they would be published. Now they can blog. Contacting an elected representative has become a simple matter of sending an e-mail.

The story so far is that technology intensifies the democratic process, but does not fundamentally change it. For example, the internet is now a vital way of raising money for political campaigns in America, but it has not supplanted the public meeting. Howard Dean's campaign for the Democratic party nomination in 2004 was a huge success in the blogosphere, but failed to translate into votes in real life. The internet has provided citizens with vastly more information about their elected representatives: their voting behaviour, their sources of finance, their outside interests, the content of every public speech they ever made. But the effects tend to cancel each other out. When each side has heavier ammunition, the battle rages on.

Some e-democracy efforts look like little more than gimmicks. Giving out politicians' personal e-mail addresses does not make them any more likely to read the result. Gordon.brown@no10.gsi.x.gov.uk, or president@whitehouse.gov make the recipients seem more accessible, but the message will probably be answered by a computer. Politicians and civil servants who have tried blogging have found it remarkably difficult to be both interesting and sensible. The spontaneous (and sometimes half-baked) tone of the blogosphere sits ill with the need to sound measured and definitive. Most politicians' blogs tend to degenerate into anodyne travelogues. One senior British official, Jeremy Gould, has an excellent blog on e-government. “We think he's been very brave,” says a colleague, carefully.

Where e-democracy may make a difference is in places where the middle class has become largely disengaged from politics. In India, for example, educated people are much less likely to vote than the rest. Opinion polls suggest that they are disgusted with bad government, but this rarely translates into votes against the incumbent parties.

Yet a few glimmers of hope are appearing. India is developing a caustic and increasingly effective blogosphere. Melody Laila, for example, electronically lambasts the inadequate public services in her native Mumbai, as well as the kid-glove treatment of corrupt politicians in Delhi. “Blogs give us the freedom to say things that wouldn't be published in the mainstream media, and the safety of anonymity,” she says. In a country like India, they may also prove more effective than their counterparts in older democracies. It is hard to imagine a blogger who would wish to promote the cause of corruption and bad government.

Technology offers an opening, too, to outfits such as Lok Satta, a clean-government campaign run by a formidable, Economist-wielding doctor called J.P. Narayan. It has recently celebrated its first electoral victory, in municipal elections in Mumbai. Its candidate, an energetic entrepreneur and community activist called Adolf D'Souza, campaigns for decentralisation, transparent online budgeting and public accountability. What made the difference, he explains, was that during house-to-house campaigning he collected voters' mobile phone numbers. That allowed him to send text messages, bypassing the local media which are cosily tied to the established parties.

As you might expect, the place that makes the most advanced use of technology in promoting public participation is America, where officials now invite online comments from outsiders when they draw up legislation on subjects like environmental protection. A Department of Agriculture draft on organic-food standards, for example, prompted more than 250,000 comments. Yet the expertise mostly comes from a narrow range of specialists.

According to Cary Coglianese, an American e-government expert, imagining that online consultation will breathe new life into democracy “is a bit like imagining that giving automobile owners the ability to download technical manuals and order car parts online would turn a great number of them into do-it-yourself mechanics”. Greater involvement by experts may make for more sensible rules, but it will not turn the system of public administration on its head.

Aux armes, citoyens

The sad truth is that most citizens find government and politics rather boring and think they have better things to do with their time. For outsiders, the online world is obscure and complicated. Similarly, the inherent complexity of government risks blocking the gains that technology can bring. Rupert George, who runs a site called eGov Monitor that enthusiasts find fascinating, explains: “All too often, public-sector investment in technology has been wasted by administrations unable to tackle the cultural change necessary to realise its potential.”

