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George Crump

Eliminate Storage Headaches: Virtualize

Learn how virtualization, automation, and cloud computing can make your data center a competitive advantage, not a cost center.

The primary objective of virtualization and cloud computing is to create a data center that is more responsive to the needs of the business, that enables technology to be a competitive weapon instead of a cost center. Storage has to play a key role in this evolution so it can support these Agile IT initiatives.

In our upcoming webinar 3 Ways To Use The Cloud To Eliminate Storage Headaches, we are going to discuss how to eliminate storage administrative headaches like provisioning, performance management, storage expansion, and data protection. The key to eliminating these headaches is to create a storage value infrastructure which has three steps: virtualize the storage, automate the storage, and cloud-extend the storage. This first column will be devoted to storage virtualization, and we'll cover the other two steps in our next column.

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Storage virtualization can take two forms. First, the storage administrative processes like provisioning, LUN creation, and RAID configuration can be virtualized as part of the storage system so that you are not dealing with individual hard disk spindles.

Provisioning tasks are one of the storage management headaches, and virtualization eliminates them for the most part. Virtualization allows for storage administrators or application owners to simply "dial in" the amount of capacity they need and assign that capacity to a host or virtual machine. The storage software takes care of the rest in the background.

[ Where can you cut corners with commodity tech? See Storage Software Vs. Hardware: What's More Important? ]

The next type of storage virtualization builds on the above capabilities and extends them across multiple storage platforms, even if those storage platforms are from different vendors. In other words, the typical data center storage infrastructure. It is becoming increasingly apparent that no single storage solution can solve all of a data center's storage needs, especially as that data center grows.

The need for multiple storage solutions can cause a serious storage administration headache. Having to separately manage multiple storage systems from multiple storage vendors is time consuming and error prone. Storage hardware virtualization eases those headaches by providing a centralizing management and data services platform for these assets. These solutions provide flexibility in storage hardware purchases while at the same time unifying operations so that all tasks execute the same way, which reduces administration time and errors.

The remote storage cloud also has a role to play in storage virtualization. As we demonstrated in a recent test drive, Tuning The Cloud For Primary Storage, cloud storage software typically leverages a hybrid model, where local cache is leveraged for performance, but remote cloud storage is leveraged for almost limitless capacity. The cloud software will typically use any available storage system and then present this same "dial-in" provisioning. It can work in conjunction with other storage virtualization solutions for a totally unified on-premises / off-premises storage strategy.

The next step in creating a storage value infrastructure to reduce administration headaches is to leverage storage automation and to leverage cloud storage's innate data protection and disaster recovery capabilities. We'll cover these aspects in detail in our webinar as well as in our next column.



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By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



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