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Network World - This vendor-written tech primer has been edited by Network World to eliminate product promotion, but readers should note it will likely favor the submitter's approach.
There is a lot of discussion in the storage industry in regard to "scale-up" versus "scale-out" architectures for backup and recovery operations. More and more organizations are reducing or eliminating the use of tape by deploying disk-based appliances that use deduplication. But the architectural approach used by the appliance vendor can make a significant difference to the performance, scalability and total cost of the selected solution.
Before discussing the pros and cons of the scale-up and scale-out approaches, let's define the terms:
• Scale-up typically refers to architectures that use a single, fixed resource controller for all processing. To add capacity, you attach disk-shelves up to the maximum for which the controller is rated.
• Scale-out typically refers to architectures that scale performance and capacity separately or in lockstep by not relying on a single controller, but instead provide processing power with each unit of disk.
With either approach a key thing to understand about disk-based backup is that, without deduplication, the economics do not work well against tape. Because many organizations keep weeks, months or even years of backup data, the actual amount of backup data is typically many times the amount of live data in the environment. This makes straight disk too expensive. So combining disk and deduplication is the first step to having an actual product for the backup and recovery market.
On the face of it, scale-up architectures represent a simple premise: Disk plus deduplication creates a backup and recovery appliance that can meet the economics of backup. But backup and recovery is more than just a storage problem. In fact, backup and recovery is:
• A data movement problem -- moving significant data amounts within a pre-defined backup window.
• A data processing problem -- data needs to be processed to be stored in deduplicated form.
• And a storage problem -- deduplication allows for more backup data to be stored in far less disk space.
That said, scale-up approaches offer several advantages: They have a perceived simplicity as they typically only have one computing element where you do configuration and management; in some cases, a scale-up architecture may require less power and cooling; scale-up approaches have been around longer and are more familiar to administrators, generally offering a good feature set and functionality to suit their purpose.
But data growth leads to performance problems in a scale-up architecture, and the reason is simple. Because the architectures include a single computing element that houses all network ports, processor and memory, their performance is limited by the capabilities of that component. As data inevitably grows, only capacity (meaning more workload) can be added until such time that the maximum capacity of that controller is reached.