In short, badly managed organisations with computers will stay badly managed. That has been the lesson from private business, and it equally applies to the public sector, where e-government has barely begun to scratch the surface of what is possible. That is reason for disappointment, but also for hope.

http://www.economist.com/specialreports/displaystory.cfm?story_id=10638222

GigaOM | SaaS - How Not to End Up as an Anachronism

Imagine that your friend tells you that he has an idea for a new Palo Alto, Calif.-area restaurant that he wants you to invest in. His pitch goes like this: The restaurant is all about self-sufficiency. In addition to actually serving good food, this restaurant will feature the following:

• All food served will be organically raised and processed on-site
• Power will be provided by an on-premise power plant
• Water will be provided by a well-and-rain capture
• A self-contained waste management system will eliminate the need for a sewer hookup

While there are probably some people in Palo Alto that might actually think this is a good idea, you being of sound mind respond, “Is this a joke? Why build basic infrastructure like foodstuff production, water, sewer, etc. when very efficient, cost-effective, ‘pay-as-you-need-it’ options already exist?”

Imagine that your other friend tells you that she has an idea for a new software application company she wants you to invest in, and that this company (in addition to actually creating a useful service-based application) will:

• Build and manage redundant data centers with a carefully constructed custom hardware and software stack
• Set up an advanced network peering infrastructure for redundancy and improved latency
• Implement a flexible payment system for customers and channel partners

This could also be misconstrued as a joke. Why would a small application provider spend so much capital, time and energy building infrastructure when readily available ‘pay-as-you-need-it’ services exist, such as compute, storage and network infrastructure services (e.g. Amazon’s EC2 & S3 services), and payment services from Google, Amazon, etc.?

It is possible that specifics of your friend’s application make use of available service options infeasible, but it is just as likely that your friend has simply not yet adapted to a service-based infrastructure reality. There are always seemingly good reasons to continue doing things the way they were done in the past, and transition always presents challenges. As ironic as it may be, we continue to see software applications deployed as a service but which fail to use any service-based infrastructure themselves. They are two basic reasons for this situation: Change of existing operational services is hard. So is changing people behavior.

Once an application service is deployed, infrastructure changes are hard to make. Often commitments of capital cannot be undone without very high switching costs, such as advanced purchases of compute and storage capacity. Many architectural choices can have lasting ramifications.

For example, if a provider built their application based on the assumption of very large SMP servers, a proprietary commercial database clustering approach and vendor-specific HA infrastructure, they would find it difficult if not impossible to move to a service-based infrastructure that’s based on generic hardware/software platforms and horizontal scaling.

Even for a new application service, it’s often hard to find people who will embrace disruptive infrastructure options. It is almost inherent in human nature that once we develop a difficult skill we are reluctant to give up using it — even after simpler and more efficient alternatives become obvious. Often, people perceive that their livelihood is tied to the skill and then fear their own obsolescence in the obsolescence of the skill. The history of software applications provides a rich set of examples of this phenomenon. At one time, it was common for software application providers to create their own hardware, operating systems, networking infrastructure, languages, compilers, user interface technology, etc. Eventually, successful application providers took advantage of standard hardware platforms, operating systems and languages — to the detriment of the many providers that clung to the prior model. Likewise, vendors that leveraged the Internet and application servers gained, while many others continued to cling to proprietary client/server architectures and were the worse for it.

The recent “software-as-service” phenomenon is a particularly interesting example of disruptive change. SaaS was first seen as a disruptive force inside of the IT groups of large application users. Most companies are starting to understand that they would be better off with less information technology on their premises and more of it procured as a service over the Internet. Still, however, many within IT organizations are reluctant to embrace this form of change. (Personally, every time I see an IBM Blade Server commercial during a major sporting event, I’m wondering what percentage of the viewers know what it is, what percentage of those could actually affect the purchase of one, and then what percentage of those should actually be buying data center servers in an efficient universe).

We are now at point where implementors of SaaS capabilities are being disrupted by newer SaaS capabilities. Services that are built largely from other services are a reality, and offer many clear advantages. The types of services that could be used in the creation of new services span the spectrum, from base infrastructure services to complementary high-level application services that can be composed or mashed up. Example services include: compute and storage services; DB and message-based queuing services; identity management services; log analysis and analytic services; monitoring and health management services, payment processing services; e-commerce services like storefronts or catalogs; mapping services; advertisement services; in addition to the more well-known business application services like CRM and accounting.

