Why Clustered Data ONTAP?

                 A helpful way to start understanding the benefits offered by clustered Data ONTAP is to consider server virtualization. Before server virtualization system administrators frequently deployed applications on dedicated servers in order to maximize application performance and to avoid the instabilities often encountered when combining multiple applications on the same operating system instance. While this design approach was effective it also had the following drawbacks:

•  It does not scale well – adding new servers for every new application is extremely expensive.
•  It is inefficient – most servers are significantly underutilized meaning that businesses are not extracting the full benefit of their hardware investment.
•  It is inflexible – re-allocating standalone server resources for other purposes is time consuming, staff intensive, and highly disruptive.

Server virtualization directly addresses all three of these limitations by decoupling the application instance from the underlying physical hardware. Multiple virtual servers can share a pool of physical hardware, meaning that businesses can now consolidate their server workloads to a smaller set of more effectively utilized physical servers. In addition, the ability to transparently migrate running virtual machines across a pool of physical servers enables businesses to reduce the impact of downtime due to scheduled maintenance activities.

Cluster Benefits:

Clustered Data ONTAP brings these same benefits and many others to storage systems. As with server virtualization, clustered Data ONTAP enables you to combine multiple physical storage controllers into a single logical cluster that can non-disruptively service multiple storage workload needs. With clustered Data ONTAP you can:

•  Combine different types and models of NetApp storage controllers (known as nodes) into a shared physical storage resource pool (referred to as a cluster).

•  Support multiple data access protocols (CIFS, NFS, Fibre Channel, iSCSI, FCoE) concurrently on the same storage cluster.

•  Consolidate various storage workloads to the cluster. Each workload can be assigned its own Storage Virtual Machine (SVM), which is essentially a dedicated virtual storage controller, and its own data volumes, LUNs, CIFS shares, and NFS exports.

•  Support multitenancy with delegated administration of SVMs. Tenants can be different companies, business units, or even individual application owners, each with their own distinct administrators whose admin rights are limited to just the assigned SVM.

•  Use Quality of Service (QoS) capabilities to manage resource utilization between storage workloads.

•  Non-disruptively migrate live data volumes and client connections from one cluster node to another.

•  Non-disruptively scale the cluster out by adding nodes. Nodes can likewise be non-disruptively removed from the cluster, meaning that you can non-disruptively scale a cluster up and down during hardware refresh cycles.

•  Leverage multiple nodes in the cluster to simultaneously service a given SVM’s storage workloads. This means that businesses can scale out their SVMs beyond the bounds of a single physical node in response to growing storage and performance requirements, all non-disruptively.

•  Apply software & firmware updates and configuration changes without cluster, SVM, and volume downtime.