@CloudExpo Authors: Liz McMillan, Zakia Bouachraoui, Yeshim Deniz, Pat Romanski, Elizabeth White

Related Topics: @CloudExpo

@CloudExpo: Article

Datapipe Tells Which Way the Wind Blows

Predictions or Previews? You Decide.

A few weeks ago, I wrote a piece about the tony managed service provider, Datapipe, and their newest offering, managed private clouds deployed in Amazon's infrastructure, a first for both companies.  I think the new service is a very cool idea that presages things to come - "Cloud VARs".

Today the company put out one of those "the way we see it" releases that I typically ignore because they are usually empty self-promotion devoid of news, data, or insight.  You know the ones I am talking about - "Acme Technowidgets Predicts Cloud Adoption Will Continue in 2011".  But, this one is worth noting, because it is somewhat insightful, but more because it probably telegraphs future news for Datapipe, a company worth following.

Ed Laczynski, Datapipe's vice-president for cloud strategy and architecture, a smart guy with a good grip on where cloud computing is going, has cited these three trends for 2011:

Household Names Will Make Big Cloud Decisions

"2011 will be the year when industry giants from across the spectrum - including major financial institutions, pharmaceuticals and retailers - will migrate major internal and external IT systems to the cloud."

Enterprise-Grade SLAs

"Robust SLAs around full solution availability, performance and incident response will allow more customers to trust mission-critical and production-level systems to cloud computing."

Industry-Targeted Clouds

"As the value-chain between cloud providers, ISVs and managed services continue to take shape and evolve, experts in industries such as healthcare, gaming, and financial services will offer new solutions that leverage cloud computing technology to meet the specific IT requirements of these communities."

I know, not exactly earth-shattering, but consider the source.  Laczynski is not a pundit.  He is a cloudsmith in a hosting outfit that doesn't (yet) have the name recognition of a Rackspace but one that has data centers on both US coasts, as well as London, Hong Kong, and Shanghai, internal mindshare at AWS, the backing of Goldman Sachs, and a blue-chip customer list.  To me, Datapipe is a weather vane for cloud computing, and I take these three trend predictions more as indications of what the company itself is actually up to.

Datapipe has a number of name-brand customers in financial services, pharma and retail, and the services it is now providing to them include managed services and hosted infrastructure.  Prediction 1 tells me that Datapipe is in the process of convincing some of those customers to move some of their major apps to its new cloud.  This is especially interesting because, if you read my other piece about Datapipe, you know that that cloud infrastructure is not running in Datapipe's  data centers, but rather in Amazon's cloud.  In other words, Datapipe is making Amazon safe for serious enterprise apps.  That's news.

Prediction 2, "enterprise-grade SLAs around full solution availability" in the cloud, is a type of value that Datapipe is already adding to AWS, as I outlined previously:

"The Datapipe Managed Cloud also provides a range of SLA options, from pass-through support for Amazon's standard EC2 and S3 service level agreements to custom agreements providing up to 100% availability, made possible by combining multi-region AWS deployments with dedicated Datapipe server resources."

So, on this one, they are just vamping, but well they should.  Amazon itself doesn't promise 100% SLAs.

Prediction 3, "Industry-targeted clouds" is, by far, the most interesting of the three.  I am hearing Morse code again.  Part of the prediction's wording is,

"In 2011, Datapipe expects to see new products and services that focus not just on general IT needs, but also on opportunities related to specific industries and verticals."

Expects to see new products from whom?  They are letting us believe that they are talking about the industry at large, but I think this is more of statement about them.  As mentioned above, Datapipe already has customers in financial services, and they also already have ones in health care and gaming.  On their web site they talk about the solutions they have developed for these customers in their conventional managed services business.  Methinks they are moving some of that stuff to their cloud with an eye towards vertical sector leadership, which is smart.

Now, blend all three predictions into one and allow it to be about Datapipe itself, rather than the industry at large: Datapipe is building vertical clouds (nice) with comprehensive SLAs (sure) for industry-leading customers (hmmm), running on Amazon Web Services (yowza!)

Compare that to Rackspace's generic, one-size-fits-all cloudservers, cloudfiles, and cloudsites, running in their shopping mall-sized data center in San Antonio (it actually was originally a shopping mall) for a gazillion mostly small customers.  Meh!  If you like, throw in Open Stack, the open source cloud platform specification that Rackspace is developing with NASA and a legion of various kinds of technology providers.  It is low-level, commodity stuff that anybody, including Datapipe or Amazon, can use when it becomes real, if they want to.  It's great nerd candy, but it doesn't make Rackspace itself more competitive or enhance their commercial leadership.

Datapipe's got the mojo - you just watch.


More Stories By Tim Negris

Tim Negris is SVP, Marketing & Sales at Yottamine Analytics, a pioneering Big Data machine learning software company. He occasionally authors software industry news analysis and insights on Ulitzer.com, is a 25-year technology industry veteran with expertise in software development, database, networking, social media, cloud computing, mobile apps, analytics, and other enabling technologies.

He is recognized for ability to rapidly translate complex technical information and concepts into compelling, actionable knowledge. He is also widely credited with coining the term and co-developing the concept of the “Thin Client” computing model while working for Larry Ellison in the early days of Oracle.

Tim has also held a variety of executive and consulting roles in a numerous start-ups, and several established companies, including Sybase, Oracle, HP, Dell, and IBM. He is a frequent contributor to a number of publications and sites, focusing on technologies and their applications, and has written a number of advanced software applications for social media, video streaming, and music education.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.

CloudEXPO Stories
With more than 30 Kubernetes solutions in the marketplace, it's tempting to think Kubernetes and the vendor ecosystem has solved the problem of operationalizing containers at scale or of automatically managing the elasticity of the underlying infrastructure that these solutions need to be truly scalable. Far from it. There are at least six major pain points that companies experience when they try to deploy and run Kubernetes in their complex environments. In this presentation, the speaker will detail these pain points and explain how cloud can address them.
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-centric compute for the most data-intensive applications. Hyperconverged systems already in place can be revitalized with vendor-agnostic, PCIe-deployed, disaggregated approach to composable, maximizing the value of previous investments.
When building large, cloud-based applications that operate at a high scale, it's important to maintain a high availability and resilience to failures. In order to do that, you must be tolerant of failures, even in light of failures in other areas of your application. "Fly two mistakes high" is an old adage in the radio control airplane hobby. It means, fly high enough so that if you make a mistake, you can continue flying with room to still make mistakes. In his session at 18th Cloud Expo, Lee Atchison, Principal Cloud Architect and Advocate at New Relic, discussed how this same philosophy can be applied to highly scaled applications, and can dramatically increase your resilience to failure.
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by sharing information within the building and with outside city infrastructure via real time shared cloud capabilities.
As Cybric's Chief Technology Officer, Mike D. Kail is responsible for the strategic vision and technical direction of the platform. Prior to founding Cybric, Mike was Yahoo's CIO and SVP of Infrastructure, where he led the IT and Data Center functions for the company. He has more than 24 years of IT Operations experience with a focus on highly-scalable architectures.