Consolidation projects are typically initiated in order to lower IT costs and improve overall IT operational efficiency. Internal reorganization, mergers, acquisition activity and the overall trend to data center consolidation because of server consolidation and storage consolidation all create challenges and unpredictable results when not planned correctly.
The consolidation of servers and storage can substantially increase the efficient use of resources, but can also result in complex configurations of data, networks, applications, and virtual servers that need to support highly unpredictable workloads. Risk is usually increased, especially when it comes to performance. Changing the mix of applications and evolving data management requirements are driving major change in storage requirements. IT managers are demanding storage solutions that allow them to deploy complementary tiers of networked storage systems optimized to meet specific requirements for performance, capacity, reliability, and cost. Consolidating older, expensive tier 1 storage systems into newer, more cost-effective lower tiered storage is another strategy often employed in consolidation projects.
Consolidated storage inevitably includes new network infrastructures to support the greater I/O demands. While these are potentially beneficial from a performance perspective, transitioning to higher speeds creates real challenges for storage architects in balancing performance with cost. WorkloadWisdom enables storage engineers and architects to make intelligent sizing and deployment decisions evaluating and testing:
Performance testing storage systems using accurate workload simulations that realistically resemble their production environments.
Configuration optimization helps determine the optimal number of consolidated workloads that the new centralized storage system can adequately support without over-provisioning or under-provisioning the storage infrastructure.
Pre-production validation with workload modeling accurately simulates how well the target storage systems will perform in production based on a variety of real-world testing scenarios, prior to going live. You can determine ahead of deployment, exactly at what point your storage resources will begin to exceed performance SLA.