The Road to Private Cloud Doesn’t Need to Be Bumpy!

Industry analyst Bill Claybrook wrote a lengthy article that recently appeared discussing the “bumpy ride” many companies may face on the road to private cloud implementation. Ironically, the article coincided with the release of Platform’s ISF Starter Pack, which is actually designed specifically to make that road less bumpy!

The good news, according to Claybrook, is that private clouds are the focus of many IT managers these days, as evidenced by Gartner, which reports 75 percent of IT managers would both pursue and invest more in private clouds than in public clouds through 2012.

Claybrook cited a number of challenges that private clouds can pose for companies, which include:

• Budget – According to Claybrook, private clouds can be expensive.
• Public Cloud Integration – Claybrook says companies should build private clouds that can be easily moved to a hybrid public model if necessary.
  Scale – Private clouds often don’t have the same capacity to scale as public ones, says Claybrook.
• Reconfiguration – Claybrook claims many organizations will need to tear down their infrastructure on the road to private cloud.
• Legacy hardware – Similarly, Claybrook recommends not repurposing old servers that require manual configuration for private clouds.
• Technology obsolescence – Claybrook advises that once implemented, private cloud stacks be kept up-to-date with the latest upgrades.
• Fear of change – Finally, IT teams will need to learn new ways of doing things, Claybrook says. This should be turned into a growth opportunity for your IT staff.

At Platform, we’re fond of saying that private clouds are indeed “built not bought.” But we have to respectfully disagree with Claybrook that the road will be bumpy for most. That’s part of why you go through the “build” process in the first place. Private clouds are not necessarily meant to be an immediate replacement for all IT operations within an organization. Taking an iterative approach to private cloud and “building” it out from department to department as necessary is the best way to implement a private cloud—and not all IT operations may need to be part of the cloud, either.

Making private cloud implementation easier and at low cost and low risk is exactly why we came up with the Platform ISF Starter Pack. For $4995, the ISF Starter Pack allows companies to quickly and easily set up a private cloud while avoiding many of Claybrook’s stated pitfalls:

• Budget – At $4995, the ISF Starter Pack is an affordable option. Many private cloud options in the market can cost upwards of $50K.
• Public Cloud Integration – The Starter Pack includes the same functionality as Platform ISF, including the ability extend the initial deployment to public clouds like Amazon EC2.
• Scale – Platform’s history in workload and resource management guarantees a high-scaling private cloud solution.
• Reconfiguration – Platform works with what you have in place because it’s implemented as a management layer – there’s no need to rip and replace your entire infrastructure. Most organizations can’t afford this anyway.
• Legacy hardware – Lather, rinse, repeat the “Reconfiguration” entry...
• Technology obsolescence - with Platform ISF you get a single private cloud management focused product that is the core of your private cloud architecture. This will enable you to evolve your cloud at your pace (not another technology suppliers pace) and ensure you retain control and have a partner that will protect you from technology obsolescence.
• Fear of change – The Starter Pack allows organizations that want to try private clouds to test them at minimal risk without a huge upfront investment. You can ease into the cloud on your own terms.

If you want to test private cloud without changing your entire infrastructure from the get-go try the ISF Starter Pack—it can help make the road to private cloud less bumpy.

Three ways to HPC Clouds

Almost one year ago, Platform’s CTO, Phil Morris blogged about some of the primary drivers for cloud adoption.  Looking back at his post, it is interesting to observe the paths many of our customers have since taken to actually implement cloud and, more specifically, HPC cloud.  HPC clouds, loosely defined, are systems where your scheduler realizes that current HPC loads require more resources than are physically or virtually available and then negotiates with a public cloud provider (EC2, Azure, etc) to obtain/rent/lease more computing horsepower.