The move to SaaS applications built on SaaS is a much more profound shift than the move from on-premise applications to SaaS applications. The software industry is beginning to display characteristics that mimic the supply chains and service layering that are commonplace in other industries like transportation, financial services, insurance, food processing, etc. A simple set of categories like applications, middleware and infrastructure no longer represents the reality of software products or vendors. Instead of a small number of very large, vertically integrated vendors, we are seeing an explosion of smaller, more focused software services and vendors. The reasons for this transition are simple: It takes less capital and other resources to create, integrate, assemble and distribute useful software capabilities.

By leveraging service options like Amazon’s EC2 and S3, a small company can deploy a complex, highly available and scalable multi-user software application — without huge upfront investments in hardware or software infrastructure. Likewise, a very small company can build a simple, narrowly focused service and can cost-effectively sell it to a mass audience. Neither of these companies would have been possible only a short time ago.

A new software service economy is rapidly unfolding and is causing disruption in the software industry. Ironically, some of the first victims of this new economy may be some pioneers of the software-as-a-service movement. Today, many established SaaS application providers are applying much more of their precious focus and capital to infrastructure issues than newer competitors that are aggressively utilizing service-based infrastructure. The self-contained restaurant and the build-it-all-ourselves SaaS application vendor both have seemingly good rationales for their chosen paths, but both will ultimately end up as anachronisms that are left behind by their competition.

http://gigaom.com/2008/02/14/how-not-to-end-up-as-an-anachronism/

VentureBeat | Sun continues open source rampage, buys PC virtualization company Innotek

Sun Microsystems has acquired Innotek, a Stuttgart, Germany provider of open source desktop virtualization software called VirtualBox, for an undisclosed amount.

VirtualBox is part of a hot group of companies allowing for much more efficient use of computers within large companies. VirtualBox enables desktop or laptop PCs running pretty much any operating system — Windows, Linux, Mac or Solaris — to run multiple, different operating systems side-by-side, switching between them with just a click of the mouse.

This allows software developers to more easily build multi-tier or cross-platform applications, and saves a company from having to buy multiple machines.

VirtualBox is also open source, and the move keeps Sun in the leadership pack as a major provider of open source software. It just acquired open source database company MySQL for $1 billion.

With more than four million downloads since January 2007, Innotek’s VirtualBox also has offices in Dresden, Berlin and the Russian Federation.

Innotek has been developing PC virtualization technology since 2001.

Yakov Sadchikov, who is following the European and Russian scenes closely, notes the acquisition comes soon after SWSoft, a competing virtualization software company from Russia was renamed Parallels.

Also, he cites Randall Kennedy of InfoWorld calling the Sun-Innotek deal a smart buy: “… even more important is Sun’s recognition of Innotek’s commitment to developers. VirtualBox has long been the preferred solution for open-source programmers seeking to ‘roll their own’ virtualization platforms.”

Innotek was privately funded.

http://venturebeat.com/2008/02/13/sun-continues-open-source-rampage-buys-pc-virtualization-company-innotek/

TechCrunch | Oracle to Acquire Salesforce.com?

Tis the season for deal speculation, with Tom Foremski quoting sources who say that Salesforce has approached Oracle “to gauge if there is any interest in a sale at $75 a share.”

If Oracle did take the deal, it would value Salesforce at just shy of $9 billion.

Michael wrote in June 2007 that Saleforce was “acquisition bait,” although at the time the rumors were pointing to a deal with Google. That didn’t happen, although Google and Salesforce did end up partnering for online ad sales.

Salesforce’s stock has weathered the stock market downturn fairly well, closing at $50.86 Friday, down from a peak of $64 in December, however a deal at $75 a share is still down on speculation of a deal at $80-$85 a share last year.

See our previous Salesforce coverage here.

http://www.techcrunch.com/2008/02/09/salesforce-shopping-itself-to-oracle-for-75-share/