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May 5, 2014

The battle between Amazon Web Services, Google and Microsoft for the public cloud gets more and more attention these days, but global managed services provider Dimension Data has thrown in its own hat into the equation with a new hybrid Windows Server cloud.

The company's plan is to offer enterprise customers the chance to migrate a legacy Windows app into a cloudy environment where it can be given the managed services treatment, complete with service level agreement.

That SLA, says David Hanrahan, general manager of Dimension Data Cloud Services, is likely to be rather more granular than the guarantees offered by a pure-play public cloud.

“If everyone's Cloud apps had been designed to run natively, that would be great,” he said. “The cost of re-platforming them is significant. We are getting traction to manage them and patch them.”

“Clients want to be able to migrate legacy 32-bit software to the cloud,” he said, adding that he feels many enterprises will take their first steps into the cloud in that manner.

That's perhaps an odd observation given the likes of AWS repeatedly point to very considerable adoption by big business, but perhaps also not surprising given he's selling just that kind of service.

In Hanrahan's defence, he also said that this kind of work is as balance-sheet friendly as its traditional engagements, thanks largely to a “build once and redeploy at will” approach to building out its cloudy offerings.

Perhaps surprising a bit is that Dimension Data isn't alone in this kind of market. The likes of Fujitsu and CSC also operate clouds on very large scales, offering the elasticity of pure-play public clouds with a promise of rather more grooming, feeding and SLA backing.

Dimension Data certainly thinks that there's plenty of upside in this kind of market-- last week it said it can quadruple its US $1 billion data centre business by 2018.

Some of that growth is expected to come from acquisitions like one announced today-- IT services company Nexus today came under the 'DiData' umbrella for an undisclosed sum, bringing with it 19 offices across the United States.

In other IT news

The Hadoop community said late yesterday that it's currently working as a team on various new patches that will bring Docker into the data management system, and independent benchmarks are already showing that the technology is now a lot faster than traditional server virtualization methods. The technology actually is a new breakthrough.

Docker is an open source Linux containerization technology that uses underlying kernel elements like namespaces, lxc, and cgroups to let a system admin run multiple apps with all their dependencies in secure sandboxes on the same underlying Linux operating system, making it an attractive option to server virtualization, which bundles a copy of the OS with each app.

In a set of specific benchmarks that an IBM worker released on Thursday, Big Blue demonstrated that Docker containerization has some huge advantages over the KVM hypervisor, from an overall performance perspective.

Alongside this, we also discovered some pretty impressive work by the Hadoop community to bring the technology into the eponymous data analysis and management engine.

This will add more punch to the idea that Docker could become an eventual replacement for traditional server virtualization approaches, granting businesses huge benefits from an open source technology.

To start with, benchmarks conducted by IBM show that Docker has a number of performance advantages over the KVM hypervisor when running on the open source cloud infrastructure tool OpenStack.

An informative post published by IBM's Boden Russell goes into further details about the results. "From an OpenStack Cloudy operational time perspective (boot, reboot, delete, snapshot, etc.) docker LXC outperformed KVM ranging from 1.09x (delete) to 49x (reboot)," Russell wrote.

"Based on the compute node resource usage metrics during the serial VM packing test, Docker LXC CPU growth is approximately 26 times lower than KVM. On this surface, this indicates a 26x density potential increase from a CPU point of view using docker LXC vs a traditional hypervisor. Docker LXC memory growth is approximately 3 times lower than KVM. On the surface, this indicates a 3x density potential increase from a memory point of view using docker LXC vs a traditional hypervisor," he added.

Not only does Docker have desirable resource-usage characteristics, but the way it allows developers to package applications has attracted attention from the open source Hadoop community.

Recently, we learned that some people are diligently working to add Docker support into a crucial component of Apache Hadoop 2.0 named YARN, with the goal of increasing the usefuleness of both technologies.

YARN was introduced in version two of Apache Hadoop, and it lets the software run multiple applications within Hadoop rather than purely MapReduce jobs.

Thanks to this, YARN is helping to transform Hadoop from a batch processing and storage system into a more general tool for manipulating and storing data.

By combining YARN with Docker, the community hopes that it can make it trivial for developers to package an application in a Docker container, then sling it onto the YARN tech as part of a larger Hadoop installation.

Altiscale, the company behind the code contributions that make this possible, was kind enough to answer some of our questions about why this could be useful.

"As a company building Hadoop as a Service (HaaS) platform, we are particularly interested in YARN as it allows Hadoop to move beyond map-reduce to a much more diverse variety of applications," explained the company's chief executive Raymie Stata.

"One of the key components of YARN that make this possible are containers. The existing YARN container implementation does not adequately provide all the types of isolation required to address a scenario we are noticing with our larger customers-– multiple, independent groups in the same organization with different software requirements."

By adding Docker support, Altiscale hopes that it can flatten some of the barriers that lie between enterprise developers and a greater utilization of Hadoop.

"For example, a common issue for users is software dependency management," Stata explained. "Docker provides an intriguing approach to solving that problem by allowing users to upload prepackaged environments or images into repositories which can then easily be downloaded and run in isolation".

"For instance, there are public repositories in the Docker community called Docker Registries which provide a variety of language environments such as Java and Ruby. There is also support for private repositories where containers with more specialized environments can be placed," he added.

Other members of the Hadoop community are keen on the addition of Docker as well. "Where Docker makes perfect sense for YARN is that we can use Docker Images to fully describe the entire Unix filesystem image for any YARN container," explained Arun Murthy, a founder and system architect at Hortonworks.

"In this manner, instead of forcing a user to deal with individual files or binaries as things stand today, we can allow the application to package the entire Unix filesystem image it needs as a Docker image and then get perfect predictability from an environment perspective at runtime."

"This is where Docker has the most amount of interest to the YARN/Hadoop community, particularly for users packaging complex applications which need their own version of Perl, Python, Java, Libc etc, that is hard to manage on YARN currently," he said.

The addition of Docker to YARN looks like a potentially useful tool and is another example of the enthusiasm with which Silicon Valley has adopted the young open source technology.

This follows Red Hat announcing the broad support for Docker in its eponymous Linux distribution, and launching a project named "Atomic" built around the technology. Amazon also recently added Docker support to its "Elastic Beanstalk" platform-as-a-service cloud.

Source: Dimension Data Cloud Services.

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