Almost one month ago, Phil and I attended the annual HPC Day at Stanford University, where he described in detail the three common ways our customers are implementing Platform products to benefit from high-performance cloud computing.  The first way includes expanding and augmenting your existing cluster with instances from a virtual private cloud using Amazon’s high powered Cluster Compute Instances (CCI).  In case you’re not familiar with CCI, a cluster of them provides low latency, full bisection 10 GBPS bandwidth between instances.  Not only are they impressively robust systems (23 GB of usable memory, quad-core “Nehalem” architectures at 2.93GHz and 1690 GB of storage), but they can also be preconfigured to use IP addresses that are specific to your corporate domain.  In other words, they can appear to be running inside your own data center.  Because Platform LSF can automatically discover and add new compute instances within a specified IP range, expanding your local cluster by adding new instances from the cloud is as simple as starting new CCIs with the correct IP values.

 

The second way to HPC cloud is very similar to the first one, with the major distinction being that instead of adding new virtual instances to an existing physical cluster, you add a completely new virtualized cluster. In this instance it’s important to note that based on your organization’s security and compliance reasons, you may be allowed to only run certain jobs in the cloud while others must run inside your data center. Since our scheduler add-on product, Platform LSF Multicluster, is smart enough to dispatch jobs in compliance with your security and sharing policies, in this second version of HPC Cloud, the jobs that need to run locally are run locally, while those that can run in the cloud are run there.

As you can imagine, creating, managing, and enforcing security and sharing policies across physical and virtual clusters can be a daunting and complex task.  To address all the management challenges that can arise, we recommend leveraging Platform ISF to help you administer your private cloud.  Since ISF can determine when no internal resources are available and which jobs can be run in the cloud based on policy, it requests more resources from external cloud providers and builds new clusters on the fly in the public cloud.  Since it works in conjunction with Platform LSF, jobs get sent to the new cluster as soon as they become available.  This is the third way to extend your HPC resources into the cloud.

Cloud Use Case Series, Part 4: HPC Cloud

Last, but definitely not least in my four-part cloud use case blog series is the high-performance computing (HPC) cloud. This type of private cloud use case allows an organization to automatically change compute node personalities based on workload requirements, enabling resource harvesting within the datacenter and cloud bursting to external resources or the public cloud. This resource maximization results in near-100 percent utilization of the infrastructure with a cost-effective means to scale capacity to meet dynamic business demand.

A perfect example of an HPC cloud in use is CERN (European Organization for Nuclear Research), one of the world’s largest and most respected centers for scientific research. CERN depends on computing power to ensure that 17,000+ scientists and researchers in 270 research centers in 48 countries can collaborate on a global scale to solve the mysteries of matter and the universe. To accelerate their research, CERN requires a cost-effective shared computing infrastructure that can support any combination of RHEL, KVM, Xen, and Hyper-V for a widely diverse set of scientific applications on x86 servers. Previously, their clusters could not flex or be re-provisioned automatically, creating idle resources as users waited for their environments to become available.

With Platform ISF CERN is able to eliminate silos by re-provisioning thousands of nodes and VM’s based on application workload requirements. Platform ISF provides the self-service capability that allows scientists to directly choose their application environments and manage their own workloads, increasing user efficiency and reducing IT management costs.

As a scientific research organization, CERN keeps a close watch on expenses and with Platform ISF, they are delivering more services within a fixed budget with performance doubled on many applications. Dr. Tony Cass, Leader Group, Fabric Infrastructure, CERN told me that “if we can move 150 machines [from a total of 200] out of this environment by improving utilization, we can either save some significant power and cooling costs, or we can redeploy the machines to the batch cluster without increasing the hardware budget.” This type of resource maximization is what is needed to get the most return on investment from an HPC cloud deployment.

This concludes my four-part blog series that outlines all four private cloud use cases for companies evaluating internal shared infrastructures (should you want to review some of my previous posts, just click on the links below):
1. Infrastructure Cloud
2. Application Cloud
3. Test/Dev Cloud

Microsoft and Platform supercharge the HPC cluster!

