Big Data Made Easy — Right Cloud, Right Workload, Right Time
Over the past five to six years, the platform and infrastructure ecosystem has gone through some major changes. A key change was the introduction of virtualization in infrastructure architecture. This not only provides a consolidation solution and, therefore, a cost-saving answer, but it also enables orchestration and management of the server, network and storage ecosystem.
Before virtualization, the ability to dynamically stand up, configure and scale an environment was time-consuming, manually intensive and inflexible. Now, virtualization is embraced by many organizations, and its use to support business growth is commonplace. If we wrap some utility commercial frameworks around this, pre-package some servers, storage and network architecture, and a support framework, we have the makings of an agile, scalable solution.
This all sounds perfect, so where can I buy one?
One what? Well let's call this new world order "the cloud" But which cloud? There are many different cloud solutions: public, private, on-premises, off-premises and everything in between.
Your choice will depend on your workload, need for regulatory compliance, confidence level and finances, so it's unlikely that just one cloud solution will solve all your needs. This is not uncommon. The reality is that today's businesses have a complex set of requirements, and no one cloud will solve them all. Not yet, anyway!
The next step is to determine how to align your business needs with the right cloud and how to provision the cloud to deliver your business applications — gaining benefits such as reduced effort and complexity, a standard process, and an app store type of front end.
This is the role the CSC Agility Platform is designed to fill. ServiceMesh, CSC's recent acquisition, is able to orchestrate multiple clouds with predefined application blueprints that can be rolled out and deployed on a range of public and private cloud solutions.
Great, but how does it help my Big Data Projects?
Since big data is enabled by a collection of applications — open source and commercial — we can now create application blueprints for deploying big data solutions rapidly on the cloud. Let's concentrate on big data running on a cloud infrastructure. (Quick refresh: Hadoop drives the infrastructure to commodity x64-based architecture with internal dedicated storage, configured in grid-based architecture with a high-performance back-end network.)
Today, some companies are running Hadoop clusters in the public cloud on providers such as Amazon and Google. For the longer term, those companies will discover that scaling issues and regulatory compliance will prevent this from being a single-answer solution. At the other end of the spectrum, Yahoo, Facebook and LinkedIn environments are built on dedicated petabyte-scale clusters running on commodity-based architecture. Although we see some very large clients with this kind of need, the typical big data deployment will sit somewhere between these two bookends.
With a controlled virtualization technology to underpin the dedicated Hadoop clusters at scale, configured in a way that does not have an impact on performance, ServiceMesh can be used effectively to provision and manage big data environments. This can include delivery on public clouds such as Amazon. Also, through the use of big data blueprints, the same solution can be deployed with on- and off-premises cloud solutions, enabling you to choose — through an intuitive interface — the right hosting platform for the workload you are trying to align with.
Does the combination make sense?
Absolutely. The intent of big data is to focus on driving business value through insightful analytics, not provisioning and deploying Hadoop clusters. If we can simplify and speed up the provisioning process, we can align the workloads with the most appropriate hosting platform. The complexity of deploying and configuring big data solutions requires key skills. Seeking to do this on multiple environments can become time-consuming and very difficult to manage. That's why the use of an advanced orchestration tool can reduce your resource overhead, costs and errors, while also letting you operate more quickly. Creating this kind of environment is a specialty task. CSC Big Data platforms can manage multiple clouds, scalable workloads faster with limited upfront investment for you to derive the right insights, to be the best at your business.