It’s no secret that time is money, and designers, engineers and product analysts need to design, prototype and deliver products to market faster in order to meet shrinking product lifecycles and be competitive. To date, the obvious solution has been to do more and larger simulations that can create and even test parts prior to any metal being machined. Increased model sizes and the need for reduced run times has led many design teams to purchase and deploy several high performance computing (HPC) clusters for the muscle required to power their much needed solutions.

The challenge of this obvious solution is that the applications selected by design teams for complex simulations--which can include mechanical analysis, thermal modeling, rendering and fluid flow--are not always optimized for the same operating systems. This has led many enterprises to deploy multiple HPC clusters—one for each operating system—to allow users to run different applications, resulting in cluster silos and underutilized capacity. Design teams need a cluster that can dynamically switch between Windows and Linux, depending upon workload, and Platform Adaptive Cluster is what design teams can use to deploy a hybrid Windows/Linux HPC cluster.

A hybrid Windows/Linux cluster also cuts cost. Since the cluster can support both Linux and Windows less hardware needs to be purchased, and Platform Adaptive Cluster also increases effective application performance by allowing applications to access the capacity of the entire cluster. Cluster silos are eliminated and cluster resources are maximized.

Earlier this week, Microsoft made some waves in the HPC market by with the release of its much-awaited Windows HPC Server 2008 R2. When Windows HPC Server 2008 R2 release is used in combination with Platform Adaptive Cluster, HPC designers, engineers and product analysts can optimally coordinate the management of their HPC environment and workloads.

What’s great about the new Windows HPC Server 2008 R2 is that it integrates well with all the leading HPC solutions such as Dell, Cray, and Platform, allowing lots of collaboration and performance improvements across an enterprise’s HPC solution portfolio. With the Platform-Microsoft solution, enterprises no longer need to deploy separate HPC clusters to accommodate different operating systems, making it easier and more cost effective to deploy and use hybrid Windows and Linux clusters. The net result of the Platform-Microsoft solution is that design teams can better leverage technology in their quest to deliver better products to market faster.

Green HPC Using Adaptive Clusters

Greener data centers continue to be a priority with Platform customers, especially with rising energy costs and growing environmental awareness. There are several tools that Platform is developing to help make everyone's data center "greener" and more efficient.  From simple mechanisms to power-off idle machines to smarter placement of heat-generating jobs within a data center to minimize air flow disruption between your hot and cold aisles, Platform has been exploring, implementing and delivering a number of innovative, earth-friendly technologies. One relatively new solution that may not immediately strike you as a green solution is Platform’s Adaptive Cluster product, which I recently helped set- up for an oil and gas exploration customer of mine...

As is typical in many industries, this particular oil & gas company runs a number of different software packages which require different operating systems. Since many of their applications run on either Windows or Linux, but not both, they had to supply the power, space, cooling, and maintenance costs to support one cluster dedicated to Windows and another one dedicated to Linux. Since neither cluster was running to full capacity, they wanted to learn how to maximize each cluster’s spare capacity and thereby reduce the environmental impact of an idle infrastructure.

My immediate recommendation was to leverage our Platform Adaptive Cluster product, which allows you to maximize a cluster’s spare capacity by running BOTH Windows and Linux operating systems (OS) on the same cluster and automatically provisioning application resources across both. With all the recent advances in virtualization, having a mixed OS cluster is nothing new, however, what is new about Platform Adaptive Cluster is its ability to dynamically change the ratio of running operating systems based on workload demand. Let's say that 75 percent of your day-time jobs require Windows, but at night, Windows OS activity decreases to just 25 percent.  Platform Adaptive Cluster automatically handles the provisioning and de-provisioning of Windows systems to make sure all job requirements get met - regardless of OS.

Having a solution that can dynamically change the make-up of the currently running OS without manual intervention was of much interest to my customer. Using Adaptive Cluster, they’ve been able to really capitalize on their new system by consolidating capacity during low activity hours, saving considerable money on data center overhead costs.  During peak hours, however, they’ve been able to get more compute power across all clusters thanks to the flexibility of Adaptive Cluster.  If it is of interest to you as well, please make sure to check out my next blog on how the provisioning process works and visit the Adaptive Cluster section on our web site at http://www.platform.com/private-cloud-computing/hpc-cloud

Cloud Use Case Series, Part 3: Test/Dev Cloud

The third installment of my four-part cloud use case blog series is the test and development cloud. This type of private cloud deployment provides a self-service test and development infrastructure where resources are provisioned automatically and within minutes according to project timelines for test/dev teams within an organization. This results in better utilization of existing servers, lower costs, increased developer productivity, and a proving ground for a production application cloud.

A classic example of a test/dev cloud is a leading global financial services firm that has multiple software development groups distributed across the world. The bank’s main challenges stemmed from regional groups building siloed “build and development” environments that each manage 30 or more applications. This caused slow software build processes and wasted configuration time required to set-up application environments, as well as duplication of effort across teams.

Thanks to Platform ISF, the bank was able to consolidate their application development environments into a shared cloud solution, which dynamically creates complete application environments for development teams according to self-service requests and resource reservations according to project schedules. This has enabled a shared environment for application development across global teams, using fewer resources at lower cost, while increasing developer productivity.

Stay tuned for part 4 in my cloud use case series – HPC cloud - next week!

Cloud adoption is a marathon, not a sprint

Forrester’s James Staten recently made some interesting points on how organizations are feeling the heat when it comes to ‘doing cloud’. According to James, many organizations are talking the talk when it comes to cloud but in reality are doing little more than virtualizing part of their IT environment. This isn’t surprising given the attention cloud is receiving, everyone is eager to get on-board but it’s also concerning since as we all know, jumping head-first into any major IT project is almost always easier said than done.

As James points out, implementing a cloud environment is part of a journey and it can literally take years to get cloud-ready. Even for smaller organisations, setting up a successful cloud environment will not happen overnight. This view is in-line with the delegate research we’ve recently conducted and highlights that when it comes to cloud it’s all about gradual steps.

Experimenting is an important part of this process which is why James advocates organisations using ‘cloud-in-a-box solutions’ to learn how clouds operate and how far they need to go on their journey to full scale private cloud deployment.

Establishing a private cloud using out-of-the-box offerings is low risk, low cost and allows companies to quickly establish private clouds so they can evaluate the benefits. It also makes it easier for IT executives to achieve senior level buy-in for large scale cloud initiatives at a time when ROI is the name of the game.

We’ve recently announced the availability of the Platform ISF Starter Pack which enables organizations to establish initial private cloud environments extremely quickly and at a cost of just US$4,995. The Starter Park offers organizations a highly cost effective way to start their journey to private cloud, enabling them to explore the benefits and challenges of moving from their legacy IT infrastructure towards a new model of delivering IT.

Will the CIO allow the frog to be boiled?

What do you get when you combine a grass roots solution portfolio and adoption strategy with enterprise pricing schemes? Answer: A very attractive short-term value proposition that is sure to put many customers on the path to vCloud.

What’s the problem? Cost and vendor lock-in.

Cloud computing is the third major wave in the history of distributed computing and offers the promise of open systems enabling customer leverage through commodity IT components. However, incumbent vendors are fighting desperately to create integrated proprietary stacks that protect their core products and licensing models.

This battle for leverage between big vendors and customers comes down to a basic architectural decision: Does the CIO and senior architect team have an open systems vision for private cloud that they are willing to pursue in-spite of bundled offerings from vendors?

Platform Computing is betting that a large portion of the market will architect their private cloud platforms with heterogeneity and commodity as key principals.

Anyone who doubts that the frog is getting warm or that the intent for customer lock-in is real needs only to read Microsoft’s ad decrying vendor lock-in.